diff --git a/docs/about-us/beta-and-experimental-features.md b/docs/about-us/beta-and-experimental-features.md index 311d7d9ed0b..97db696828b 100644 --- a/docs/about-us/beta-and-experimental-features.md +++ b/docs/about-us/beta-and-experimental-features.md @@ -158,6 +158,7 @@ Please note: no additional experimental features are allowed to be enabled in Cl | [enable_replacing_merge_with_cleanup_for_min_age_to_force_merge](/operations/settings/merge-tree-settings#enable_replacing_merge_with_cleanup_for_min_age_to_force_merge) | `0` | | [force_read_through_cache_for_merges](/operations/settings/merge-tree-settings#force_read_through_cache_for_merges) | `0` | | [merge_selector_algorithm](/operations/settings/merge-tree-settings#merge_selector_algorithm) | `Simple` | +| [merge_selector_enable_heuristic_to_lower_max_parts_to_merge_at_once](/operations/settings/merge-tree-settings#merge_selector_enable_heuristic_to_lower_max_parts_to_merge_at_once) | `0` | | [notify_newest_block_number](/operations/settings/merge-tree-settings#notify_newest_block_number) | `0` | | [part_moves_between_shards_delay_seconds](/operations/settings/merge-tree-settings#part_moves_between_shards_delay_seconds) | `30` | | [part_moves_between_shards_enable](/operations/settings/merge-tree-settings#part_moves_between_shards_enable) | `0` | diff --git a/gt-lock.json b/gt-lock.json index d1f86fde02e..06ee8efbc51 100644 --- a/gt-lock.json +++ b/gt-lock.json @@ -49,15 +49,15 @@ }, "a8710471f3f4af77c39b30a518f52a8deb6584069b4bfb8e64158f30627b4792": { "zh": { - "updatedAt": "2025-12-04T20:16:57.006Z", + "updatedAt": "2025-12-07T10:43:20.457Z", "postProcessHash": "dea80e8633a01661415a8f657db721e366107e6372f47980f87efcebec57d84a" }, "ru": { - "updatedAt": "2025-12-04T20:16:57.006Z", + "updatedAt": "2025-12-07T10:43:20.457Z", "postProcessHash": "80b4843e916f7b1e577f8e4b72a589432fbe5af00d6591dc500c49a69d00de25" }, "jp": { - "updatedAt": "2025-12-04T20:16:57.006Z", + 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"2025-12-04T20:16:57.056Z", + "updatedAt": "2025-12-07T10:43:20.508Z", "postProcessHash": "7c296de0f54e7682022f49c1685b45c553b7b55f0435e812ffff18e2d9236460" } } @@ -30751,15 +30897,15 @@ "0e3c84ac0dcb64d166a9e4cad32d3420219fe50fe305e36aa358456c172e2cf7": { "318568dae18d539030ba9900a07a5c387e0ffd38a7b84468080ad1adcdccfc39": { "ru": { - "updatedAt": "2025-12-04T20:16:57.066Z", + "updatedAt": "2025-12-07T10:43:20.528Z", "postProcessHash": "00c46ce01f15ad9fdeab2f72691d4fab5783030e67224ce2bc3767c72f58a420" }, "zh": { - "updatedAt": "2025-12-04T20:16:57.068Z", + "updatedAt": "2025-12-07T10:43:20.531Z", "postProcessHash": "2b9ed3b6e9abe2f5307e8e4356e714558f9d57c5e41f54eb4943c1e669090501" }, "jp": { - "updatedAt": "2025-12-04T20:16:57.052Z", + "updatedAt": "2025-12-07T10:43:20.500Z", "postProcessHash": "30e8ebe13f8b17e8593ba3dd75e594be4c97930c33a5e77c1286bbfe51aeaa97" } } @@ -30767,15 +30913,15 @@ "808e737b87d86c00037ee9499555e8d37bc7fd2e51f5ef796a4a104d5f453b14": { "4719caa724ba0e2a9f5dae16a0fe1e64ccb82cd37762f0d2649a253c1acc65eb": { "zh": { - "updatedAt": "2025-12-04T20:16:57.054Z", + "updatedAt": "2025-12-07T10:43:20.503Z", "postProcessHash": "dbd1e9397e889a9c7f66a1d040df799ad545fe0ff2974b8186c5a2a90b1bd100" }, "ru": { - "updatedAt": "2025-12-04T20:16:57.054Z", + "updatedAt": "2025-12-07T10:43:20.505Z", "postProcessHash": "010fabb308c8285f625f3d634f1941a9e92cd0b5a1a170e9886d7c0caddc17c2" }, "jp": { - "updatedAt": "2025-12-04T20:16:57.052Z", + "updatedAt": "2025-12-07T10:43:20.500Z", "postProcessHash": "4d677cfe542defa2ba654cec1ee86d16b46db800cef2f502ee7fbdb7f4dd8cdc" } } @@ -30790,15 +30936,15 @@ "66bbf0d8525a651b70357530fa66ca0f30073bb1460c57979838338b1c0d8749": { "9a8d534c4d4974d982e6c1d6d31787e905d1215b8eade3bf1524a2e15a6fa2c0": { "jp": { - "updatedAt": "2025-12-04T20:16:58.007Z", + "updatedAt": "2025-12-07T10:43:21.778Z", "postProcessHash": "818e4633c64fa1a38d9ff6344004d822542d1c75f9ca903990b2dcf9352de3c1" }, "ru": { - "updatedAt": "2025-12-04T20:16:58.007Z", + "updatedAt": "2025-12-07T10:43:21.778Z", "postProcessHash": "3074f61c403e9ebcde3ca106438c8b0831b3ed985093f361160cce11270f7c5a" }, "zh": { - "updatedAt": "2025-12-04T20:16:58.007Z", + "updatedAt": "2025-12-07T10:43:21.778Z", "postProcessHash": "d198a414e81c93bac339df3d0c993ae01ae0b8e4b92cda3d4cc695d15b0343b6" } } @@ -30806,15 +30952,15 @@ "004214d1284aa8fe518aa336fea065f912357ada315224cb8c2c05631ff36449": { "1f8a48298f98b2b8149a2007bd5ec17c019f567f61d697e95322a03baab80eba": { "ru": { - "updatedAt": "2025-12-04T20:16:57.265Z", + "updatedAt": "2025-12-07T10:43:21.085Z", "postProcessHash": "8ab59d531a0f8bfeb4e02dae478702f215be910deadfdcf075371cf2a6557076" }, "jp": { - "updatedAt": "2025-12-04T20:16:57.232Z", + "updatedAt": "2025-12-07T10:43:21.037Z", "postProcessHash": "121388e7b53fdf557c939937c2e0567b38ef9a19aef02c417160cdc13ca3e55a" }, "zh": { - "updatedAt": "2025-12-04T20:16:57.265Z", + "updatedAt": "2025-12-07T10:43:21.085Z", "postProcessHash": "c5711362aadc931422448731f50ed222c7123e7cdcae547136368bae2efa9752" } } @@ -30822,15 +30968,15 @@ "0e53576e2d568d32de6d52366ca09d6d3d3b9244b9b950224874f63b7def8e0b": { "4f03aabba29c1d276fbd55f6443c7d1e281d6d6d68ae1d946877245547ca2157": { "zh": { - "updatedAt": "2025-12-04T20:16:57.724Z", + "updatedAt": "2025-12-07T10:43:21.524Z", "postProcessHash": "6a351e20558b6425dae5c0dd4c9dd4d76e78135a678346264493846826c7795a" }, "jp": { - "updatedAt": "2025-12-04T20:16:57.724Z", + "updatedAt": "2025-12-07T10:43:21.524Z", "postProcessHash": "9374f3df5c0b7a3c476f022124892fd637f67d6abece5bef9a553610072963f2" }, "ru": { - "updatedAt": "2025-12-04T20:16:57.724Z", + "updatedAt": "2025-12-07T10:43:21.524Z", "postProcessHash": "da35376e1f288ce3c7c7dc29ccd29ae448afc5e42a2ff36e5d34b2b89f6cffd4" } } @@ -30838,15 +30984,15 @@ "2ed9dd905d29a21da9ab592836fca34a8ed19a4db4490a78058048382b846b88": { "48c110e866cf2a664e3dab6a338d16c6af206ae8ef6c018c3017a83854065ed6": { "zh": { - "updatedAt": "2025-12-04T20:16:58.024Z", + "updatedAt": "2025-12-07T10:43:21.796Z", "postProcessHash": "85bbca18e559edf4f82155f736f8f834e720ba9578601b8ec7b68c8e1499d61a" }, "jp": { - "updatedAt": "2025-12-04T20:16:58.024Z", + "updatedAt": "2025-12-07T10:43:21.796Z", "postProcessHash": "184917ddc8ce0e0945644630ea8c8d0bb18384a8874c3063419f1ac6952a267d" }, "ru": { - "updatedAt": "2025-12-04T20:16:58.025Z", + "updatedAt": "2025-12-07T10:43:21.797Z", "postProcessHash": "85f233e1234be55a3c231a18a5bf5902315fb78d73a68fe43fca7826f3f601a3" } } @@ -30865,15 +31011,15 @@ }, "555a83de7b1fedbbe92860951f89c33d800c65562d765e18c773348463b9d4b1": { "ru": { - "updatedAt": "2025-12-04T20:16:57.347Z", + "updatedAt": "2025-12-07T10:43:21.231Z", "postProcessHash": "066af3c924b8a1250e88d2a27f16f53b507e0e9617a80a2a2b39f5ae891cb83e" }, "jp": { - "updatedAt": "2025-12-04T20:16:57.347Z", + "updatedAt": "2025-12-07T10:43:21.231Z", "postProcessHash": "b4cb559387b02cea9e01ec9df786d8fc50eec0d6812133631e63900a442aa537" }, "zh": { - "updatedAt": "2025-12-04T20:16:57.347Z", + "updatedAt": "2025-12-07T10:43:21.231Z", "postProcessHash": "4e83cadff41e2a0c707e45df7b711b0e0e964bf60b1a4b03f5e71b666d40d8b1" } } @@ -30881,15 +31027,15 @@ "4512096e994b4597d26312dcc20aaa261a25d919afc1ca576d81943eb7dba5e8": { "576c6b22e45a20fa5f3f50de6a9f620190ca1b7786a288fd05ea72e443dae788": { "ru": { - "updatedAt": "2025-12-04T20:16:57.192Z", + "updatedAt": "2025-12-07T10:43:20.929Z", "postProcessHash": "029d7772bdb14d0cc2ca4ecd00965c2dd784bf2737c76648f3b83e2759635ab2" }, "zh": { - "updatedAt": "2025-12-04T20:16:57.192Z", + "updatedAt": "2025-12-07T10:43:20.929Z", "postProcessHash": "87b394d8ba23742c70b4892f614c9b2af257a3ed57ec33b408023a5a240c200b" }, "jp": { - "updatedAt": "2025-12-04T20:16:57.192Z", + "updatedAt": "2025-12-07T10:43:20.929Z", "postProcessHash": "89a6704010a470d3ca4894395bb7ba76be226d708320c4469a6d9e73d2719fac" } } @@ -30897,15 +31043,15 @@ "9b80672ce4026210dce9b9fc8dcdd3cc250a0a78eb37e87ce9abe3344154ce7e": { "9f070809829dec1b3881cdd3a76e90a0533684952dfa123150bed063c8156ad3": { "zh": { - "updatedAt": "2025-12-04T20:16:58.129Z", + "updatedAt": "2025-12-07T10:43:21.864Z", "postProcessHash": "0994ddd9d6117cf05d60f206499af364ed1976ebcdf1aa459354f33559442e6a" }, "ru": { - "updatedAt": "2025-12-04T20:16:58.129Z", + "updatedAt": "2025-12-07T10:43:21.864Z", "postProcessHash": "2c6541332e0756a46b93d6c3f0ad0489bedce7ac204bb4a42658148411433625" }, "jp": { - "updatedAt": "2025-12-04T20:16:58.129Z", + "updatedAt": "2025-12-07T10:43:21.864Z", "postProcessHash": "1b9b45c62e0d849d1af07fdbdaf20aad3a08a4a6a8cd0c474fc00bc1ccf9732b" } } diff --git a/i18n/jp/docusaurus-plugin-content-docs/current/about-us/beta-and-experimental-features.md b/i18n/jp/docusaurus-plugin-content-docs/current/about-us/beta-and-experimental-features.md index 344f52224e1..25fd036d1db 100644 --- a/i18n/jp/docusaurus-plugin-content-docs/current/about-us/beta-and-experimental-features.md +++ b/i18n/jp/docusaurus-plugin-content-docs/current/about-us/beta-and-experimental-features.md @@ -94,76 +94,77 @@ ClickHouse はオープンソースであるため、ClickHouse の従業員だ ## 実験的設定 {#experimental-settings} -| 名前 | デフォルト | -| ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------- | -| [allow_experimental_replacing_merge_with_cleanup](/operations/settings/merge-tree-settings#allow_experimental_replacing_merge_with_cleanup) | `0` | -| [allow_experimental_reverse_key](/operations/settings/merge-tree-settings#allow_experimental_reverse_key) | `0` | -| [allow_remote_fs_zero_copy_replication](/operations/settings/merge-tree-settings#allow_remote_fs_zero_copy_replication) | `0` | -| [enable_replacing_merge_with_cleanup_for_min_age_to_force_merge](/operations/settings/merge-tree-settings#enable_replacing_merge_with_cleanup_for_min_age_to_force_merge) | `0` | -| [force_read_through_cache_for_merges](/operations/settings/merge-tree-settings#force_read_through_cache_for_merges) | `0` | -| [merge_selector_algorithm](/operations/settings/merge-tree-settings#merge_selector_algorithm) | `シンプル` | -| [notify_newest_block_number](/operations/settings/merge-tree-settings#notify_newest_block_number) | `0` | -| [part_moves_between_shards_delay_seconds](/operations/settings/merge-tree-settings#part_moves_between_shards_delay_seconds) | `30` | -| [part_moves_between_shards_enable](/operations/settings/merge-tree-settings#part_moves_between_shards_enable) | `0` | -| [remote_fs_zero_copy_path_compatible_mode](/operations/settings/merge-tree-settings#remote_fs_zero_copy_path_compatible_mode) | `0` | -| [remote_fs_zero_copy_zookeeper_path](/operations/settings/merge-tree-settings#remote_fs_zero_copy_zookeeper_path) | `/clickhouse/zero_copy` | -| [remove_rolled_back_parts_immediately](/operations/settings/merge-tree-settings#remove_rolled_back_parts_immediately) | `1` | -| [shared_merge_tree_virtual_parts_discovery_batch](/operations/settings/merge-tree-settings#shared_merge_tree_virtual_parts_discovery_batch) | `1` | -| [allow_experimental_kafka_offsets_storage_in_keeper](/operations/settings/settings#allow_experimental_kafka_offsets_storage_in_keeper) | `0` | -| [allow_experimental_delta_lake_writes](/operations/settings/settings#allow_experimental_delta_lake_writes) | `0` | -| [allow_experimental_materialized_postgresql_table](/operations/settings/settings#allow_experimental_materialized_postgresql_table) | `0` | -| [allow_experimental_funnel_functions](/operations/settings/settings#allow_experimental_funnel_functions) | `0` | -| [allow_experimental_nlp_functions](/operations/settings/settings#allow_experimental_nlp_functions) | `0` | -| [allow_experimental_hash_functions](/operations/settings/settings#allow_experimental_hash_functions) | `0` | -| [allow_experimental_time_series_table](/operations/settings/settings#allow_experimental_time_series_table) | `0` | -| [allow_experimental_codecs](/operations/settings/settings#allow_experimental_codecs) | `0` | -| [throw_on_unsupported_query_inside_transaction](/operations/settings/settings#throw_on_unsupported_query_inside_transaction) | `1` | -| [wait_changes_become_visible_after_commit_mode](/operations/settings/settings#wait_changes_become_visible_after_commit_mode) | `wait_unknown` | -| [implicit_transaction](/operations/settings/settings#implicit_transaction) | `0` | -| [grace_hash_join_initial_buckets](/operations/settings/settings#grace_hash_join_initial_buckets) | `1` | -| [grace_hash_join_max_buckets](/operations/settings/settings#grace_hash_join_max_buckets) | `1024` | -| [join_to_sort_minimum_perkey_rows](/operations/settings/settings#join_to_sort_minimum_perkey_rows) | `40` | -| [join_to_sort_maximum_table_rows](/operations/settings/settings#join_to_sort_maximum_table_rows) | `10000` | -| [allow_experimental_join_right_table_sorting](/operations/settings/settings#allow_experimental_join_right_table_sorting) | `0` | -| [allow_experimental_statistics](/operations/settings/settings#allow_experimental_statistics) | `0` | -| [use_statistics_cache](/operations/settings/settings#use_statistics_cache) | `0` | -| [allow_experimental_full_text_index](/operations/settings/settings#allow_experimental_full_text_index) | `0` | -| [allow_experimental_window_view](/operations/settings/settings#allow_experimental_window_view) | `0` | -| [window_view_clean_interval](/operations/settings/settings#window_view_clean_interval) | `60` | -| [window_view_heartbeat_interval](/operations/settings/settings#window_view_heartbeat_interval) | `15` | -| [wait_for_window_view_fire_signal_timeout](/operations/settings/settings#wait_for_window_view_fire_signal_timeout) | `10` | -| [stop_refreshable_materialized_views_on_startup](/operations/settings/settings#stop_refreshable_materialized_views_on_startup) | `0` | -| [allow_experimental_database_materialized_postgresql](/operations/settings/settings#allow_experimental_database_materialized_postgresql) | `0` | -| [allow_experimental_qbit_type](/operations/settings/settings#allow_experimental_qbit_type) | `0` | -| [allow_experimental_query_deduplication](/operations/settings/settings#allow_experimental_query_deduplication) | `0` | -| [allow_experimental_database_hms_catalog](/operations/settings/settings#allow_experimental_database_hms_catalog) | `0` | -| [allow_experimental_kusto_dialect](/operations/settings/settings#allow_experimental_kusto_dialect) | `0` | -| [allow_experimental_prql_dialect](/operations/settings/settings#allow_experimental_prql_dialect) | `0` | -| [enable_adaptive_memory_spill_scheduler](/operations/settings/settings#enable_adaptive_memory_spill_scheduler) | `0` | -| [allow_experimental_insert_into_iceberg](/operations/settings/settings#allow_experimental_insert_into_iceberg) | `0` | -| [allow_experimental_iceberg_compaction](/operations/settings/settings#allow_experimental_iceberg_compaction) | `0` | -| [write_full_path_in_iceberg_metadata](/operations/settings/settings#write_full_path_in_iceberg_metadata) | `0` | -| [iceberg_metadata_compression_method](/operations/settings/settings#iceberg_metadata_compression_method) | `` | -| [make_distributed_plan](/operations/settings/settings#make_distributed_plan) | `0` | -| [distributed_plan_execute_locally](/operations/settings/settings#distributed_plan_execute_locally) | `0` | -| [distributed_plan_default_shuffle_join_bucket_count](/operations/settings/settings#distributed_plan_default_shuffle_join_bucket_count) | `8` | -| [distributed_plan_default_reader_bucket_count](/operations/settings/settings#distributed_plan_default_reader_bucket_count) | `8` | -| [distributed_plan_force_exchange_kind](/operations/settings/settings#distributed_plan_force_exchange_kind) | `` | -| [distributed_plan_max_rows_to_broadcast](/operations/settings/settings#distributed_plan_max_rows_to_broadcast) | `20000` | -| [allow_experimental_ytsaurus_table_engine](/operations/settings/settings#allow_experimental_ytsaurus_table_engine) | `0` | -| [allow_experimental_ytsaurus_table_function](/operations/settings/settings#allow_experimental_ytsaurus_table_function) | `0` | -| [allow_experimental_ytsaurus_dictionary_source](/operations/settings/settings#allow_experimental_ytsaurus_dictionary_source) | `0` | -| [distributed_plan_force_shuffle_aggregation](/operations/settings/settings#distributed_plan_force_shuffle_aggregation) | `0` | -| [enable_join_runtime_filters](/operations/settings/settings#enable_join_runtime_filters) | `0` | -| [join_runtime_filter_exact_values_limit](/operations/settings/settings#join_runtime_filter_exact_values_limit) | `10000` | -| [join_runtime_bloom_filter_bytes](/operations/settings/settings#join_runtime_bloom_filter_bytes) | `524288` | -| [join_runtime_bloom_filter_hash_functions](/operations/settings/settings#join_runtime_bloom_filter_hash_functions) | `3` | -| [rewrite_in_to_join](/operations/settings/settings#rewrite_in_to_join) | `0` | -| [allow_experimental_time_series_aggregate_functions](/operations/settings/settings#allow_experimental_time_series_aggregate_functions) | `0` | -| [promql_database](/operations/settings/settings#promql_database) | `` | -| [promql_table](/operations/settings/settings#promql_table) | `` | -| [promql_evaluation_time](/operations/settings/settings#promql_evaluation_time) | `auto` | -| [allow_experimental_alias_table_engine](/operations/settings/settings#allow_experimental_alias_table_engine) | `0` | -| [use_paimon_partition_pruning](/operations/settings/settings#use_paimon_partition_pruning) | `0` | +| 名前 | デフォルト | +| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------- | +| [allow_experimental_kafka_offsets_storage_in_keeper](/operations/settings/settings#allow_experimental_kafka_offsets_storage_in_keeper) | `0` | +| [allow_experimental_delta_lake_writes](/operations/settings/settings#allow_experimental_delta_lake_writes) | `0` | +| [allow_experimental_materialized_postgresql_table](/operations/settings/settings#allow_experimental_materialized_postgresql_table) | `0` | +| [allow_experimental_funnel_functions](/operations/settings/settings#allow_experimental_funnel_functions) | `0` | +| [allow_experimental_nlp_functions](/operations/settings/settings#allow_experimental_nlp_functions) | `0` | +| [allow_experimental_hash_functions](/operations/settings/settings#allow_experimental_hash_functions) | `0` | +| [allow_experimental_time_series_table](/operations/settings/settings#allow_experimental_time_series_table) | `0` | +| [allow_experimental_codecs](/operations/settings/settings#allow_experimental_codecs) | `0` | +| [throw_on_unsupported_query_inside_transaction](/operations/settings/settings#throw_on_unsupported_query_inside_transaction) | `1` | +| [wait_changes_become_visible_after_commit_mode](/operations/settings/settings#wait_changes_become_visible_after_commit_mode) | `wait_unknown` | +| [implicit_transaction](/operations/settings/settings#implicit_transaction) | `0` | +| [grace_hash_join_initial_buckets](/operations/settings/settings#grace_hash_join_initial_buckets) | `1` | +| [grace_hash_join_max_buckets](/operations/settings/settings#grace_hash_join_max_buckets) | `1024` | +| [join_to_sort_minimum_perkey_rows](/operations/settings/settings#join_to_sort_minimum_perkey_rows) | `40` | +| [join_to_sort_maximum_table_rows](/operations/settings/settings#join_to_sort_maximum_table_rows) | `10000` | +| [allow_experimental_join_right_table_sorting](/operations/settings/settings#allow_experimental_join_right_table_sorting) | `0` | +| [allow_experimental_statistics](/operations/settings/settings#allow_experimental_statistics) | `0` | +| [use_statistics_cache](/operations/settings/settings#use_statistics_cache) | `0` | +| [allow_experimental_full_text_index](/operations/settings/settings#allow_experimental_full_text_index) | `0` | +| [allow_experimental_window_view](/operations/settings/settings#allow_experimental_window_view) | `0` | +| [window_view_clean_interval](/operations/settings/settings#window_view_clean_interval) | `60` | +| [window_view_heartbeat_interval](/operations/settings/settings#window_view_heartbeat_interval) | `15` | +| [wait_for_window_view_fire_signal_timeout](/operations/settings/settings#wait_for_window_view_fire_signal_timeout) | `10` | +| [stop_refreshable_materialized_views_on_startup](/operations/settings/settings#stop_refreshable_materialized_views_on_startup) | `0` | +| [allow_experimental_database_materialized_postgresql](/operations/settings/settings#allow_experimental_database_materialized_postgresql) | `0` | +| [allow_experimental_qbit_type](/operations/settings/settings#allow_experimental_qbit_type) | `0` | +| [allow_experimental_query_deduplication](/operations/settings/settings#allow_experimental_query_deduplication) | `0` | +| [allow_experimental_database_hms_catalog](/operations/settings/settings#allow_experimental_database_hms_catalog) | `0` | +| [allow_experimental_kusto_dialect](/operations/settings/settings#allow_experimental_kusto_dialect) | `0` | +| [allow_experimental_prql_dialect](/operations/settings/settings#allow_experimental_prql_dialect) | `0` | +| [enable_adaptive_memory_spill_scheduler](/operations/settings/settings#enable_adaptive_memory_spill_scheduler) | `0` | +| [allow_experimental_insert_into_iceberg](/operations/settings/settings#allow_experimental_insert_into_iceberg) | `0` | +| [allow_experimental_iceberg_compaction](/operations/settings/settings#allow_experimental_iceberg_compaction) | `0` | +| [write_full_path_in_iceberg_metadata](/operations/settings/settings#write_full_path_in_iceberg_metadata) | `0` | +| [iceberg_metadata_compression_method](/operations/settings/settings#iceberg_metadata_compression_method) | `` | +| [make_distributed_plan](/operations/settings/settings#make_distributed_plan) | `0` | +| [distributed_plan_execute_locally](/operations/settings/settings#distributed_plan_execute_locally) | `0` | +| [distributed_plan_default_shuffle_join_bucket_count](/operations/settings/settings#distributed_plan_default_shuffle_join_bucket_count) | `8` | +| [distributed_plan_default_reader_bucket_count](/operations/settings/settings#distributed_plan_default_reader_bucket_count) | `8` | +| [distributed_plan_force_exchange_kind](/operations/settings/settings#distributed_plan_force_exchange_kind) | `` | +| [distributed_plan_max_rows_to_broadcast](/operations/settings/settings#distributed_plan_max_rows_to_broadcast) | `20000` | +| [allow_experimental_ytsaurus_table_engine](/operations/settings/settings#allow_experimental_ytsaurus_table_engine) | `0` | +| [allow_experimental_ytsaurus_table_function](/operations/settings/settings#allow_experimental_ytsaurus_table_function) | `0` | +| [allow_experimental_ytsaurus_dictionary_source](/operations/settings/settings#allow_experimental_ytsaurus_dictionary_source) | `0` | +| [distributed_plan_force_shuffle_aggregation](/operations/settings/settings#distributed_plan_force_shuffle_aggregation) | `0` | +| [enable_join_runtime_filters](/operations/settings/settings#enable_join_runtime_filters) | `0` | +| [join_runtime_filter_exact_values_limit](/operations/settings/settings#join_runtime_filter_exact_values_limit) | `10000` | +| [join_runtime_bloom_filter_bytes](/operations/settings/settings#join_runtime_bloom_filter_bytes) | `524288` | +| [join_runtime_bloom_filter_hash_functions](/operations/settings/settings#join_runtime_bloom_filter_hash_functions) | `3` | +| [rewrite_in_to_join](/operations/settings/settings#rewrite_in_to_join) | `0` | +| [allow_experimental_time_series_aggregate_functions](/operations/settings/settings#allow_experimental_time_series_aggregate_functions) | `0` | +| [promql_database](/operations/settings/settings#promql_database) | `` | +| [promql_table](/operations/settings/settings#promql_table) | `` | +| [promql_evaluation_time](/operations/settings/settings#promql_evaluation_time) | `auto` | +| [allow_experimental_alias_table_engine](/operations/settings/settings#allow_experimental_alias_table_engine) | `0` | +| [use_paimon_partition_pruning](/operations/settings/settings#use_paimon_partition_pruning) | `0` | +| [allow_experimental_replacing_merge_with_cleanup](/operations/settings/merge-tree-settings#allow_experimental_replacing_merge_with_cleanup) | `0` | +| [allow_experimental_reverse_key](/operations/settings/merge-tree-settings#allow_experimental_reverse_key) | `0` | +| [allow_remote_fs_zero_copy_replication](/operations/settings/merge-tree-settings#allow_remote_fs_zero_copy_replication) | `0` | +| [enable_replacing_merge_with_cleanup_for_min_age_to_force_merge](/operations/settings/merge-tree-settings#enable_replacing_merge_with_cleanup_for_min_age_to_force_merge) | `0` | +| [force_read_through_cache_for_merges](/operations/settings/merge-tree-settings#force_read_through_cache_for_merges) | `0` | +| [merge_selector_algorithm](/operations/settings/merge-tree-settings#merge_selector_algorithm) | `シンプル` | +| [merge_selector_enable_heuristic_to_lower_max_parts_to_merge_at_once](/operations/settings/merge-tree-settings#merge_selector_enable_heuristic_to_lower_max_parts_to_merge_at_once) | `0` | +| [notify_newest_block_number](/operations/settings/merge-tree-settings#notify_newest_block_number) | `0` | +| [part_moves_between_shards_delay_seconds](/operations/settings/merge-tree-settings#part_moves_between_shards_delay_seconds) | `30` | +| [part_moves_between_shards_enable](/operations/settings/merge-tree-settings#part_moves_between_shards_enable) | `0` | +| [remote_fs_zero_copy_path_compatible_mode](/operations/settings/merge-tree-settings#remote_fs_zero_copy_path_compatible_mode) | `0` | +| [remote_fs_zero_copy_zookeeper_path](/operations/settings/merge-tree-settings#remote_fs_zero_copy_zookeeper_path) | `/clickhouse/zero_copy` | +| [remove_rolled_back_parts_immediately](/operations/settings/merge-tree-settings#remove_rolled_back_parts_immediately) | `1` | +| [shared_merge_tree_virtual_parts_discovery_batch](/operations/settings/merge-tree-settings#shared_merge_tree_virtual_parts_discovery_batch) | `1` | {/*AUTOGENERATED_END*/ } diff --git a/i18n/jp/docusaurus-plugin-content-docs/current/about-us/history.md b/i18n/jp/docusaurus-plugin-content-docs/current/about-us/history.md index 87a6a865652..02db58ba244 100644 --- a/i18n/jp/docusaurus-plugin-content-docs/current/about-us/history.md +++ b/i18n/jp/docusaurus-plugin-content-docs/current/about-us/history.md @@ -8,8 +8,6 @@ title: 'ClickHouse の歴史' doc_type: 'reference' --- - - # ClickHouse の歴史 {#clickhouse-history} ClickHouse は当初、[Yandex.Metrica](https://metrica.yandex.com/)([世界第 2 位の規模を持つウェブ解析プラットフォーム](http://w3techs.com/technologies/overview/traffic_analysis/all))を支えるために開発され、現在もその中核コンポーネントとして利用されています。データベース内には 13 兆件を超えるレコードが存在し、1 日あたり 200 億件以上のイベントが蓄積されるという規模においても、ClickHouse は非集約データから直接、オンザフライでカスタムレポートを生成することを可能にします。本記事では、ClickHouse 開発初期段階における目標について簡潔に説明します。 @@ -18,8 +16,6 @@ Yandex.Metrica は、ヒットおよびセッションに基づき、ユーザ 2014 年 4 月時点で、Yandex.Metrica は 1 日あたり約 120 億件のイベント(ページビューおよびクリック)を追跡していました。これらすべてのイベントは、カスタムレポートを作成するために保存しておく必要があります。単一のクエリであっても、数百ミリ秒のうちに数百万行、あるいは数秒のうちに数億行をスキャンする必要がある場合がありました。 - - ## Yandex.Metrica およびその他の Yandex サービスでの利用 {#usage-in-yandex-metrica-and-other-yandex-services} ClickHouse は、Yandex.Metrica の中で複数の目的に利用されています。 @@ -35,8 +31,6 @@ ClickHouse は、次のプロセスにおいても重要な役割を果たして 現在では、Yandex のその他のサービスや部門(検索バーティカル、e コマース、広告、ビジネスアナリティクス、モバイル開発、パーソナルサービスなど)においても、数十の ClickHouse インストール環境が稼働しています。 - - ## 集計済みデータと非集計データ {#aggregated-and-non-aggregated-data} 統計を効率的に計算するには、データ量を削減するためにデータを集計しなければならない、という考え方が一般的です。 @@ -60,4 +54,4 @@ Yandex.Metrica には、Metrage と呼ばれるデータ集計専用システム 2009 年からは、非集計データ用の専用 OLAP データベースである OLAPServer も Yandex.Metrica で使用されるようになりました。これは、以前はレポートビルダー向けに使用されていたものです。 OLAPServer は非集計データに対してはうまく動作していましたが、すべてのレポートで期待どおりに利用できない多くの制約がありました。たとえば、さまざまなデータ型をサポートしていない(数値のみを扱える)、データをリアルタイムに増分更新できない(データは毎日書き換えることでしか更新できない)といった制約です。OLAPServer は DBMS ではなく、専用の DB です。 -ClickHouse の当初の目標は、OLAPServer の制約を取り除き、すべてのレポートに対して非集計データを扱う問題を解決することでしたが、年月を経て、幅広い分析タスクに適した汎用的なデータベース管理システムへと成長しました。 +ClickHouse の当初の目標は、OLAPServer の制約を取り除き、すべてのレポートに対して非集計データを扱う問題を解決することでしたが、年月を経て、幅広い分析タスクに適した汎用的なデータベース管理システムへと成長しました。 \ No newline at end of file diff --git a/i18n/jp/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/azure-queue.md b/i18n/jp/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/azure-queue.md index 3fd28dfe261..5e57fba5b64 100644 --- a/i18n/jp/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/azure-queue.md +++ b/i18n/jp/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/azure-queue.md @@ -41,6 +41,7 @@ ENGINE = AzureQueue('DefaultEndpointsProtocol=http;AccountName=devstoreaccount1; SETTINGS mode = 'unordered' ``` + ## Settings {#settings} サポートされている設定項目は、ほとんどが `S3Queue` テーブルエンジンと同じですが、`s3queue_` プレフィックスは付きません。[設定の全リスト](../../../engines/table-engines/integrations/s3queue.md#settings)を参照してください。 @@ -48,7 +49,7 @@ SETTINGS mode = 'unordered' 以下は、AzureQueue にのみ対応し、S3Queue には適用されない設定です。 -### `after_processing_move_connection_string` {#after_processing_move_connection_string} +### `after_processing_move_connection_string` {#after_processing_move_connection_string} 宛先が別の Azure コンテナーである場合に、正常に処理されたファイルを移動するための Azure Blob Storage 接続文字列。 @@ -58,7 +59,7 @@ SETTINGS mode = 'unordered' デフォルト値: 空文字列。 -### `after_processing_move_container` {#after_processing_move_container} +### `after_processing_move_container` {#after_processing_move_container} 移動先が別の Azure コンテナである場合に、正常に処理されたファイルを移動する移動先コンテナ名。 @@ -84,6 +85,13 @@ SETTINGS after_processing_move_container = 'dst-container'; ``` + +## AzureQueue テーブルエンジンからの SELECT {#select} + +AzureQueue テーブルに対する SELECT クエリは、既定では禁止されています。これは、データを一度読み取ったらキューから削除するという一般的なキューの利用パターンに従うためです。誤ってデータを失わないようにする目的で、SELECT は禁止されています。 +ただし、状況によってはこれが必要になる場合もあります。その場合は、SETTING `stream_like_engine_allow_direct_select` を `True` に設定する必要があります。 +AzureQueue エンジンには、SELECT クエリ用の特別な SETTING `commit_on_select` があります。これを `False` に設定すると、読み取り後もキュー内のデータを保持し、`True` に設定すると削除します。 + ## 説明 {#description} `SELECT` は、各ファイルを 1 回しかインポートできないため(デバッグ用途を除き)ストリーミングインポートにはあまり有用ではありません。代わりに、[マテリアライズドビュー](../../../sql-reference/statements/create/view.md) を使用してリアルタイム処理フローを作成する方が実用的です。これを行うには、次のようにします。 @@ -111,6 +119,7 @@ CREATE MATERIALIZED VIEW consumer TO stats SELECT * FROM stats ORDER BY key; ``` + ## 仮想カラム {#virtual-columns} * `_path` — ファイルパス。 @@ -134,7 +143,7 @@ SELECT * FROM stats ORDER BY key; ``` -この永続テーブルは、`system.s3queue` と同様の情報を保持しますが、対象は処理済みおよび失敗したファイルです。 +この永続テーブルは、`system.s3queue` と同じ情報を保持しますが、処理済みおよび失敗したファイルに関するものです。 このテーブルの構造は次のとおりです。 @@ -142,24 +151,24 @@ SELECT * FROM stats ORDER BY key; CREATE TABLE system.azure_queue_log ( - `hostname` LowCardinality(String) COMMENT 'ホスト名', - `event_date` Date COMMENT 'このログ行の書き込みイベント日付', - `event_time` DateTime COMMENT 'このログ行の書き込みイベント時刻', - `database` String COMMENT '現在のS3Queueテーブルが存在するデータベース名。', - `table` String COMMENT 'S3Queueテーブル名。', - `uuid` String COMMENT 'S3QueueテーブルのUUID', - `file_name` String COMMENT '処理対象ファイルのファイル名', - `rows_processed` UInt64 COMMENT '処理された行数', - `status` Enum8('Processed' = 0, 'Failed' = 1) COMMENT 'ファイル処理のステータス', - `processing_start_time` Nullable(DateTime) COMMENT 'ファイル処理の開始時刻', - `processing_end_time` Nullable(DateTime) COMMENT 'ファイル処理の終了時刻', - `exception` String COMMENT '例外が発生した場合の例外メッセージ' + `hostname` LowCardinality(String) COMMENT 'Hostname', + `event_date` Date COMMENT 'Event date of writing this log row', + `event_time` DateTime COMMENT 'Event time of writing this log row', + `database` String COMMENT 'The name of a database where current S3Queue table lives.', + `table` String COMMENT 'The name of S3Queue table.', + `uuid` String COMMENT 'The UUID of S3Queue table', + `file_name` String COMMENT 'File name of the processing file', + `rows_processed` UInt64 COMMENT 'Number of processed rows', + `status` Enum8('Processed' = 0, 'Failed' = 1) COMMENT 'Status of the processing file', + `processing_start_time` Nullable(DateTime) COMMENT 'Time of the start of processing the file', + `processing_end_time` Nullable(DateTime) COMMENT 'Time of the end of processing the file', + `exception` String COMMENT 'Exception message if happened' ) ENGINE = MergeTree PARTITION BY toYYYYMM(event_date) ORDER BY (event_date, event_time) SETTINGS index_granularity = 8192 -COMMENT 'S3Queueエンジンによって処理されるファイルの情報を含むログエントリを格納する。' +COMMENT 'Contains logging entries with the information files processes by S3Queue engine.' ``` @@ -171,7 +180,7 @@ FROM system.azure_queue_log LIMIT 1 FORMAT Vertical -行 1: +Row 1: ────── hostname: clickhouse event_date: 2024-12-16 @@ -186,6 +195,6 @@ processing_start_time: 2024-12-16 13:42:47 processing_end_time: 2024-12-16 13:42:47 exception: -1行が結果セットに含まれています。経過時間: 0.002秒。 +1 row in set. Elapsed: 0.002 sec. ``` diff --git a/i18n/jp/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/s3queue.md b/i18n/jp/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/s3queue.md index 0f056972c0f..4b58f9b5af1 100644 --- a/i18n/jp/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/s3queue.md +++ b/i18n/jp/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/s3queue.md @@ -62,7 +62,7 @@ SETTINGS mode = 'unordered'; ``` -名前付きコレクションの使用: +名前付きコレクションの利用: ```xml @@ -83,20 +83,21 @@ SETTINGS mode = 'ordered'; ``` + ## 設定 {#settings} -テーブルに対して構成された設定の一覧を取得するには、`system.s3_queue_settings` テーブルを使用します。`24.10` 以降で利用可能です。 +テーブルに対して構成されている設定の一覧を取得するには、`system.s3_queue_settings` テーブルを使用します。`24.10` 以降で利用可能です。 ### Mode {#mode} 指定可能な値: -* unordered — `unordered` モードでは、すでに処理されたすべてのファイルの集合が ZooKeeper 内の永続ノードとして管理されます。 +* unordered — `unordered` モードでは、すでに処理されたすべてのファイルの集合が ZooKeeper 内の永続ノードとして追跡されます。 * ordered — `ordered` モードでは、ファイルは辞書順で処理されます。つまり、ファイル名 `BBB` のファイルがある時点で処理され、その後にファイル名 `AA` のファイルがバケットに追加された場合、そのファイルは無視されます。ZooKeeper には、正常に取り込まれたファイル名のうち最大のもの(辞書順での最大値)と、読み込みに失敗して再試行対象となるファイル名のみが保存されます。 -デフォルト値: バージョン 24.6 より前は `ordered`。24.6 以降ではデフォルト値は存在せず、この設定は手動で指定する必要があります。以前のバージョンで作成されたテーブルについては、互換性のためデフォルト値は引き続き `Ordered` のままです。 +デフォルト値: バージョン 24.6 より前は `ordered`。24.6 以降ではデフォルト値は存在せず、この設定の指定が必須になります。以前のバージョンで作成されたテーブルについては、互換性のためデフォルト値は引き続き `Ordered` のままです。 -### `after_processing` {#after_processing} +### `after_processing` {#after_processing} ファイルの処理が正常に完了した後の扱い方法。 @@ -132,7 +133,8 @@ Azure コンテナから別の Azure コンテナに移動するには、Blob St タグ付けを行うには、タグキーと値をそれぞれ `after_processing_tag_key` および `after_processing_tag_value` として指定します。 -### `after_processing_retries` {#after_processing_retries} + +### `after_processing_retries` {#after_processing_retries} 要求された後処理アクションに対して、処理を中止するまでに行う再試行回数。 @@ -142,7 +144,7 @@ Azure コンテナから別の Azure コンテナに移動するには、Blob St デフォルト値: `10`。 -### `after_processing_move_access_key_id` {#after_processing_move_access_key_id} +### `after_processing_move_access_key_id` {#after_processing_move_access_key_id} 移動先が別の S3 バケットである場合に、正常に処理されたファイルをそのバケットへ移動するための Access Key ID。 @@ -152,7 +154,7 @@ Azure コンテナから別の Azure コンテナに移動するには、Blob St デフォルト値: 空文字列。 -### `after_processing_move_prefix` {#after_processing_move_prefix} +### `after_processing_move_prefix` {#after_processing_move_prefix} 正常に処理されたファイルを移動する先のパスプレフィックスです。同一バケット内での移動と、別のバケットへの移動の両方で有効です。 @@ -162,7 +164,7 @@ Azure コンテナから別の Azure コンテナに移動するには、Blob St デフォルト値: 空文字列。 -### `after_processing_move_secret_access_key` {#after_processing_move_secret_access_key} +### `after_processing_move_secret_access_key` {#after_processing_move_secret_access_key} 移動先が別の S3 バケットである場合に、正常に処理されたファイルをそのバケットへ移動するための Secret Access Key。 @@ -172,7 +174,7 @@ Azure コンテナから別の Azure コンテナに移動するには、Blob St デフォルト値: 空文字列。 -### `after_processing_move_uri` {#after_processing_move_uri} +### `after_processing_move_uri` {#after_processing_move_uri} 宛先が別の S3 バケットである場合に、正常に処理されたファイルを移動する先となる S3 バケットの URI。 @@ -182,7 +184,7 @@ Azure コンテナから別の Azure コンテナに移動するには、Blob St デフォルト値: 空文字列。 -### `after_processing_tag_key` {#after_processing_tag_key} +### `after_processing_tag_key` {#after_processing_tag_key} `after_processing='tag'` の場合に、正常に処理されたファイルへタグ付けを行うためのタグキー。 @@ -192,7 +194,7 @@ Azure コンテナから別の Azure コンテナに移動するには、Blob St デフォルト値: 空文字列。 -### `after_processing_tag_value` {#after_processing_tag_value} +### `after_processing_tag_value` {#after_processing_tag_value} `after_processing` が `tag` の場合に、正常に処理されたファイルに付与するタグ値。 @@ -202,10 +204,10 @@ Azure コンテナから別の Azure コンテナに移動するには、Blob St デフォルト値: 空文字列。 -### `keeper_path` {#keeper_path} +### `keeper_path` {#keeper_path} ZooKeeper 内のパスはテーブルエンジンの設定として指定するか、グローバル設定で指定されたパスとテーブル UUID から既定パスを生成できます。 -取りうる値: +取り得る値: * 文字列。 @@ -220,13 +222,13 @@ ZooKeeper 内のパスはテーブルエンジンの設定として指定する デフォルト値: `0`。 -### `s3queue_processing_threads_num` {#processing_threads_num} +### `s3queue_processing_threads_num` {#processing_threads_num} 処理を実行するスレッド数。`Unordered` モードでのみ適用されます。 デフォルト値: CPU の数または 16。 -### `s3queue_parallel_inserts` {#parallel_inserts} +### `s3queue_parallel_inserts` {#parallel_inserts} デフォルトでは、`processing_threads_num` は 1 つの `INSERT` しか生成されないため、複数スレッドで実行されるのはファイルのダウンロードとパース処理だけです。 しかし、これは並列度を制限するため、スループットを向上させるには `parallel_inserts=true` を使用してください。これによりデータを並列に挿入できるようになります(ただし、その結果として MergeTree ファミリーのテーブルに対して生成されるデータパーツの数が増加する点に注意してください)。 @@ -237,7 +239,7 @@ ZooKeeper 内のパスはテーブルエンジンの設定として指定する デフォルト値: `false`。 -### `s3queue_enable_logging_to_s3queue_log` {#enable_logging_to_s3queue_log} +### `s3queue_enable_logging_to_s3queue_log` {#enable_logging_to_s3queue_log} `system.s3queue_log` へのログ記録を有効にします。 @@ -253,7 +255,7 @@ ClickHouse が次のポーリングを実行する前に待機する最小時間 デフォルト値: `1000`。 -### `s3queue_polling_max_timeout_ms` {#polling_max_timeout_ms} +### `s3queue_polling_max_timeout_ms` {#polling_max_timeout_ms} ClickHouse が次のポーリング試行を開始するまでに待機する最大時間を、ミリ秒単位で定義します。 @@ -261,9 +263,9 @@ ClickHouse が次のポーリング試行を開始するまでに待機する最 * 正の整数。 -デフォルト値: `10000`. +デフォルト値: `10000`。 -### `s3queue_polling_backoff_ms` {#polling_backoff_ms} +### `s3queue_polling_backoff_ms` {#polling_backoff_ms} 新しいファイルが見つからなかった場合に、前回のポーリング間隔に追加される待機時間を決定します。次回のポーリングは、前回の間隔にこのバックオフ値を加えた値と最大間隔のうち、短い方の時間が経過した後に行われます。 @@ -273,12 +275,12 @@ ClickHouse が次のポーリング試行を開始するまでに待機する最 デフォルト値: `0`。 -### `s3queue_tracked_files_limit` {#tracked_files_limit} +### `s3queue_tracked_files_limit` {#tracked_files_limit} `unordered` モードが使用されている場合に、ZooKeeper ノードの数に上限を設けるための設定です。`ordered` モードでは何も行いません。 上限に達した場合、最も古く処理されたファイルが ZooKeeper ノードから削除され、再度処理されます。 -取り得る値: +設定可能な値: * 正の整数。 @@ -297,11 +299,11 @@ ClickHouse が次のポーリング試行を開始するまでに待機する最 ### `s3queue_cleanup_interval_min_ms` {#cleanup_interval_min_ms} -'Ordered' モード用。追跡対象ファイルの TTL および追跡対象ファイル集合の最大数を維持するバックグラウンドタスクについて、その再スケジュールの間隔の下限値を定義します。 +'Ordered' モード用。追跡対象ファイルの TTL および追跡対象ファイル集合の最大数を維持するバックグラウンドタスクについて、その再スケジュールの間隔の下限値を定義します。 デフォルト値: `10000`。 -### `s3queue_cleanup_interval_max_ms` {#cleanup_interval_max_ms} +### `s3queue_cleanup_interval_max_ms` {#cleanup_interval_max_ms} 「Ordered」モード用。追跡対象ファイルの TTL と、追跡対象ファイル集合の最大数を維持するバックグラウンドタスクの再スケジュール間隔に対する上限値を定義します。 @@ -309,13 +311,13 @@ ClickHouse が次のポーリング試行を開始するまでに待機する最 ### `s3queue_buckets` {#buckets} -「Ordered」モードで使用します。`24.6` から利用可能です。S3Queue テーブルのレプリカが複数あり、それぞれが keeper 内の同一のメタデータディレクトリを使用している場合、`s3queue_buckets` の値はレプリカ数以上に設定する必要があります。`s3queue_processing_threads` 設定も併用している場合は、`S3Queue` の処理における実際の並列度を決定するため、`s3queue_buckets` 設定の値をさらに大きくすることが推奨されます。 +「Ordered」モードで使用します。`24.6` から利用可能です。S3Queue テーブルのレプリカが複数あり、それぞれが keeper 内の同一のメタデータディレクトリを使用している場合、`s3queue_buckets` の値はレプリカ数以上に設定する必要があります。`s3queue_processing_threads` 設定も併用している場合は、`S3Queue` の処理における実際の並列度合いをこの設定が決定するため、`s3queue_buckets` 設定の値をさらに大きくすることが推奨されます。 -### `use_persistent_processing_nodes` {#use_persistent_processing_nodes} +### `use_persistent_processing_nodes` {#use_persistent_processing_nodes} -デフォルトでは、S3Queue テーブルは常に一時的な処理ノードを使用しており、ZooKeeper セッションが、S3Queue が処理済みファイルを ZooKeeper にコミットする前に期限切れになり、かつ処理は開始されていた場合、データが重複する可能性がありました。この設定は、keeper セッションの期限切れに起因する重複が発生しないよう、サーバーに強制します。 +デフォルトでは、S3Queue テーブルは常に一時的な処理ノードを使用しており、ZooKeeper セッションが、S3Queue が処理済みファイルを ZooKeeper にコミットする前に期限切れになり、かつ処理は開始されていた場合、データが重複する可能性がありました。この設定により、Keeper セッションの期限切れに起因する重複が発生しないようサーバーを強制的に動作させます。 -### `persistent_processing_nodes_ttl_seconds` {#persistent_processing_nodes_ttl_seconds} +### `persistent_processing_nodes_ttl_seconds` {#persistent_processing_nodes_ttl_seconds} サーバーが正常終了しなかった場合、`use_persistent_processing_nodes` が有効になっていると、処理ノードが削除されずに残る可能性があります。この設定は、それらの処理ノードを安全にクリーンアップできる猶予時間を定義します。 @@ -323,7 +325,7 @@ ClickHouse が次のポーリング試行を開始するまでに待機する最 ## S3 に関連する設定 {#s3-settings} -このエンジンでは、すべての S3 関連設定が利用できます。S3 設定の詳細は[こちら](../../../engines/table-engines/integrations/s3.md)を参照してください。 +このエンジンは、すべての S3 関連の設定をサポートしています。S3 に関する設定の詳細は[こちら](../../../engines/table-engines/integrations/s3.md)を参照してください。 ## S3 ロールベースアクセス {#s3-role-based-access} @@ -348,6 +350,7 @@ SETTINGS ... ``` + ## S3Queue の ordered モード {#ordered-mode} `S3Queue` の処理モードでは、ZooKeeper に保存するメタデータ量を減らせますが、時間的に後から追加されるファイルの名前は、英数字としてそれ以前のファイル名より大きくなる必要があるという制約があります。 @@ -357,6 +360,12 @@ SETTINGS `(s3queue_)processing_threads_num` 設定は、バージョン `24.6` より前での使用は推奨されません。 `(s3queue_)buckets` 設定は、バージョン `24.6` から利用可能です。 +## S3Queue テーブルエンジンからの SELECT {#select} + +S3Queue テーブルに対する SELECT クエリは、デフォルトでは禁止されています。これは、データを 1 回だけ読み取り、その後キューから削除するという一般的なキューのパターンに従うためです。SELECT を禁止することで、誤ってデータを失うことを防ぎます。 +ただし、場合によってはこれが役立つこともあります。そのためには、`stream_like_engine_allow_direct_select` 設定を `True` にする必要があります。 +S3Queue エンジンには、SELECT クエリ用の特別な設定 `commit_on_select` があります。これを `False` に設定すると、読み取り後もデータをキューに保持し、`True` に設定すると削除します。 + ## 説明 {#description} `SELECT` は、各ファイルを 1 回しかインポートできないため(デバッグ用途を除いて)ストリーミングインポートにはあまり有用ではありません。代わりに、[マテリアライズドビュー](../../../sql-reference/statements/create/view.md) を使ってリアルタイムの処理フローを作成する方が実用的です。そのためには次のようにします。 @@ -384,6 +393,7 @@ SETTINGS SELECT * FROM stats ORDER BY name; ``` + ## 仮想カラム {#virtual-columns} * `_path` — ファイルへのパス。 @@ -407,15 +417,15 @@ SETTINGS ## 制限事項 {#limitations} -1. 行の重複は以下の要因により発生する可能性があります: +1. 行の重複は以下の要因により発生する可能性があります: -* ファイル処理の途中でパース中に例外が発生し、`s3queue_loading_retries` によってリトライが有効になっている場合。 +* ファイル処理の途中のパース時に例外が発生し、`s3queue_loading_retries` によってリトライが有効になっている場合。 -* 複数のサーバーで同じ zookeeper のパスを指すように `S3Queue` が構成されており、1つのサーバーが処理済みファイルをコミットする前に keeper セッションが期限切れになった場合。これにより、別のサーバーがそのファイルの処理を引き継ぐ可能性があり、そのファイルは最初のサーバーによって部分的または完全に処理されている場合があります。ただし、バージョン 25.8 以降で `use_persistent_processing_nodes = 1` が設定されている場合、これは発生しません。 +* 複数のサーバーで同じ ZooKeeper のパスを指すように `S3Queue` が構成されており、1つのサーバーが処理済みファイルをコミットする前に Keeper セッションが期限切れになった場合。これにより、別のサーバーがそのファイルの処理を引き継ぐ可能性があり、そのファイルは最初のサーバーによって部分的または完全に処理されている場合があります。ただし、バージョン 25.8 以降で `use_persistent_processing_nodes = 1` が設定されている場合、これは発生しません。 * サーバーの異常終了。 -2. 複数のサーバーで同じ zookeeper のパスを指すように `S3Queue` が構成されており、かつ `Ordered` モードが使用されている場合、`s3queue_loading_retries` は動作しません。これは近いうちに修正される予定です。 +2. 複数のサーバーで同じ ZooKeeper のパスを指すように `S3Queue` が構成されており、かつ `Ordered` モードが使用されている場合、`s3queue_loading_retries` は動作しません。これは近いうちに修正される予定です。 ## 内部状態の確認 {#introspection} @@ -438,7 +448,7 @@ SETTINGS `exception` String ) ENGINE = SystemS3Queue -COMMENT 'S3Queueメタデータのインメモリ状態と、ファイルごとに現在処理されている行を含みます。' │ +COMMENT 'Contains in-memory state of S3Queue metadata and currently processed rows per file.' │ └────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘ ``` @@ -468,7 +478,7 @@ exception: ```sql SHOW CREATE TABLE system.s3queue_log -クエリ ID: 0ad619c3-0f2a-4ee4-8b40-c73d86e04314 +Query id: 0ad619c3-0f2a-4ee4-8b40-c73d86e04314 ┌─statement──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐ │ CREATE TABLE system.s3queue_log @@ -491,7 +501,7 @@ SETTINGS index_granularity = 8192 │ └────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘ ``` -`system.s3queue_log` を使用するには、サーバーの設定ファイルでその構成を定義してください。 +`system.s3queue_log` を使用するには、サーバーの設定ファイルでその設定を定義する必要があります。 ```xml @@ -500,7 +510,7 @@ SETTINGS index_granularity = 8192 │ ``` -例: +例: ```sql SELECT * diff --git a/i18n/jp/docusaurus-plugin-content-docs/current/interfaces/formats.md b/i18n/jp/docusaurus-plugin-content-docs/current/interfaces/formats.md index 6cd9bbf893d..8d9bcab6226 100644 --- a/i18n/jp/docusaurus-plugin-content-docs/current/interfaces/formats.md +++ b/i18n/jp/docusaurus-plugin-content-docs/current/interfaces/formats.md @@ -9,13 +9,10 @@ doc_type: 'reference' import CloudNotSupportedBadge from '@theme/badges/CloudNotSupportedBadge'; - # 入力および出力データのフォーマット {#formats-for-input-and-output-data} ClickHouse は、一般的なテキスト形式およびバイナリ形式のほとんどをサポートしています。これにより、運用中のほぼあらゆるデータパイプラインに容易に統合し、ClickHouse の利点を活用できます。 - - ## 入力フォーマット {#input-formats} 入力フォーマットは次の用途に使用されます: @@ -34,22 +31,16 @@ ClickHouse にデータを効率的にインジェストするには、適切な 完全版の [ベンチマーク分析](https://www.clickhouse.com/blog/clickhouse-input-format-matchup-which-is-fastest-most-efficient) を参照してください。 テスト結果の全体像は、[FastFormats](https://fastformats.clickhouse.com/) のオンラインダッシュボードで確認できます。 - - ## 出力形式 {#output-formats} 出力としてサポートされている形式は、次の用途に使用されます: - `SELECT` クエリ結果の整形 - ファイルベースのテーブルへの `INSERT` 操作の実行 - - ## フォーマットの概要 {#formats-overview} サポートされているフォーマットは以下のとおりです。 - - | フォーマット | 入力 | 出力 | | ---------------------------------------------------------------------------------------------------------- | -- | -- | | [TabSeparated](./formats/TabSeparated/TabSeparated.md) | ✔ | ✔ | @@ -139,12 +130,8 @@ ClickHouse にデータを効率的にインジェストするには、適切な | [Markdown](./formats/Markdown.md) | ✗ | ✔ | | [フォーム](./formats/Form.md) | ✔ | ✗ | - - ClickHouse の設定を使用して、一部のフォーマット処理パラメータを制御できます。詳細については、[Settings](/operations/settings/settings-formats.md) セクションを参照してください。 - - ## フォーマットスキーマ {#formatschema} フォーマットスキーマを格納したファイル名は、設定 `format_schema` で指定します。 @@ -160,8 +147,6 @@ ClickHouse の設定を使用して、一部のフォーマット処理パラメ [HTTP インターフェイス](/interfaces/http.md)経由でデータを入力または出力する場合、フォーマットスキーマで指定するファイル名は、 サーバー設定の [format_schema_path](/operations/server-configuration-parameters/settings.md/#format_schema_path) で指定されたディレクトリ内に存在している必要があります。 - - ## エラーのスキップ {#skippingerrors} `CSV`、`TabSeparated`、`TSKV`、`JSONEachRow`、`Template`、`CustomSeparated`、`Protobuf` などの一部の形式では、パースエラーが発生した場合に不正な行をスキップし、次の行の先頭からパースを継続できます。詳細は [input_format_allow_errors_num](/operations/settings/settings-formats.md/#input_format_allow_errors_num) および diff --git a/i18n/jp/docusaurus-plugin-content-docs/current/operations/settings/merge-tree-settings.md b/i18n/jp/docusaurus-plugin-content-docs/current/operations/settings/merge-tree-settings.md index 7934877cde4..5f5626393aa 100644 --- a/i18n/jp/docusaurus-plugin-content-docs/current/operations/settings/merge-tree-settings.md +++ b/i18n/jp/docusaurus-plugin-content-docs/current/operations/settings/merge-tree-settings.md @@ -522,7 +522,7 @@ Dynamic データ型のシリアル化バージョン。互換性のために必 - + `min_age_to_force_merge_seconds` と `min_age_to_force_merge_on_partition_only` の両設定が、 @@ -1285,6 +1285,17 @@ Wide データパートへのマージ後には、このパート内の動的パ パーティション内のパーツ数に応じて、このロジックがいつ適用されるかを制御します。係数が大きいほど、反応の開始はより遅くなります。 +## merge_selector_enable_heuristic_to_lower_max_parts_to_merge_at_once {#merge_selector_enable_heuristic_to_lower_max_parts_to_merge_at_once} + + + + + + + +シンプルなマージセレクタに対して、マージ選択時の上限値を引き下げるヒューリスティックを有効にします。 +これにより同時に実行されるマージの数が増え、TOO_MANY_PARTS エラーの軽減に役立つ可能性がありますが、その一方で書き込み増幅も増加します。 + ## merge_selector_enable_heuristic_to_remove_small_parts_at_right {#merge_selector_enable_heuristic_to_remove_small_parts_at_right} diff --git a/i18n/jp/docusaurus-plugin-content-docs/current/operations/settings/settings.md b/i18n/jp/docusaurus-plugin-content-docs/current/operations/settings/settings.md index 0a39ba7b03d..b96e0236faf 100644 --- a/i18n/jp/docusaurus-plugin-content-docs/current/operations/settings/settings.md +++ b/i18n/jp/docusaurus-plugin-content-docs/current/operations/settings/settings.md @@ -10090,6 +10090,15 @@ S3 へのマルチパートアップロードでアップロードする各パ S3 へのマルチパートアップロードでアップロードするパートの最小サイズ。 +## s3_path_filter_limit {#s3_path_filter_limit} + + + + + +ファイルを走査する際に glob リストの代わりに利用するため、クエリフィルタから抽出できる `_path` 値の最大数です。 +0 を指定すると無効になります。 + ## s3_request_timeout_ms {#s3_request_timeout_ms} @@ -10652,7 +10661,8 @@ FINAL 最適化中にパーツ範囲を交差するものと交差しないも -Kafka、RabbitMQ、FileLog、Redis Streams、NATS エンジンに対して、直接の SELECT クエリの実行を許可します。materialized view がアタッチされている場合は、この設定が有効でも SELECT クエリは許可されません。 +Kafka、RabbitMQ、FileLog、Redis Streams、S3Queue、AzureQueue、NATS エンジンに対して、直接の SELECT クエリの実行を許可します。materialized view がアタッチされている場合は、この設定が有効でも SELECT クエリは許可されません。 +materialized view がアタッチされていない場合、この設定を有効にするとデータを読み取れるようになります。通常は、読み取ったデータはキューから削除される点に注意してください。読み取ったデータを削除しないようにするには、関連するエンジンの設定を適切に構成する必要があります。 ## stream_like_engine_insert_queue {#stream_like_engine_insert_queue} diff --git a/i18n/jp/docusaurus-plugin-content-docs/current/operations/system-tables/index.md b/i18n/jp/docusaurus-plugin-content-docs/current/operations/system-tables/index.md index 22dfe89b603..18ab3fe7436 100644 --- a/i18n/jp/docusaurus-plugin-content-docs/current/operations/system-tables/index.md +++ b/i18n/jp/docusaurus-plugin-content-docs/current/operations/system-tables/index.md @@ -21,117 +21,117 @@ doc_type: 'reference' | ページ | 概要 | | ----------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------- | -| [システムテーブル概要](/operations/system-tables/overview) | システムテーブルとは何か、なぜ有用なのかの概要。 | -| [INFORMATION_SCHEMA](/operations/system-tables/information_schema) | データベースオブジェクトのメタデータに対して、ほぼ標準化された形式の DBMS 非依存ビューを提供するシステムデータベース。 | +| [システムテーブル概要](/operations/system-tables/overview) | システムテーブルとは何か、なぜ有用なのかについての概要。 | +| [INFORMATION_SCHEMA](/operations/system-tables/information_schema) | データベースオブジェクトのメタデータについて、ほぼ標準化された形式の DBMS 非依存ビューを提供するシステムデータベース。 | | [system.asynchronous_insert_log](/operations/system-tables/asynchronous_insert_log) | 非同期インサートの情報を保持するシステムテーブル。各エントリは、非同期インサートとしてバッファリングされた INSERT クエリを表します。 | -| [system.asynchronous_inserts](/operations/system-tables/asynchronous_inserts) | キューにたまっている非同期挿入の情報を保持するシステムテーブル。 | +| [system.asynchronous_inserts](/operations/system-tables/asynchronous_inserts) | キューに保留されている非同期インサートの情報を保持するシステムテーブル。 | | [system.asynchronous_loader](/operations/system-tables/asynchronous_loader) | 最近の非同期ジョブ(テーブルのロード処理など)に関する情報とステータスを保持する system テーブルです。テーブルにはジョブごとに 1 行が格納されます。 | | [system.asynchronous_metric_log](/operations/system-tables/asynchronous_metric_log) | `system.asynchronous_metrics` の履歴値を保持するシステムテーブル。これらの値は一定の時間間隔ごと(デフォルトでは 1 秒ごと)に保存されます。 | -| [system.asynchronous_metrics](/operations/system-tables/asynchronous_metrics) | バックグラウンドで定期的に集計されるメトリクスを含むシステムテーブル。例えば、使用中の RAM 量など。 | -| [system.azure_queue_settings](/operations/system-tables/azure_queue_settings) | AzureQueue テーブルの設定情報を含むシステムテーブル。サーバーのバージョン `24.10` 以降で利用可能。 | +| [system.asynchronous_metrics](/operations/system-tables/asynchronous_metrics) | バックグラウンドで定期的に計算されるメトリクスを含むシステムテーブル。例えば、RAM の使用量など。 | +| [system.azure_queue_settings](/operations/system-tables/azure_queue_settings) | AzureQueue テーブルの設定に関する情報を含む system テーブル。サーバーのバージョン `24.10` 以降で利用可能です。 | | [system.backup_log](/operations/system-tables/backup_log) | `BACKUP` および `RESTORE` 操作に関する情報を含むログエントリを格納するシステムテーブル。 | -| [system.backups](/operations/system-tables/backups) | `BACKUP` および `RESTORE` 操作に関する情報を記録しているログエントリを含むシステムテーブル。 | -| [system.blob_storage_log](/operations/system-tables/blob_storage_log) | BLOB ストレージでのアップロードや削除など、さまざまな操作に関する情報を含むログレコードを保持するシステムテーブル。 | -| [system.build_options](/operations/system-tables/build_options) | ClickHouse サーバーのビルドオプションに関する情報を保持する system テーブル。 | -| [system.clusters](/operations/system-tables/clusters) | 設定ファイルで定義されているクラスタおよびそれらのクラスタ内のサーバーに関する情報を保持するシステムテーブル。 | -| [system.codecs](/operations/system-tables/codecs) | キュー内のコーデックに関する情報を保持するシステムテーブル。 | -| [system.columns](/operations/system-tables/columns) | すべてのテーブルのカラム情報を保持するシステムテーブル | +| [system.backups](/operations/system-tables/backups) | `BACKUP` および `RESTORE` 操作に関する情報を含むログエントリを格納するシステムテーブル。 | +| [system.blob_storage_log](/operations/system-tables/blob_storage_log) | BLOB ストレージでのアップロードや削除など、さまざまな操作に関する情報を含むログエントリを保持するシステムテーブル。 | +| [system.build_options](/operations/system-tables/build_options) | ClickHouse サーバーのビルドオプションに関する情報を含むシステムテーブル。 | +| [system.clusters](/operations/system-tables/clusters) | 設定ファイルで定義されているクラスタおよびそれらに含まれるサーバーに関する情報を保持するシステムテーブル。 | +| [system.codecs](/operations/system-tables/codecs) | キュー内のコーデック情報を保持するシステムテーブル。 | +| [system.columns](/operations/system-tables/columns) | すべてのテーブルのカラムに関する情報を保持するシステムテーブル | | [system.contributors](/operations/system-tables/contributors) | コントリビューターに関する情報を格納するシステムテーブル。 | -| [system.crash_log](/operations/system-tables/crash_log) | 致命的エラーのスタックトレース情報を含むシステムテーブル。 | -| [system.current_roles](/operations/system-tables/current_roles) | 現在のユーザーに対して有効なロールを保持しているシステムテーブル。 | -| [system.dashboards](/operations/system-tables/dashboards) | HTTP インターフェイス経由でアクセスできる `/dashboard` ページで使用されるクエリが含まれます。監視やトラブルシューティングに役立ちます。 | +| [system.crash_log](/operations/system-tables/crash_log) | 致命的エラーのスタックトレースに関する情報を保持するシステムテーブル。 | +| [system.current_roles](/operations/system-tables/current_roles) | 現在のユーザーに対して有効なロールを保持するシステムテーブル。 | +| [system.dashboards](/operations/system-tables/dashboards) | HTTP インターフェイス経由でアクセス可能な `/dashboard` ページで使用されるクエリを含むシステムテーブルです。監視やトラブルシューティングに役立ちます。 | | [system.data_skipping_indices](/operations/system-tables/data_skipping_indices) | すべてのテーブルで定義されているデータスキッピングインデックスに関する情報を保持するシステムテーブル。 | | [system.data_type_families](/operations/system-tables/data_type_families) | サポートされているデータ型に関する情報を保持するシステムテーブル | | [system.database_engines](/operations/system-tables/database_engines) | サーバーがサポートするデータベースエンジンの一覧を含むシステムテーブル。 | -| [system.database_replicas](/operations/system-tables/database_replicas) | レプリケートされたデータベースの情報および状態を保持する system テーブル。 | +| [system.database_replicas](/operations/system-tables/database_replicas) | レプリケートされたデータベースの情報および状態を保持するシステムテーブル。 | | [system.databases](/operations/system-tables/databases) | 現在のユーザーが利用できるデータベースに関する情報を保持するシステムテーブル。 | -| [system.dead_letter_queue](/operations/system-tables/dead_letter_queue) | ストリーミングエンジン経由で受信され、解析時にエラーが発生したメッセージに関する情報を含むシステムテーブル。 | -| [system.delta_lake_metadata_log](/operations/system-tables/delta_lake_metadata_log) | Delta Lake テーブルから読み込まれたメタデータファイルに関する情報を格納するシステムテーブル。各エントリはメタデータのルート JSON ファイルを表します。 | +| [system.dead_letter_queue](/operations/system-tables/dead_letter_queue) | ストリーミングエンジン経由で受信され、解析時にエラーが発生したメッセージに関する情報を保持するシステムテーブル。 | +| [system.delta_lake_metadata_log](/operations/system-tables/delta_lake_metadata_log) | Delta Lake テーブルから読み込まれたメタデータファイルに関する情報を格納するシステムテーブル。各エントリはルートメタデータ JSON ファイルを表します。 | | [system.detached_parts](/operations/system-tables/detached_parts) | MergeTree テーブルの切り離されたパーツに関する情報を含むシステムテーブル | -| [system.detached_tables](/operations/system-tables/detached_tables) | 切り離された各テーブルに関する情報を格納するシステムテーブル。 | +| [system.detached_tables](/operations/system-tables/detached_tables) | 切り離された各テーブルに関する情報を含むシステムテーブル。 | | [system.dictionaries](/operations/system-tables/dictionaries) | 辞書に関する情報を保持するシステムテーブル | | [system.dimensional_metrics](/operations/system-tables/dimensional_metrics) | このテーブルには、即時に計算でき、Prometheus 形式でエクスポート可能なディメンションのメトリクスが含まれています。常に最新の状態に保たれています。 | | [system.disks](/operations/system-tables/disks) | サーバー設定で定義されているディスクに関する情報を保持するシステムテーブル | -| [system.distributed_ddl_queue](/operations/system-tables/distributed_ddl_queue) | クラスタ上で実行された分散 DDL クエリ(`ON CLUSTER` 句を使用するクエリ)に関する情報を格納しているシステムテーブル。 | -| [system.distribution_queue](/operations/system-tables/distribution_queue) | 分片に送信されるためキューに入っているローカルファイルに関する情報を保持する system テーブル。 | -| [system.dns_cache](/operations/system-tables/dns_cache) | DNS レコードのキャッシュ情報を含むシステムテーブル。 | -| [system.dropped_tables](/operations/system-tables/dropped_tables) | `DROP TABLE` が実行されたが、まだデータのクリーンアップが完了していないテーブルに関する情報を含むシステムテーブル | +| [system.distributed_ddl_queue](/operations/system-tables/distributed_ddl_queue) | クラスタ上で実行された分散 DDL クエリ(`ON CLUSTER` 句を使用するクエリ)に関する情報を保持するシステムテーブル。 | +| [system.distribution_queue](/operations/system-tables/distribution_queue) | 分片に送信するためにキューに入っているローカルファイルに関する情報を保持する system テーブル。 | +| [system.dns_cache](/operations/system-tables/dns_cache) | キャッシュ済みの DNS レコードに関する情報を含むシステムテーブル。 | +| [system.dropped_tables](/operations/system-tables/dropped_tables) | `DROP TABLE` が実行されたものの、まだデータのクリーンアップが完了していないテーブルの情報を保持するシステムテーブル | | [system.dropped_tables_parts](/operations/system-tables/dropped_tables_parts) | `system.dropped_tables` に記録されている削除済み MergeTree テーブルのパーツに関する情報を保持する system テーブル | -| [system.enabled_roles](/operations/system-tables/enabled_roles) | 現在有効なすべてのロールを含むシステムテーブルであり、現在のユーザーの現在のロールおよびそのロールに対して付与されているロールも含みます | -| [system.error_log](/operations/system-tables/system-error-log) | `system.errors` テーブルのエラー値の履歴を保持するシステムテーブルであり、定期的にディスクにフラッシュされます。 | +| [system.enabled_roles](/operations/system-tables/enabled_roles) | 現在有効なすべてのロールを含むシステムテーブルであり、現在のユーザーのカレントロールおよびそのカレントロールに付与されているロールも含みます | +| [system.error_log](/operations/system-tables/system-error-log) | `system.errors` テーブルにおけるエラー値の履歴を保持するシステムテーブルで、その内容は定期的にディスクにフラッシュされます。 | | [system.errors](/operations/system-tables/errors) | 各エラーコードとその発生回数を含むシステムテーブル。 | -| [system.events](/operations/system-tables/events) | システムで発生したイベント件数に関する情報を保持するシステムテーブル。 | +| [system.events](/operations/system-tables/events) | システムで発生したイベントの回数に関する情報を保持するシステムテーブル。 | | [system.functions](/operations/system-tables/functions) | 通常の関数および集約関数に関する情報を格納するシステムテーブル。 | -| [system.grants](/operations/system-tables/grants) | ClickHouse のユーザーアカウントに付与されている権限を示すシステムテーブル。 | +| [system.grants](/operations/system-tables/grants) | ClickHouse のユーザーアカウントに対してどの権限が付与されているかを示すシステムテーブル。 | | [system.graphite_retentions](/operations/system-tables/graphite_retentions) | `GraphiteMergeTree` 型エンジンのテーブルで使用される `graphite_rollup` パラメータに関する情報を保持するシステムテーブルです。 | -| [system.histogram_metrics](/operations/system-tables/histogram_metrics) | このテーブルには、その場で計算でき、Prometheus 形式でエクスポート可能なヒストグラムメトリクスが含まれます。常に最新の状態に保たれています。 | -| [system.iceberg_history](/operations/system-tables/iceberg_history) | システム Iceberg スナップショット履歴 | +| [system.histogram_metrics](/operations/system-tables/histogram_metrics) | このテーブルには、即時に計算でき、Prometheus 形式でエクスポート可能なヒストグラムメトリクスが含まれています。常に最新の状態に保たれています。 | +| [system.iceberg_history](/operations/system-tables/iceberg_history) | Iceberg のスナップショット履歴を保持するシステムテーブル | | [system.iceberg_metadata_log](/operations/system-tables/iceberg_metadata_log) | Iceberg テーブルから読み取られたメタデータファイルに関する情報を含むシステムテーブルです。各エントリは、ルートメタデータファイル、Avro ファイルから抽出されたメタデータ、または特定の Avro ファイル内のエントリのいずれかを表します。 | -| [system.instrumentation](/operations/system-tables/instrumentation) | 計測ポイントを格納するシステムテーブル | -| [system.jemalloc_bins](/operations/system-tables/jemalloc_bins) | `jemalloc` アロケータによるサイズクラス(bin)ごとのメモリアロケーション情報を、すべてのアリーナから集約したシステムテーブル。 | +| [system.instrumentation](/operations/system-tables/instrumentation) | 計測ポイントに関する情報を保持するシステムテーブル | +| [system.jemalloc_bins](/operations/system-tables/jemalloc_bins) | `jemalloc` アロケータで行われたサイズクラス(bin)ごとのメモリアロケーション情報を、すべてのアリーナから集約して保持するシステムテーブル。 | | [system.kafka_consumers](/operations/system-tables/kafka_consumers) | Kafka コンシューマーに関する情報を格納するシステムテーブル。 | -| [system.licenses](/operations/system-tables/licenses) | ClickHouse のソースの `contrib` ディレクトリ内にあるサードパーティライブラリのライセンス情報を格納する system テーブル。 | +| [system.licenses](/operations/system-tables/licenses) | ClickHouse のソースコードの `contrib` ディレクトリ内にあるサードパーティライブラリのライセンス情報を格納する system テーブル。 | | [system.merge_tree_settings](/operations/system-tables/merge_tree_settings) | MergeTree テーブルの設定に関する情報を含む system テーブル。 | | [system.merges](/operations/system-tables/merges) | MergeTree ファミリーのテーブルに対して現在実行中のマージおよびパーツミューテーションに関する情報を含むシステムテーブル。 | -| [system.metric_log](/operations/system-tables/metric_log) | `system.metrics` および `system.events` テーブルのメトリクス値の履歴を保持し、その内容が定期的にディスクにフラッシュされるシステムテーブル。` | -| [system.metrics](/operations/system-tables/metrics) | 瞬時に計算可能なメトリクス、あるいは現在値を保持しているメトリクスを含むシステムテーブル。 | -| [system.moves](/operations/system-tables/moves) | 進行中の MergeTree テーブルのデータパート移動に関する情報を含む system テーブルです。各データパートの移動は 1 行で表されます。 | +| [system.metric_log](/operations/system-tables/metric_log) | `system.metrics` および `system.events` テーブルのメトリクス値の履歴を保持し、その内容が定期的にディスクにフラッシュされるシステムテーブル。 | +| [system.metrics](/operations/system-tables/metrics) | 即時に計算できるメトリクス、または現在値を持つメトリクスを含むシステムテーブル。 | +| [system.moves](/operations/system-tables/moves) | MergeTree テーブルで進行中のデータパーツの移動に関する情報を保持する system テーブルです。各データパーツの移動は 1 行で表されます。 | | [system.mutations](/operations/system-tables/mutations) | MergeTree テーブルに対する mutation とその進行状況に関する情報を保持する system テーブルです。各 mutation コマンドは 1 行で表されます。 | | [system.numbers](/operations/system-tables/numbers) | `number` という名前の単一の UInt64 カラムを持つシステムテーブルで、0 から始まるほとんどの自然数を格納しています。 | -| [system.numbers_mt](/operations/system-tables/numbers_mt) | `system.numbers` と類似したシステムテーブルですが、読み取りが並列化されており、数値は任意の順序で返されます。 | -| [system.one](/operations/system-tables/one) | 単一の `dummy` UInt8 カラムに値 0 を持つ、1 行のみのシステムテーブルです。他の DBMS で見られる `DUAL` テーブルと同様です。 | -| [system.opentelemetry_span_log](/operations/system-tables/opentelemetry_span_log) | 実行されたクエリのトレーススパン情報を保持するシステムテーブル。 | -| [system.part_log](/operations/system-tables/part_log) | MergeTree ファミリのテーブルにおけるデータパーツに対して発生した、データの追加やマージなどのイベントに関する情報を格納する system テーブル。 | -| [system.parts](/operations/system-tables/parts) | MergeTree のパーツに関する情報を保持するシステムテーブル | +| [system.numbers_mt](/operations/system-tables/numbers_mt) | `system.numbers` と同様のシステムテーブルですが、読み取り処理が並列化されており、数値は任意の順序で返されます。 | +| [system.one](/operations/system-tables/one) | `dummy` という単一の UInt8 カラムに値 0 を持つ、1 行のみからなるシステムテーブルです。他の DBMS で見られる `DUAL` テーブルと同様です。 | +| [system.opentelemetry_span_log](/operations/system-tables/opentelemetry_span_log) | 実行されたクエリのトレーススパンに関する情報を保持するシステムテーブル。 | +| [system.part_log](/operations/system-tables/part_log) | MergeTree ファミリーのテーブルにおけるデータパーツに対して発生した、データの追加やマージなどのイベントに関する情報を格納する system テーブル。 | +| [system.parts](/operations/system-tables/parts) | MergeTree テーブルのパーツに関する情報を保持するシステムテーブル | | [system.parts_columns](/operations/system-tables/parts_columns) | MergeTree テーブルのパーツおよびカラムに関する情報を保持するシステムテーブル。 | -| [system.processes](/operations/system-tables/processes) | `SHOW PROCESSLIST` クエリの実装に使用されるシステムテーブル。 | -| [system.processors_profile_log](/operations/system-tables/processors_profile_log) | プロセッサ単位のプロファイリング情報を含むシステムテーブルです(`EXPLAIN PIPELINE` で確認できます) | +| [system.processes](/operations/system-tables/processes) | `SHOW PROCESSLIST` クエリを実装するために使用されるシステムテーブル。 | +| [system.processors_profile_log](/operations/system-tables/processors_profile_log) | プロセッサレベルのプロファイリング情報を含むシステムテーブルです(`EXPLAIN PIPELINE` で確認できます)。 | | [system.projection_parts](/operations/system-tables/projection_parts) | MergeTree ファミリーのテーブルにおける PROJECTION パーツに関する情報を保持するシステムテーブル。 | -| [system.projection_parts_columns](/operations/system-tables/projection_parts_columns) | MergeTree ファミリーのテーブルにおけるプロジェクションパーツ内のカラム情報を保持する system テーブル | -| [system.projections](/operations/system-tables/projections) | すべてのテーブルの既存の PROJECTION に関する情報を保持する system テーブル。 | +| [system.projection_parts_columns](/operations/system-tables/projection_parts_columns) | MergeTree ファミリーのテーブルにおける PROJECTION パーツ内のカラムに関する情報を保持する system テーブル | +| [system.projections](/operations/system-tables/projections) | すべてのテーブルに存在する PROJECTION に関する情報を保持する system テーブル。 | | [system.query_cache](/operations/system-tables/query_cache) | クエリキャッシュの内容を表示するシステムテーブル。 | | [system.query_condition_cache](/operations/system-tables/query_condition_cache) | クエリ条件キャッシュの内容を表示するシステムテーブル。 | | [system.query_log](/operations/system-tables/query_log) | 実行されたクエリについて、開始時刻、処理時間、エラーメッセージなどの情報を保持するシステムテーブルです。 | -| [system.query_metric_log](/operations/system-tables/query_metric_log) | テーブル `system.events` の値に基づいて個々のクエリのメモリ使用量およびメトリクスの履歴を保持し、その内容を定期的にディスクにフラッシュするシステムテーブル。 | -| [system.query_thread_log](/operations/system-tables/query_thread_log) | クエリを実行するスレッドに関する情報を保持するシステムテーブル。例えば、スレッド名、スレッドの開始時刻、クエリ処理に要した時間などを含みます。 | -| [system.query_views_log](/operations/system-tables/query_views_log) | クエリの実行時に動作する依存ビューに関する情報を保持するシステムテーブルです。たとえば、ビューのタイプや実行時間などが含まれます。 | -| [system.quota_limits](/operations/system-tables/quota_limits) | すべての QUOTA について、各間隔ごとの最大値に関する情報を含む system テーブルです。1 つの QUOTA に対応する行数は、0 行を含む任意の数になり得ます。 | +| [system.query_metric_log](/operations/system-tables/query_metric_log) | テーブル `system.events` の値に基づいて個々のクエリのメモリ使用量およびメトリクスの履歴を保持するシステムテーブルであり、その内容が定期的にディスクにフラッシュされます。 | +| [system.query_thread_log](/operations/system-tables/query_thread_log) | クエリを実行するスレッドに関する情報を保持するシステムテーブル。例えば、スレッド名、開始時刻、クエリ処理時間などを含みます。 | +| [system.query_views_log](/operations/system-tables/query_views_log) | クエリ実行時に実行される依存ビューに関する情報を保持するシステムテーブルです。たとえば、ビューの種類や実行時間などが含まれます。 | +| [system.quota_limits](/operations/system-tables/quota_limits) | すべての QUOTA について、すべての間隔ごとの最大値に関する情報を含む system テーブルです。1 つの QUOTA に対応する行数は、0 行を含む任意の数となり得ます。 | | [system.quota_usage](/operations/system-tables/quota_usage) | 現在のUSERについて、QUOTAの使用量や残量などの使用状況に関する情報を含む system テーブル。 | | [system.quotas](/operations/system-tables/quotas) | QUOTA に関する情報を保持するシステムテーブル。 | | [system.quotas_usage](/operations/system-tables/quotas_usage) | 全ユーザーのQUOTA使用状況に関する情報を保持するシステムテーブルです。 | | [system.replicas](/operations/system-tables/replicas) | ローカルサーバー上にあるレプリケートされたテーブルの情報と状態を保持するシステムテーブルです。監視用途に役立ちます。 | | [system.replicated_fetches](/operations/system-tables/replicated_fetches) | 現在実行中のバックグラウンドフェッチに関する情報を保持するシステムテーブル。 | -| [system.replication_queue](/operations/system-tables/replication_queue) | `ReplicatedMergeTree` ファミリーのテーブル向けに、ClickHouse Keeper または ZooKeeper に保存されているレプリケーションキュー内のタスクに関する情報を保持する system テーブルです。 | -| [system.resources](/operations/system-tables/resources) | ローカルサーバー上に存在する各リソースごとに1行を持つ、リソースに関する情報を格納したシステムテーブルです。 | -| [system.role_grants](/operations/system-tables/role_grants) | ユーザーおよびロールに対するロールの付与を保持するシステムテーブル。 | +| [system.replication_queue](/operations/system-tables/replication_queue) | `ReplicatedMergeTree` ファミリーのテーブル用に、ClickHouse Keeper または ZooKeeper に保存されているレプリケーションキューに含まれるタスクに関する情報を保持する system テーブルです。 | +| [system.resources](/operations/system-tables/resources) | ローカルサーバー上に存在するリソースに関する情報を保持するシステムテーブルで、各リソースごとに 1 行が格納されます。 | +| [system.role_grants](/operations/system-tables/role_grants) | ユーザーおよびロールに対するロール付与情報を保持するシステムテーブル。 | | [system.roles](/operations/system-tables/roles) | 構成済みのロールに関する情報を保持するシステムテーブル。 | | [system.row_policies](/operations/system-tables/row_policies) | 特定のテーブルに対するフィルタと、このROW POLICYを適用すべきロールおよび/またはユーザーの一覧を含むシステムテーブル。 | -| [system.s3_queue_settings](/operations/system-tables/s3_queue_settings) | S3Queue テーブルの設定に関する情報を含む system テーブル。サーバーのバージョン `24.10` 以降で利用可能です。 | -| [system.scheduler](/operations/system-tables/scheduler) | ローカルサーバー上のスケジューリングノードの情報および状態を保持するシステムテーブル。 | -| [system.schema_inference_cache](/operations/system-tables/schema_inference_cache) | すべてのキャッシュ済みファイルスキーマに関する情報を保持するシステムテーブル。 | +| [system.s3_queue_settings](/operations/system-tables/s3_queue_settings) | S3Queue テーブルの設定情報を含むシステムテーブル。サーバーのバージョン `24.10` 以降で利用可能。 | +| [system.scheduler](/operations/system-tables/scheduler) | ローカルサーバー上に存在するスケジューリングノードの情報および状態を保持するシステムテーブル。 | +| [system.schema_inference_cache](/operations/system-tables/schema_inference_cache) | キャッシュされたすべてのファイルスキーマに関する情報を保持するシステムテーブル。 | | [system.server_settings](/operations/system-tables/server_settings) | `config.xml` で指定されたサーバーのグローバル設定に関する情報を保持する system テーブル。 | | [system.session_log](/operations/system-tables/session_log) | すべてのログインおよびログアウトの成功・失敗イベントに関する情報を保持するシステムテーブル。 | | [system.settings](/operations/system-tables/settings) | 現在のユーザーのセッション設定に関する情報を保持するシステムテーブルです。 | | [system.settings_changes](/operations/system-tables/settings_changes) | 過去の ClickHouse バージョンでの設定変更に関する情報を含むシステムテーブル。 | | [system.settings_profile_elements](/operations/system-tables/settings_profile_elements) | 設定プロファイルの内容(制約、設定が適用されるロールおよびユーザー、親設定プロファイル)を表すシステムテーブルです。 | | [system.settings_profiles](/operations/system-tables/settings_profiles) | 設定プロファイルのプロパティを保持する system テーブル。 | -| [system.stack_trace](/operations/system-tables/stack_trace) | すべてのサーバースレッドのスタックトレースを保持するシステムテーブル。開発者がサーバーの状態を詳細に把握・調査するために利用できます。 | +| [system.stack_trace](/operations/system-tables/stack_trace) | すべてのサーバースレッドのスタックトレースを保持するシステムテーブル。開発者がサーバーの内部状態を解析する際に利用できます。 | | [system.storage_policies](/operations/system-tables/storage_policies) | サーバー構成で定義されたストレージポリシーおよびボリュームに関する情報を保持するシステムテーブル。 | -| [system.symbols](/operations/system-tables/symbols) | C++ のエキスパートや ClickHouse エンジニア向けのシステムテーブルで、`clickhouse` バイナリの内部解析に役立つ情報を含みます。 | -| [system.table_engines](/operations/system-tables/table_engines) | サーバーでサポートされているテーブルエンジンと、それらが対応する機能の説明を含むシステムテーブル。 | -| [system.tables](/operations/system-tables/tables) | サーバーが認識している各テーブルのメタデータを保持するシステムテーブルです。 | +| [system.symbols](/operations/system-tables/symbols) | C++ のエキスパートや ClickHouse エンジニア向けのシステムテーブルで、`clickhouse` バイナリの内部を調査するための情報を含みます。 | +| [system.table_engines](/operations/system-tables/table_engines) | サーバーがサポートするテーブルエンジンおよびそれぞれがサポートする機能の説明を含むシステムテーブル。 | +| [system.tables](/operations/system-tables/tables) | サーバーが把握しているすべてのテーブルのメタデータを保持するシステムテーブルです。 | | [system.text_log](/operations/system-tables/text_log) | ログエントリを格納するシステムテーブル。 | | [system.time_zones](/operations/system-tables/time_zones) | ClickHouse サーバーでサポートされているタイムゾーンの一覧を含むシステムテーブル。 | | [system.trace_log](/operations/system-tables/trace_log) | サンプリングクエリプロファイラによって収集されたスタックトレースを格納するシステムテーブルです。 | -| [system.unicode](/operations/system-tables/unicode) | Unicode 文字とその属性の一覧を持つシステムテーブル。 | -| [system.user_processes](/operations/system-tables/user_processes) | ユーザーのメモリ使用量と ProfileEvents の概要把握に有用な情報を含む system テーブル。 | -| [system.users](/operations/system-tables/users) | サーバー上で構成されているユーザーアカウントの一覧を保持するシステムテーブル。 | -| [system.view_refreshes](/operations/system-tables/view_refreshes) | リフレッシャブルmaterialized viewに関する情報を保持するシステムテーブルです。 | +| [system.unicode](/operations/system-tables/unicode) | Unicode 文字とそのプロパティの一覧を含むシステムテーブル。 | +| [system.user_processes](/operations/system-tables/user_processes) | ユーザーごとのメモリ使用量や ProfileEvents の概要を把握するのに有用な情報を含む system テーブル。 | +| [system.users](/operations/system-tables/users) | サーバー上で構成済みのユーザーアカウント一覧を保持するシステムテーブル。 | +| [system.view_refreshes](/operations/system-tables/view_refreshes) | リフレッシャブルmaterialized view の情報を保持するシステムテーブルです。 | | [system.warnings](/operations/system-tables/system_warnings) | このテーブルには ClickHouse サーバーに関する警告メッセージが含まれています。 | -| [system.workloads](/operations/system-tables/workloads) | ローカルサーバー上に存在するワークロードに関する情報を格納するシステムテーブル。 | +| [system.workloads](/operations/system-tables/workloads) | ローカルサーバー上で実行されているワークロードに関する情報を格納するシステムテーブル。 | +| [system.zookeeper_log](/operations/system-tables/zookeeper_log) | ZooKeeper サーバーへのリクエストパラメータとその応答に関する情報を保持するシステムテーブルです。 | | [system.zookeeper](/operations/system-tables/zookeeper) | ClickHouse Keeper または ZooKeeper が構成されている場合にのみ存在するシステムテーブルです。設定ファイルで定義された Keeper クラスターのデータを提供します。 | | [system.zookeeper_connection](/operations/system-tables/zookeeper_connection) | ZooKeeper が構成されている場合にのみ存在するシステムテーブル。ZooKeeper(補助的な ZooKeeper を含む)への現在の接続を表示します。 | -| [system.zookeeper_connection_log](/operations/system-tables/zookeeper_connection_log) | ZooKeeper への接続履歴(補助 ZooKeeper を含む)を表示します。 | -| [system.zookeeper_log](/operations/system-tables/zookeeper_log) | ZooKeeper サーバーへのリクエストパラメータとその応答に関する情報を保持するシステムテーブルです。 | +| [system.zookeeper_connection_log](/operations/system-tables/zookeeper_connection_log) | ZooKeeper(補助的な ZooKeeper を含む)への接続履歴を表示します。 | {/*AUTOGENERATED_END*/ } diff --git a/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/index.md b/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/index.md index 10aad2b30c5..df285d28927 100644 --- a/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/index.md +++ b/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/index.md @@ -21,141 +21,141 @@ ClickHouse は、標準的な SQL 集約関数([sum](../reference/sum.md)、[a {/*AUTOGENERATED_START*/ } -| ページ | 概要 | -| --------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| [aggThrow](/sql-reference/aggregate-functions/reference/aggthrow) | この関数は例外安全性をテストするために使用できます。指定した確率で、生成時に例外をスローします。 | -| [analysisOfVariance](/sql-reference/aggregate-functions/reference/analysis_of_variance) | 一元配置分散分析(ANOVA)用の統計検定を提供します。これは、正規分布に従う複数のグループの観測値について、すべてのグループの平均が同一かどうかを判定するための検定です。 | -| [any](/sql-reference/aggregate-functions/reference/any) | 指定したカラムで最初に出現した値を選択します。 | -| [anyHeavy](/sql-reference/aggregate-functions/reference/anyheavy) | heavy hitters アルゴリズムを使用して、頻繁に出現する値を選択します。各クエリ実行スレッドにおいて、全ケースの過半数で出現する値がある場合、その値が返されます。通常、結果は決定的ではありません。 | -| [anyLast](/sql-reference/aggregate-functions/reference/anylast) | カラム内で最後に出現した値を返します。 | -| [approx_top_k](/sql-reference/aggregate-functions/reference/approxtopk) | 指定されたカラム内で、おおよそ最も頻繁に出現する値とその出現回数の配列を返します。 | -| [approx_top_sum](/sql-reference/aggregate-functions/reference/approxtopsum) | 指定したカラムにおける、おおよそ最も頻出する値とその出現回数を配列で返します。 | -| [argMax](/sql-reference/aggregate-functions/reference/argmax) | 最大の `val` に対応する `arg` を計算します。 | -| [argMin](/sql-reference/aggregate-functions/reference/argmin) | 最小の `val` 値に対応する `arg` の値を計算します。最小となる `val` が同じ行が複数ある場合、どの行の `arg` が返されるかは未定義です。 | -| [argAndMax](/sql-reference/aggregate-functions/reference/argandmax) | 最大の `val` 値に対応する `arg` と `val` の値を計算します。最大値となる `val` を持つ行が複数存在する場合、どの `arg` および `val` が返されるかは非決定的です。 | -| [argAndMin](/sql-reference/aggregate-functions/reference/argandmin) | 最小の `val` 値に対する `arg` と `val` の値を計算します。最小となる同じ `val` を持つ行が複数ある場合、どの行に対応する `arg` と `val` が返されるかは保証されていません。 | -| [groupArrayArray](/sql-reference/aggregate-functions/reference/grouparrayarray) | 複数の配列をまとめて、それらを要素とする配列にします。 | -| [avg](/sql-reference/aggregate-functions/reference/avg) | 算術平均を求めます。 | -| [avgWeighted](/sql-reference/aggregate-functions/reference/avgweighted) | 加重算術平均を求めます。 | -| [boundingRatio](/sql-reference/aggregate-functions/reference/boundingRatio) | 値のグループ内で、最も左端の点と最も右端の点の間の傾き(スロープ)を計算する集約関数です。 | -| [categoricalInformationValue](/sql-reference/aggregate-functions/reference/categoricalinformationvalue) | 各カテゴリごとに `(P(tag = 1) - P(tag = 0))(log(P(tag = 1)) - log(P(tag = 0)))` の値を計算します。 | -| [contingency](/sql-reference/aggregate-functions/reference/contingency) | `contingency` 関数は、連関係数(contingency coefficient)を計算します。これは、テーブル内の 2 つのカラム間の関連の強さを測定する値です。計算方法は `cramersV` 関数と似ていますが、平方根の中の分母が異なります。 | -| [corr](/sql-reference/aggregate-functions/reference/corr) | ピアソンの相関係数を計算します。 | -| [corrMatrix](/sql-reference/aggregate-functions/reference/corrmatrix) | N 個の変数に対する相関行列を計算します。 | -| [corrStable](/sql-reference/aggregate-functions/reference/corrstable) | Pearson の相関係数を、数値的に安定したアルゴリズムで計算します。 | -| [count](/sql-reference/aggregate-functions/reference/count) | 行数、または NULL 以外の値の数をカウントします。 | -| [covarPop](/sql-reference/aggregate-functions/reference/covarpop) | 母集団共分散を計算します | -| [covarPopMatrix](/sql-reference/aggregate-functions/reference/covarpopmatrix) | N 個の変数間の母共分散行列を返します。 | -| [covarPopStable](/sql-reference/aggregate-functions/reference/covarpopstable) | 母共分散を計算します | -| [covarSamp](/sql-reference/aggregate-functions/reference/covarsamp) | `Σ((x - x̅)(y - y̅)) / (n - 1)` の値を計算します | -| [covarSampMatrix](/sql-reference/aggregate-functions/reference/covarsampmatrix) | N 個の変数間の標本共分散行列を返します。 | -| [covarSampStable](/sql-reference/aggregate-functions/reference/covarsampstable) | covarSamp と同様ですが、計算誤差をより小さく抑えられる反面、動作は遅くなります。 | -| [cramersV](/sql-reference/aggregate-functions/reference/cramersv) | `cramersV` 関数の結果は 0(変数間に全く連関がないことに対応)から 1 までの範囲を取り、各値が他方によって完全に一意に決定される場合にのみ 1 となります。これは、2 つの変数間の連関の強さを、それらのとりうる最大限の変動に対する割合として表したものとみなせます。 | -| [cramersVBiasCorrected](/sql-reference/aggregate-functions/reference/cramersvbiascorrected) | バイアス補正を適用した Cramer's V を計算します。 | -| [deltaSum](/sql-reference/aggregate-functions/reference/deltasum) | 連続する行の値の差を合計します。 | -| [deltaSumTimestamp](/sql-reference/aggregate-functions/reference/deltasumtimestamp) | 連続する行同士の差分を加算します。差分が負の場合は無視されます。 | -| [entropy](/sql-reference/aggregate-functions/reference/entropy) | 値からなるカラムのシャノンエントロピーを計算します。 | -| [estimateCompressionRatio](/sql-reference/aggregate-functions/reference/estimateCompressionRatio) | 指定されたカラムに対して、実際に圧縮を行うことなく圧縮率を推定します。 | -| [exponentialMovingAverage](/sql-reference/aggregate-functions/reference/exponentialMovingAverage) | 指定された期間における値の指数移動平均を計算します。 | -| [exponentialTimeDecayedAvg](/sql-reference/aggregate-functions/reference/exponentialTimeDecayedAvg) | 時刻 `t` における時系列データの値に対する指数平滑加重移動平均を返します。 | -| [exponentialTimeDecayedCount](/sql-reference/aggregate-functions/reference/exponentialTimeDecayedCount) | 時間インデックス `t` における時系列データの累積的な指数減衰を返します。 | -| [exponentialTimeDecayedMax](/sql-reference/aggregate-functions/reference/exponentialTimeDecayedMax) | 時系列データに対して計算された指数平滑移動平均について、時間インデックス `t` における値と `t-1` における値のうち、大きい方の値を返します。 | -| [exponentialTimeDecayedSum](/sql-reference/aggregate-functions/reference/exponentialTimeDecayedSum) | 時間インデックス `t` における時系列の指数平滑移動平均値の総和を返します。 | -| [first_value](/sql-reference/aggregate-functions/reference/first_value) | これは `any` のエイリアスですが、Window Functions との互換性を保つために導入されました。Window Functions では `NULL` 値を処理する必要がある場合があり(デフォルトでは、すべての ClickHouse 集約関数は `NULL` 値を無視します)、そのために用いられます。 | -| [flameGraph](/sql-reference/aggregate-functions/reference/flame_graph) | スタックトレースのリストからフレームグラフを生成する集約関数です。 | -| [groupArray](/sql-reference/aggregate-functions/reference/grouparray) | 引数値の配列を作成します。配列への値の追加順序は任意(順序は未定義)です。 | -| [groupArrayInsertAt](/sql-reference/aggregate-functions/reference/grouparrayinsertat) | 配列の指定された位置に値を挿入します。 | -| [groupArrayIntersect](/sql-reference/aggregate-functions/reference/grouparrayintersect) | 指定された配列の共通部分を返します(指定されたすべての配列に存在する要素を返します)。 | -| [groupArrayLast](/sql-reference/aggregate-functions/reference/grouparraylast) | 最後の引数の値から配列を作成します。 | -| [groupArrayMovingAvg](/sql-reference/aggregate-functions/reference/grouparraymovingavg) | 入力値の移動平均を計算します。 | -| [groupArrayMovingSum](/sql-reference/aggregate-functions/reference/grouparraymovingsum) | 入力値の移動合計を計算します。 | -| [groupArraySample](/sql-reference/aggregate-functions/reference/grouparraysample) | サンプルとなる引数値の配列を作成します。生成される配列のサイズは `max_size` 個の要素に制限されます。引数値をランダムに選択して配列に追加します。 | -| [groupArraySorted](/sql-reference/aggregate-functions/reference/grouparraysorted) | 先頭N個の要素を昇順に並べた配列を返します。 | -| [timeSeriesGroupArray](/sql-reference/aggregate-functions/reference/timeSeriesGroupArray) | 時系列データをタイムスタンプで昇順に並べ替えます。 | -| [groupBitAnd](/sql-reference/aggregate-functions/reference/groupbitand) | 一連の数値に対してビット単位の `AND` を適用します。 | -| [groupBitmap](/sql-reference/aggregate-functions/reference/groupbitmap) | 符号なし整数カラムに対してビットマップまたは集約計算を行うと、UInt64 型の基数を返します。関数名にサフィックス `-State` を付けると、ビットマップオブジェクトを返します。 | -| [groupBitmapAnd](/sql-reference/aggregate-functions/reference/groupbitmapand) | ビットマップカラム同士の AND を計算し、その結果の要素数を UInt64 型で返します。-State 接尾辞を付けると、ビットマップオブジェクトを返します。 | -| [groupBitmapOr](/sql-reference/aggregate-functions/reference/groupbitmapor) | ビットマップカラム同士の OR を計算し、その結果の基数を UInt64 型で返します。サフィックスに -State を付けると、ビットマップオブジェクトを返します。これは `groupBitmapMerge` と同等です。 | -| [groupBitmapXor](/sql-reference/aggregate-functions/reference/groupbitmapxor) | ビットマップカラムの XOR を計算し、UInt64 型の要素数(cardinality)を返します。サフィックス -State を付けて使用した場合は、ビットマップオブジェクトを返します。 | -| [groupBitOr](/sql-reference/aggregate-functions/reference/groupbitor) | 一連の数値に対してビット単位の `OR` 演算を行います。 | -| [groupBitXor](/sql-reference/aggregate-functions/reference/groupbitxor) | 数値列にビット単位の `XOR` を適用します。 | -| [groupUniqArray](/sql-reference/aggregate-functions/reference/groupuniqarray) | さまざまな引数の値から配列を作成します。 | -| [intervalLengthSum](/sql-reference/aggregate-functions/reference/intervalLengthSum) | 数値軸上のすべての区間の和集合の長さを計算します。 | -| [kolmogorovSmirnovTest](/sql-reference/aggregate-functions/reference/kolmogorovsmirnovtest) | 2つの母集団からの標本に対して Kolmogorov-Smirnov 検定を適用します。 | -| [kurtPop](/sql-reference/aggregate-functions/reference/kurtpop) | データ列の尖度を計算します。 | -| [kurtSamp](/sql-reference/aggregate-functions/reference/kurtsamp) | シーケンスの標本尖度を算出します。 | -| [largestTriangleThreeBuckets](/sql-reference/aggregate-functions/reference/largestTriangleThreeBuckets) | 入力データに Largest-Triangle-Three-Buckets アルゴリズムを適用します。 | -| [last_value](/sql-reference/aggregate-functions/reference/last_value) | 最後に出現した値を選択します。`anyLast` と類似していますが、NULL も許容します。 | -| [mannWhitneyUTest](/sql-reference/aggregate-functions/reference/mannwhitneyutest) | 2つの母集団から得られた標本に対して、Mann-Whitneyの順位検定を適用します。 | -| [max](/sql-reference/aggregate-functions/reference/max) | 値のグループにおける最大値を計算する集約関数です。 | -| [maxIntersections](/sql-reference/aggregate-functions/reference/maxintersections) | 一連の区間について、区間同士が交差する回数の最大値を(すべての区間が少なくとも一度は互いに交差する場合に)計算する集約関数。 | -| [maxIntersectionsPosition](/sql-reference/aggregate-functions/reference/maxintersectionsposition) | `maxIntersections` 関数が出現する位置を算出する集約関数。 | -| [maxMap](/sql-reference/aggregate-functions/reference/maxmap) | `key` 配列で指定されたキーに従って、`value` 配列から最大値を求めます。 | -| [meanZTest](/sql-reference/aggregate-functions/reference/meanztest) | 2つの母集団から得た標本に対して平均のZ検定を適用します。 | -| [median](/sql-reference/aggregate-functions/reference/median) | `median*` 関数は、対応する `quantile*` 関数のエイリアスです。数値データサンプルの中央値を計算します。 | -| [min](/sql-reference/aggregate-functions/reference/min) | 値のグループにおける最小値を計算する集約関数。 | -| [minMap](/sql-reference/aggregate-functions/reference/minmap) | `key` 配列で指定されたキーごとに、`value` 配列から最小値を計算します。 | -| [quantile](/sql-reference/aggregate-functions/reference/quantile) | 数値データ列の近似分位数を計算します。 | -| [quantileBFloat16](/sql-reference/aggregate-functions/reference/quantilebfloat16) | bfloat16 型の値からなるサンプルの近似分位数を計算します。 | -| [quantileDD](/sql-reference/aggregate-functions/reference/quantileddsketch) | 相対誤差保証付きで標本の近似分位数を計算します。 | -| [quantileDeterministic](/sql-reference/aggregate-functions/reference/quantiledeterministic) | 数値データのシーケンスに対して近似分位数を計算します。 | -| [quantileExact 関数](/sql-reference/aggregate-functions/reference/quantileexact) | quantileExact, quantileExactLow, quantileExactHigh, quantileExactExclusive, quantileExactInclusive 関数 | -| [quantileExactWeighted](/sql-reference/aggregate-functions/reference/quantileexactweighted) | 各要素の重みを考慮して、数値データ列の分位数を正確に計算します。 | -| [quantileGK](/sql-reference/aggregate-functions/reference/quantileGK) | Greenwald-Khanna アルゴリズムを使用して、数値データ列の分位数を計算します。 | -| [quantileExactWeightedInterpolated](/sql-reference/aggregate-functions/reference/quantileExactWeightedInterpolated) | 各要素の重みを考慮し、数値データ系列の分位点を線形補間で計算します。 | -| [quantileInterpolatedWeighted](/sql-reference/aggregate-functions/reference/quantileInterpolatedWeighted) | 各要素の重みを考慮し、線形補間を用いて数値データ系列の分位数を計算します。 | -| [quantiles 系関数](/sql-reference/aggregate-functions/reference/quantiles) | quantiles, quantilesExactExclusive, quantilesExactInclusive, quantilesGK | -| [quantileTDigest](/sql-reference/aggregate-functions/reference/quantiletdigest) | `t-digest` アルゴリズムを使用して、数値データ系列の近似的な分位点を計算します。 | -| [quantileTDigestWeighted](/sql-reference/aggregate-functions/reference/quantiletdigestweighted) | `t-digest` アルゴリズムを使用して、数値データ系列の近似分位数を計算します。 | -| [quantileTiming](/sql-reference/aggregate-functions/reference/quantiletiming) | 指定された精度で数値データシーケンスの分位数を計算します。 | -| [quantileTimingWeighted](/sql-reference/aggregate-functions/reference/quantiletimingweighted) | 指定された精度で、各要素の重みに基づいて数値データ系列の分位数を計算します。 | -| [rankCorr](/sql-reference/aggregate-functions/reference/rankCorr) | 順位相関係数を計算します。 | -| [simpleLinearRegression](/sql-reference/aggregate-functions/reference/simplelinearregression) | 1次元の線形回帰(単回帰)を実行します。 | -| [singleValueOrNull](/sql-reference/aggregate-functions/reference/singlevalueornull) | 集約関数 `singleValueOrNull` は、`x = ALL (SELECT ...)` のようなサブクエリ演算子を実装するために使用されます。データ内に NULL ではない一意の値がただ 1 つだけ存在するかどうかを確認します。 | -| [skewPop](/sql-reference/aggregate-functions/reference/skewpop) | 列の歪度を計算します。 | -| [skewSamp](/sql-reference/aggregate-functions/reference/skewsamp) | シーケンスの標本歪度を計算します。 | -| [sparkbar](/sql-reference/aggregate-functions/reference/sparkbar) | この関数は、区間 `[min_x, max_x]` における値 `x` と、その値の反復頻度 `y` に対する度数ヒストグラムをプロットします。 | -| [stddevPop](/sql-reference/aggregate-functions/reference/stddevpop) | 結果は varPop の平方根に等しくなります。 | -| [stddevPopStable](/sql-reference/aggregate-functions/reference/stddevpopstable) | 結果は varPop の平方根と等しくなります。stddevPop と異なり、この関数は数値的に安定なアルゴリズムを使用します。 | -| [stddevSamp](/sql-reference/aggregate-functions/reference/stddevsamp) | 結果は varSamp の平方根です | -| [stddevSampStable](/sql-reference/aggregate-functions/reference/stddevsampstable) | 結果は varSamp の平方根と等しくなります。この関数は varSamp とは異なり、数値的に安定なアルゴリズムを使用します。 | -| [stochasticLinearRegression](/sql-reference/aggregate-functions/reference/stochasticlinearregression) | この関数は確率的線形回帰を実装します。学習率、L2 正則化係数、ミニバッチサイズを任意に指定でき、重み更新のためのいくつかの手法(Adam、単純な SGD、Momentum、Nesterov)をサポートします。 | -| [stochasticLogisticRegression](/sql-reference/aggregate-functions/reference/stochasticlogisticregression) | この関数は確率的ロジスティック回帰を実装します。二値分類問題に使用でき、stochasticLinearRegression と同じカスタムパラメータをサポートし、動作も同様です。 | -| [studentTTest](/sql-reference/aggregate-functions/reference/studentttest) | 2つの母集団からの標本にスチューデントの t 検定を適用します。 | -| [studentTTestOneSample](/sql-reference/aggregate-functions/reference/studentttestonesample) | 既知の母平均が与えられた標本に 1 標本 Student の t 検定を適用します。 | -| [sum](/sql-reference/aggregate-functions/reference/sum) | 合計を計算します。数値に対してのみ使用できます。 | -| [sumCount](/sql-reference/aggregate-functions/reference/sumcount) | 数値の合計を計算すると同時に、行数もカウントします。この関数は ClickHouse のクエリオプティマイザーで使用されます。クエリ内に複数の `sum`、`count`、`avg` 関数がある場合、それらを 1 つの `sumCount` 関数に置き換えることで、計算結果を再利用できます。この関数を明示的に呼び出す必要があるケースはまれです。 | -| [sumKahan](/sql-reference/aggregate-functions/reference/sumkahan) | Kahan 補償和アルゴリズムを用いて数値の総和を計算します | -| [sumMap](/sql-reference/aggregate-functions/reference/summap) | `key` 配列で指定されたキーに従って、1 つ以上の `value` 配列を合計します。ソートされたキー配列と、それぞれのキーに対応する値をオーバーフローなしで合計した配列から成るタプルを返します。 | -| [sumMapWithOverflow](/sql-reference/aggregate-functions/reference/summapwithoverflow) | `key` 配列で指定されたキーに従って、`value` 配列を集計します。ソート済みのキーの配列と、それぞれのキーに対応して合計された値の配列という、2 つの配列からなるタプルを返します。オーバーフローありで加算を行う点で、sumMap 関数と異なります。 | -| [sumWithOverflow](/sql-reference/aggregate-functions/reference/sumwithoverflow) | 数値の合計を計算し、結果のデータ型は入力パラメータと同じになります。合計がこのデータ型の最大値を超えた場合、オーバーフローした結果として計算されます。 | -| [theilsU](/sql-reference/aggregate-functions/reference/theilsu) | `theilsU` 関数は、テーブル内の 2 つのカラム間の関連性を測る指標である Theils' U 不確実性係数を計算します。 | -| [topK](/sql-reference/aggregate-functions/reference/topk) | 指定したカラム内で、おおよそ頻度が高い値の配列を返します。返される配列は、値そのものではなく、値のおおよその出現頻度が高い順(降順)にソートされます。 | -| [topKWeighted](/sql-reference/aggregate-functions/reference/topkweighted) | 指定されたカラム内で、頻出すると推定される値の配列を返します。返される配列は、値そのものではなく、値の推定出現頻度に基づいて降順にソートされます。また、値の重みも考慮されます。 | -| [uniq](/sql-reference/aggregate-functions/reference/uniq) | 引数の異なる値の概算個数を計算します。 | -| [uniqCombined](/sql-reference/aggregate-functions/reference/uniqcombined) | 引数の異なる値の概数を計算します。 | -| [uniqCombined64](/sql-reference/aggregate-functions/reference/uniqcombined64) | 異なる引数の値のおおよその数を計算します。`uniqCombined` と同じですが、String データ型だけでなく、すべてのデータ型に対して 64ビットハッシュを使用します。 | -| [uniqExact](/sql-reference/aggregate-functions/reference/uniqexact) | 引数の異なる値の正確な個数を計算します。 | -| [uniqHLL12](/sql-reference/aggregate-functions/reference/uniqhll12) | HyperLogLog アルゴリズムを使用して、引数として与えられた異なる値のおおよその数を計算します。 | -| [uniqTheta](/sql-reference/aggregate-functions/reference/uniqthetasketch) | Theta Sketch Framework を使用して、引数の異なる値のおおよその個数を計算します。 | -| [varPop](/sql-reference/aggregate-functions/reference/varPop) | 母分散を計算します。 | -| [varPopStable](/sql-reference/aggregate-functions/reference/varpopstable) | 母分散を返します。varPop とは異なり、この関数は数値的に安定なアルゴリズムを使用します。処理は遅くなりますが、計算誤差は小さくなります。 | -| [varSamp](/sql-reference/aggregate-functions/reference/varSamp) | データセットの標本分散を計算します。 | -| [varSampStable](/sql-reference/aggregate-functions/reference/varsampstable) | データセットの標本分散を計算します。`varSamp` とは異なり、この関数は数値的に安定したアルゴリズムを使用します。処理は遅くなりますが、計算誤差をより小さく抑えられます。 | -| [welchTTest](/sql-reference/aggregate-functions/reference/welchttest) | 2つの母集団からの標本に Welch の t 検定を行います。 | -| [distinctDynamicTypes](/sql-reference/aggregate-functions/reference/distinctdynamictypes) | Dynamic カラムに保存されている重複のないデータ型の一覧を返します。 | -| [distinctJSONPaths](/sql-reference/aggregate-functions/reference/distinctjsonpaths) | JSON カラムに格納されたパスの一意な一覧を算出します。 | -| [timeSeriesDeltaToGrid](/sql-reference/aggregate-functions/reference/timeSeriesDeltaToGrid) | 指定されたグリッド上の時系列データに対して、PromQL 風の delta を計算する集約関数。 | -| [timeSeriesInstantDeltaToGrid](/sql-reference/aggregate-functions/reference/timeSeriesInstantDeltaToGrid) | 指定されたグリッドに従って時系列データに対し、PromQL 風の idelta を計算する集約関数。 | -| [timeSeriesInstantRateToGrid](/sql-reference/aggregate-functions/reference/timeSeriesInstantRateToGrid) | 指定されたグリッドに従い、時系列データに対して PromQL ライクな irate を計算する集約関数。 | -| [timeSeriesLastTwoSamples](/sql-reference/aggregate-functions/reference/timeSeriesLastTwoSamples) | PromQL ライクな irate および idelta 計算向けに時系列データを再サンプリングするための集約関数 | -| [timeSeriesRateToGrid](/sql-reference/aggregate-functions/reference/timeSeriesRateToGrid) | 指定されたグリッド上の時系列データに対して PromQL 風の rate を計算する集約関数。 | -| [timeSeriesResampleToGridWithStaleness](/sql-reference/aggregate-functions/reference/timeSeriesResampleToGridWithStaleness) | 指定したグリッドに従ってタイムシリーズデータを再サンプリングする集約関数。 | -| [timeSeriesDerivToGrid](/sql-reference/aggregate-functions/reference/timeSeriesDerivToGrid) | 指定されたグリッドに沿って、時系列データに対し PromQL 風の微分を計算する集約関数。 | -| [timeSeriesPredictLinearToGrid](/sql-reference/aggregate-functions/reference/timeSeriesPredictLinearToGrid) | 指定されたグリッド上の時系列データに対して、PromQL 風の線形予測を行う集約関数。 | -| [timeSeriesChangesToGrid](/sql-reference/aggregate-functions/reference/timeSeriesChangesToGrid) | 指定したグリッド上の時系列データに対して、PromQL と同様の変化量を計算する集約関数です。 | -| [timeSeriesResetsToGrid](/sql-reference/aggregate-functions/reference/timeSeriesResetsToGrid) | 指定されたグリッド上の時系列データに対して、PromQL 風のリセットを計算する集約関数。 | -| [groupConcat](/sql-reference/aggregate-functions/reference/groupconcat) | 文字列のグループから、必要に応じて区切り文字で区切りながら連結した文字列を生成し、さらに必要に応じて要素数の最大数で制限できます。 | -| [quantilePrometheusHistogram](/sql-reference/aggregate-functions/reference/quantilePrometheusHistogram) | ヒストグラムの分位点を線形補間で計算します。 | +| ページ | 説明 | +| --------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | +| [aggThrow](/sql-reference/aggregate-functions/reference/aggthrow) | この関数は例外安全性をテストするために使用できます。指定した確率で、生成時に例外を送出します。 | +| [analysisOfVariance](/sql-reference/aggregate-functions/reference/analysis_of_variance) | 一元配置分散分析(ANOVA)を行うための統計的検定です。正規分布に従う複数のグループの観測値を対象として、すべてのグループの平均が等しいかどうかを判定するための検定です。 | +| [any](/sql-reference/aggregate-functions/reference/any) | カラム内で最初に出現した値を返します。 | +| [anyHeavy](/sql-reference/aggregate-functions/reference/anyheavy) | heavy hitters アルゴリズムを使用して頻出する値を選択します。各クエリ実行スレッドにおいて、全体の半分を超えて出現する値がある場合、その値が返されます。通常、この結果は決定的ではありません。 | +| [anyLast](/sql-reference/aggregate-functions/reference/anylast) | カラムで最後に見つかった値を返します。 | +| [approx_top_k](/sql-reference/aggregate-functions/reference/approxtopk) | 指定されたカラムにおける、おおよそ最頻出の値とその出現回数の配列を返します。 | +| [approx_top_sum](/sql-reference/aggregate-functions/reference/approxtopsum) | 指定されたカラムにおけるおおよその最頻値とその出現回数からなる配列を返します。 | +| [argMax](/sql-reference/aggregate-functions/reference/argmax) | 最大の `val` 値に対応する `arg` 値を計算します。 | +| [argMin](/sql-reference/aggregate-functions/reference/argmin) | 最小の `val` 値に対応する `arg` の値を計算します。最大値となる同じ `val` を持つ行が複数ある場合、どの関連する `arg` が返されるかは保証されません。 | +| [groupArrayArray](/sql-reference/aggregate-functions/reference/grouparrayarray) | 配列を集約し、それらを要素とする大きな配列を生成します。 | +| [argAndMax](/sql-reference/aggregate-functions/reference/argandmax) | 最大の `val` 値に対応する `arg` と `val` を計算します。最大となる同じ `val` 値を持つ行が複数ある場合、どの行に対応する `arg` と `val` が返されるかは非決定的です。 | +| [argAndMin](/sql-reference/aggregate-functions/reference/argandmin) | 最小の `val` 値に対する `arg` と `val` の値を計算します。最小となる同じ `val` を持つ行が複数存在する場合、どの行に対応する `arg` と `val` が返されるかは保証されません。 | +| [avg](/sql-reference/aggregate-functions/reference/avg) | 算術平均を計算します。 | +| [avgWeighted](/sql-reference/aggregate-functions/reference/avgweighted) | 重み付き平均値を計算します。 | +| [boundingRatio](/sql-reference/aggregate-functions/reference/boundingRatio) | 値のグループ全体で、最も左端の点と最も右端の点を結ぶ直線の傾きを計算する集約関数。 | +| [categoricalInformationValue](/sql-reference/aggregate-functions/reference/categoricalinformationvalue) | 各カテゴリごとに、`(P(tag = 1) - P(tag = 0))(log(P(tag = 1)) - log(P(tag = 0)))` の値を計算します。 | +| [contingency](/sql-reference/aggregate-functions/reference/contingency) | `contingency` 関数は、連関係数(contingency coefficient)を計算します。これは、テーブル内の 2 つのカラム間の関連の強さを測定する値です。計算方法は、平方根の分母が異なる点を除き、`cramersV` 関数と類似しています。 | +| [corr](/sql-reference/aggregate-functions/reference/corr) | ピアソンの相関係数を計算します。 | +| [corrMatrix](/sql-reference/aggregate-functions/reference/corrmatrix) | N 個の変数について相関行列を計算します。 | +| [corrStable](/sql-reference/aggregate-functions/reference/corrstable) | 数値的に安定なアルゴリズムを用いてピアソンの相関係数を計算します。 | +| [count](/sql-reference/aggregate-functions/reference/count) | 行数、または NULL 以外の値の数をカウントします。 | +| [covarPop](/sql-reference/aggregate-functions/reference/covarpop) | 母集団共分散を計算します | +| [covarPopMatrix](/sql-reference/aggregate-functions/reference/covarpopmatrix) | N 個の変数の母共分散行列を返します。 | +| [covarPopStable](/sql-reference/aggregate-functions/reference/covarpopstable) | 母集団共分散の値を計算します | +| [covarSamp](/sql-reference/aggregate-functions/reference/covarsamp) | `Σ((x - x̅)(y - y̅)) / (n - 1)` の値を計算します。 | +| [covarSampMatrix](/sql-reference/aggregate-functions/reference/covarsampmatrix) | N 個の変数に対する標本共分散行列を返します。 | +| [covarSampStable](/sql-reference/aggregate-functions/reference/covarsampstable) | `covarSamp` と同様に動作しますが、計算誤差をより小さく抑えられる反面、処理速度は遅くなります。 | +| [cramersV](/sql-reference/aggregate-functions/reference/cramersv) | `cramersV` 関数の結果は 0(変数間に関連性がないことに対応)から 1 の範囲を取り、各値が互いの値によって完全に決定される場合にのみ 1 になります。これは、2 つの変数間の関連の強さを、それらが取り得る最大限の変動に対する割合として表したものとみなせます。 | +| [cramersVBiasCorrected](/sql-reference/aggregate-functions/reference/cramersvbiascorrected) | Cramer's V をバイアス補正付きで計算します。 | +| [deltaSum](/sql-reference/aggregate-functions/reference/deltasum) | 連続する行同士の算術差を合計します。 | +| [deltaSumTimestamp](/sql-reference/aggregate-functions/reference/deltasumtimestamp) | 連続する行どうしの差分を加算します。差分が負の場合は無視されます。 | +| [entropy](/sql-reference/aggregate-functions/reference/entropy) | 指定したカラムの Shannon エントロピーを計算します。 | +| [estimateCompressionRatio](/sql-reference/aggregate-functions/reference/estimateCompressionRatio) | 指定されたカラムを実際に圧縮することなく、その圧縮率を推定します。 | +| [exponentialMovingAverage](/sql-reference/aggregate-functions/reference/exponentialMovingAverage) | 指定された期間における値の指数移動平均を計算します。 | +| [exponentialTimeDecayedAvg](/sql-reference/aggregate-functions/reference/exponentialTimeDecayedAvg) | 時点 `t` における時系列データの値の指数平滑加重移動平均を返します。 | +| [exponentialTimeDecayedCount](/sql-reference/aggregate-functions/reference/exponentialTimeDecayedCount) | 時刻インデックス `t` における時系列の累積的な指数減衰を返します。 | +| [exponentialTimeDecayedMax](/sql-reference/aggregate-functions/reference/exponentialTimeDecayedMax) | 時間インデックス `t` で計算された指数平滑移動平均と、`t-1` における指数平滑移動平均との最大値を返します。 | +| [exponentialTimeDecayedSum](/sql-reference/aggregate-functions/reference/exponentialTimeDecayedSum) | 時系列における時点 `t` の指数平滑移動平均値の合計を返します。 | +| [first_value](/sql-reference/aggregate-functions/reference/first_value) | `any` と同じ動作をするエイリアスですが、Window Functions との互換性のために導入されました。Window Functions では、場合によっては `NULL` 値を処理する必要があります(デフォルトでは、すべての ClickHouse 集約関数は `NULL` 値を無視します)。 | +| [flameGraph](/sql-reference/aggregate-functions/reference/flame_graph) | スタックトレースの一覧からフレームグラフを構築する集約関数です。 | +| [groupArray](/sql-reference/aggregate-functions/reference/grouparray) | 引数の値の配列を作成します。配列への値の追加順序は任意であり、順序は保証されません。 | +| [groupArrayInsertAt](/sql-reference/aggregate-functions/reference/grouparrayinsertat) | 指定された位置に値を配列に挿入します。 | +| [groupArrayIntersect](/sql-reference/aggregate-functions/reference/grouparrayintersect) | 指定された配列の共通部分(すべての配列に共通して含まれる要素)を返します。 | +| [groupArrayLast](/sql-reference/aggregate-functions/reference/grouparraylast) | 最後の引数の値を要素とする配列を作成します。 | +| [groupArrayMovingAvg](/sql-reference/aggregate-functions/reference/grouparraymovingavg) | 入力値の移動平均を算出します。 | +| [groupArrayMovingSum](/sql-reference/aggregate-functions/reference/grouparraymovingsum) | 入力値の移動合計を計算します。 | +| [groupArraySample](/sql-reference/aggregate-functions/reference/grouparraysample) | サンプルとなる引数値からなる配列を作成します。結果の配列のサイズは `max_size` 要素を上限とします。引数値はランダムに選択され、配列に追加されます。 | +| [timeSeriesGroupArray](/sql-reference/aggregate-functions/reference/timeSeriesGroupArray) | 時系列データをタイムスタンプで昇順にソートします。 | +| [groupArraySorted](/sql-reference/aggregate-functions/reference/grouparraysorted) | 先頭の N 個の要素を昇順に並べた配列を返します。 | +| [groupBitAnd](/sql-reference/aggregate-functions/reference/groupbitand) | 数値列に対してビット単位の `AND` 演算を適用します。 | +| [groupBitmap](/sql-reference/aggregate-functions/reference/groupbitmap) | 符号なし整数カラムからビットマップ計算または集約計算を行い、UInt64 型のカーディナリティを返します。サフィックスに -State を付けた場合は、ビットマップオブジェクトを返します。 | +| [groupBitmapAnd](/sql-reference/aggregate-functions/reference/groupbitmapand) | ビットマップカラム同士の AND を計算し、その結果の基数を UInt64 型で返します。サフィックスに -State を付けると、ビットマップオブジェクトを返します。 | +| [groupBitmapOr](/sql-reference/aggregate-functions/reference/groupbitmapor) | ビットマップカラム同士の OR 演算を行い、その結果の基数を UInt64 型で返します。サフィックス `-State` を付けた場合は、ビットマップオブジェクトを返します。これは `groupBitmapMerge` と等価です。 | +| [groupBitmapXor](/sql-reference/aggregate-functions/reference/groupbitmapxor) | ビットマップカラムに対して XOR を計算し、UInt64 型のカーディナリティ値を返します。サフィックスに -State を付けて使用した場合は、ビットマップオブジェクトを返します。 | +| [groupBitOr](/sql-reference/aggregate-functions/reference/groupbitor) | 一連の数値に対してビット単位の `OR` 演算を適用します。 | +| [groupBitXor](/sql-reference/aggregate-functions/reference/groupbitxor) | 一連の数値に対してビット単位の `XOR` を適用します。 | +| [groupUniqArray](/sql-reference/aggregate-functions/reference/groupuniqarray) | 複数の引数の値から配列を作成します。 | +| [intervalLengthSum](/sql-reference/aggregate-functions/reference/intervalLengthSum) | すべての範囲(数値軸上の線分)の和集合の長さを計算します。 | +| [kolmogorovSmirnovTest](/sql-reference/aggregate-functions/reference/kolmogorovsmirnovtest) | 2つの母集団からの標本に Kolmogorov-Smirnov 検定を適用します。 | +| [kurtPop](/sql-reference/aggregate-functions/reference/kurtpop) | シーケンスの尖度を算出します。 | +| [kurtSamp](/sql-reference/aggregate-functions/reference/kurtsamp) | シーケンスの標本尖度を計算します。 | +| [largestTriangleThreeBuckets](/sql-reference/aggregate-functions/reference/largestTriangleThreeBuckets) | 入力データに Largest-Triangle-Three-Buckets アルゴリズムを適用します。 | +| [last_value](/sql-reference/aggregate-functions/reference/last_value) | `anyLast` と同様に最後に出現した値を選択しますが、NULL も受け付けます。 | +| [mannWhitneyUTest](/sql-reference/aggregate-functions/reference/mannwhitneyutest) | 2つの母集団から得られた標本に対して Mann-Whitney の順位検定を適用します。 | +| [max](/sql-reference/aggregate-functions/reference/max) | 値のグループにおける最大値を計算する集約関数。 | +| [maxIntersections](/sql-reference/aggregate-functions/reference/maxintersections) | すべての区間が少なくとも 1 回は互いに交差する場合に、区間群内での交差回数の最大値を計算する集約関数。 | +| [maxIntersectionsPosition](/sql-reference/aggregate-functions/reference/maxintersectionsposition) | `maxIntersections` 関数の出現位置を計算する集約関数。 | +| [maxMap](/sql-reference/aggregate-functions/reference/maxmap) | `key` 配列で指定されたキーに従って、`value` 配列から最大値を求めます。 | +| [meanZTest](/sql-reference/aggregate-functions/reference/meanztest) | 2つの母集団から得られた標本に対して母平均のZ検定を適用します。 | +| [median](/sql-reference/aggregate-functions/reference/median) | `median*` 関数は、対応する `quantile*` 関数のエイリアスです。数値データ標本の中央値を計算します。 | +| [min](/sql-reference/aggregate-functions/reference/min) | 値グループ内の最小値を計算する集約関数。 | +| [minMap](/sql-reference/aggregate-functions/reference/minmap) | `key` 配列で指定されたキーに基づいて、`value` 配列の最小値を計算します。 | +| [quantile](/sql-reference/aggregate-functions/reference/quantile) | 数値データ系列の近似分位点を計算します。 | +| [quantileBFloat16](/sql-reference/aggregate-functions/reference/quantilebfloat16) | bfloat16 型の値からなるサンプルの近似分位数を計算します。 | +| [quantileDD](/sql-reference/aggregate-functions/reference/quantileddsketch) | 標本の近似分位数を、相対誤差の保証付きで計算します。 | +| [quantileDeterministic](/sql-reference/aggregate-functions/reference/quantiledeterministic) | 数値データ系列の近似分位数を計算します。 | +| [quantileExact 関数](/sql-reference/aggregate-functions/reference/quantileexact) | quantileExact、quantileExactLow、quantileExactHigh、quantileExactExclusive、quantileExactInclusive 関数 | +| [quantileExactWeighted](/sql-reference/aggregate-functions/reference/quantileexactweighted) | 各要素の重みを考慮に入れて、数値データ系列の分位点を厳密に計算します。 | +| [quantileGK](/sql-reference/aggregate-functions/reference/quantileGK) | Greenwald-Khanna アルゴリズムを使用して、数値データ系列の分位数を計算します。 | +| [quantileExactWeightedInterpolated](/sql-reference/aggregate-functions/reference/quantileExactWeightedInterpolated) | 各要素の重みを考慮しつつ、線形補間により数値データ列の分位数を計算します。 | +| [quantileInterpolatedWeighted](/sql-reference/aggregate-functions/reference/quantileInterpolatedWeighted) | 各要素の重みを考慮し、線形補間を用いて数値データ系列の分位数を計算します。 | +| [quantiles 関数](/sql-reference/aggregate-functions/reference/quantiles) | quantiles, quantilesExactExclusive, quantilesExactInclusive, quantilesGK | +| [quantileTDigest](/sql-reference/aggregate-functions/reference/quantiletdigest) | t-digest アルゴリズムを使用して、数値データ系列の近似分位数を計算します。 | +| [quantileTDigestWeighted](/sql-reference/aggregate-functions/reference/quantiletdigestweighted) | t-digest アルゴリズムを使用して、数値データ系列の近似分位数を計算します。 | +| [quantileTiming](/sql-reference/aggregate-functions/reference/quantiletiming) | 指定された精度で数値データ列の分位数を計算します。 | +| [quantileTimingWeighted](/sql-reference/aggregate-functions/reference/quantiletimingweighted) | 所定の精度で、各シーケンス要素に対する重みに基づき、数値データシーケンスの分位数を計算します。 | +| [rankCorr](/sql-reference/aggregate-functions/reference/rankCorr) | 順位相関係数を計算します。 | +| [simpleLinearRegression](/sql-reference/aggregate-functions/reference/simplelinearregression) | 1 次元の単純な線形回帰を実行します。 | +| [singleValueOrNull](/sql-reference/aggregate-functions/reference/singlevalueornull) | 集約関数 `singleValueOrNull` は、`x = ALL (SELECT ...)` のようなサブクエリ演算子を実装するために使用されます。データ内に一意の非 NULL 値がちょうど 1 つだけ存在するかどうかを確認します。 | +| [skewPop](/sql-reference/aggregate-functions/reference/skewpop) | シーケンスの歪度を算出します。 | +| [skewSamp](/sql-reference/aggregate-functions/reference/skewsamp) | シーケンスの標本歪度を計算します。 | +| [sparkbar](/sql-reference/aggregate-functions/reference/sparkbar) | この関数は、区間 `[min_x, max_x]` における値 `x` の出現頻度 `y` に基づく度数ヒストグラムをプロットします。 | +| [stddevPop](/sql-reference/aggregate-functions/reference/stddevpop) | 結果はvarPopの平方根と等しくなります。 | +| [stddevPopStable](/sql-reference/aggregate-functions/reference/stddevpopstable) | 結果は varPop の平方根と同じです。stddevPop とは異なり、この関数は数値的に安定なアルゴリズムを用います。 | +| [stddevSamp](/sql-reference/aggregate-functions/reference/stddevsamp) | 結果は varSamp の平方根と等しくなります | +| [stddevSampStable](/sql-reference/aggregate-functions/reference/stddevsampstable) | 結果は varSamp の平方根と同じです。stddevSamp とは異なり、この関数では数値的に安定したアルゴリズムを使用しています。 | +| [stochasticLinearRegression](/sql-reference/aggregate-functions/reference/stochasticlinearregression) | この関数は確率的線形回帰を実装します。学習率、L2 正則化係数、ミニバッチサイズなどのカスタマイズ可能なパラメータをサポートし、重み更新のための複数の手法(Adam、単純な SGD、Momentum、Nesterov)を備えています。 | +| [stochasticLogisticRegression](/sql-reference/aggregate-functions/reference/stochasticlogisticregression) | この関数は確率的ロジスティック回帰を実装します。二値分類問題に使用でき、`stochasticLinearRegression` と同じカスタムパラメータをサポートし、同様に動作します。 | +| [studentTTest](/sql-reference/aggregate-functions/reference/studentttest) | 2つの母集団からの標本にスチューデントの t 検定を適用します。 | +| [studentTTestOneSample](/sql-reference/aggregate-functions/reference/studentttestonesample) | 既知の母平均に対して標本に 1 標本 Student の t 検定を適用します。 | +| [sum](/sql-reference/aggregate-functions/reference/sum) | 合計を計算します。数値に対してのみ使用できます。 | +| [sumCount](/sql-reference/aggregate-functions/reference/sumcount) | 数値の合計を計算すると同時に、行数をカウントします。この関数は ClickHouse のクエリオプティマイザによって使用されます。クエリ内に複数の `sum`、`count`、`avg` 関数がある場合、それらを単一の `sumCount` 関数に置き換えて計算結果を再利用できます。この関数を明示的に使用する必要が生じることはほとんどありません。 | +| [sumKahan](/sql-reference/aggregate-functions/reference/sumkahan) | Kahan の補償和アルゴリズムを用いて数値の総和を計算します | +| [sumMap](/sql-reference/aggregate-functions/reference/summap) | `key` 配列で指定されたキーに従って、1 つ以上の `value` 配列を合計します。キーをソートした配列と、それぞれのキーに対応する値をオーバーフローなしで合計した配列からなるタプルを返します。 | +| [sumMapWithOverflow](/sql-reference/aggregate-functions/reference/summapwithoverflow) | `key` 配列で指定されたキーに従って `value` 配列を集計します。戻り値は 2 つの配列から成るタプルであり、ソート済みのキー配列と、各キーに対応する値を合計した配列を返します。オーバーフローを許容して加算を行う点で、sumMap 関数と異なります。 | +| [sumWithOverflow](/sql-reference/aggregate-functions/reference/sumwithoverflow) | 入力パラメータと同じデータ型を結果にも使用して数値の合計を計算します。合計がこのデータ型の最大値を超えた場合、オーバーフローして計算されます。 | +| [theilsU](/sql-reference/aggregate-functions/reference/theilsu) | `theilsU` 関数は、Theil の U 不確実性係数を計算します。これは、テーブル内の 2 つのカラム間の関連性を測定する値です。 | +| [topK](/sql-reference/aggregate-functions/reference/topk) | 指定されたカラム内で、おおよそ最も頻繁に現れる値の配列を返します。結果の配列は、値そのものではなく、そのおおよその出現頻度に基づいて高い順にソートされます。 | +| [topKWeighted](/sql-reference/aggregate-functions/reference/topkweighted) | 指定されたカラム内の最頻値を近似的に求め、その値の配列を返します。返される配列は、値そのものではなく、値の近似的な出現頻度に基づいて高い順にソートされます。また、値の重みも考慮されます。 | +| [uniq](/sql-reference/aggregate-functions/reference/uniq) | 引数が取りうる異なる値のおおよその個数を計算します。 | +| [uniqCombined](/sql-reference/aggregate-functions/reference/uniqcombined) | 引数に現れる異なる値のおおよその個数を計算します。 | +| [uniqCombined64](/sql-reference/aggregate-functions/reference/uniqcombined64) | 引数値の異なるもののおおよその個数を計算します。`uniqCombined` と同じですが、`String` データ型だけでなく、すべてのデータ型に対して 64 ビットハッシュを使用します。 | +| [uniqExact](/sql-reference/aggregate-functions/reference/uniqexact) | 引数の異なる値の個数を正確に計算します。 | +| [uniqHLL12](/sql-reference/aggregate-functions/reference/uniqhll12) | HyperLogLog アルゴリズムを使用して、引数が取りうる異なる値のおおよその個数を計算します。 | +| [uniqTheta](/sql-reference/aggregate-functions/reference/uniqthetasketch) | Theta Sketch Framework を使用して、引数の異なる値のおおよその個数を計算します。 | +| [varPop](/sql-reference/aggregate-functions/reference/varPop) | 母分散を計算します。 | +| [varPopStable](/sql-reference/aggregate-functions/reference/varpopstable) | 母分散を返します。`varPop` とは異なり、この関数は数値的に安定なアルゴリズムを使用します。動作は遅くなりますが、計算誤差をより小さく抑えられます。 | +| [varSamp](/sql-reference/aggregate-functions/reference/varSamp) | データセットの標本分散を計算します。 | +| [varSampStable](/sql-reference/aggregate-functions/reference/varsampstable) | データセットの標本分散を計算します。`varSamp` とは異なり、この関数は数値的に安定なアルゴリズムを使用します。処理は遅くなりますが、計算誤差は小さくなります。 | +| [welchTTest](/sql-reference/aggregate-functions/reference/welchttest) | 2つの母集団からの標本に対して Welch の t 検定を適用します。 | +| [distinctDynamicTypes](/sql-reference/aggregate-functions/reference/distinctdynamictypes) | Dynamic カラムに格納されているデータ型の種類の一覧を返します。 | +| [distinctJSONPaths](/sql-reference/aggregate-functions/reference/distinctjsonpaths) | JSONカラムに保存されているパスのうち、重複を除いたリストを計算します。 | +| [timeSeriesDeltaToGrid](/sql-reference/aggregate-functions/reference/timeSeriesDeltaToGrid) | 指定されたグリッドに沿って、時系列データに対し PromQL 風の delta を計算する集約関数。 | +| [timeSeriesInstantDeltaToGrid](/sql-reference/aggregate-functions/reference/timeSeriesInstantDeltaToGrid) | 指定したグリッドに従い、時系列データに対して PromQL 風の idelta を計算する集約関数。 | +| [timeSeriesInstantRateToGrid](/sql-reference/aggregate-functions/reference/timeSeriesInstantRateToGrid) | 指定されたグリッド上の時系列データに対して、PromQL ライクな irate を計算する集約関数。 | +| [timeSeriesLastTwoSamples](/sql-reference/aggregate-functions/reference/timeSeriesLastTwoSamples) | PromQL 風の irate および idelta 計算のために時系列データを再サンプリングする集約関数 | +| [timeSeriesRateToGrid](/sql-reference/aggregate-functions/reference/timeSeriesRateToGrid) | 指定されたグリッドに沿って時系列データの PromQL 風 rate を計算する集約関数。 | +| [timeSeriesResampleToGridWithStaleness](/sql-reference/aggregate-functions/reference/timeSeriesResampleToGridWithStaleness) | 指定したグリッドに従って時系列データを再サンプリングする集約関数。 | +| [timeSeriesDerivToGrid](/sql-reference/aggregate-functions/reference/timeSeriesDerivToGrid) | 指定されたグリッドに従って時系列データに対し PromQL 風の微分を計算する集約関数。 | +| [timeSeriesPredictLinearToGrid](/sql-reference/aggregate-functions/reference/timeSeriesPredictLinearToGrid) | 指定されたグリッド上の時系列データに対して、PromQL 風の線形予測を計算する集約関数。 | +| [timeSeriesChangesToGrid](/sql-reference/aggregate-functions/reference/timeSeriesChangesToGrid) | 指定したグリッドに従って時系列データの PromQL ライクな変化量を計算する集約関数。 | +| [timeSeriesResetsToGrid](/sql-reference/aggregate-functions/reference/timeSeriesResetsToGrid) | 指定されたグリッド上の時系列データに対して、PromQL の reset 関数に類似したリセット処理を計算する集約関数。 | +| [groupConcat](/sql-reference/aggregate-functions/reference/groupconcat) | 文字列のグループから連結された文字列を計算します。必要に応じて区切り文字を指定でき、連結する要素数の上限も設定できます。 | +| [quantilePrometheusHistogram](/sql-reference/aggregate-functions/reference/quantilePrometheusHistogram) | 線形補間を用いてヒストグラムの分位数を計算します。 | {/*AUTOGENERATED_END*/ } diff --git a/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/intervalLengthSum.md b/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/intervalLengthSum.md index f65bd120aa1..8a2bb175463 100644 --- a/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/intervalLengthSum.md +++ b/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/intervalLengthSum.md @@ -86,7 +86,6 @@ SELECT id, intervalLengthSum(start, end), toTypeName(intervalLengthSum(start, en 3. 入力テーブル: - ```text ┌─id─┬──────start─┬────────end─┐ │ a │ 2020-01-01 │ 2020-01-04 │ diff --git a/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/dictionaries/index.md b/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/dictionaries/index.md index 72d77c728f8..3c8c14b10df 100644 --- a/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/dictionaries/index.md +++ b/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/dictionaries/index.md @@ -10,6 +10,8 @@ doc_type: 'reference' import SelfManaged from '@site/i18n/jp/docusaurus-plugin-content-docs/current/_snippets/_self_managed_only_no_roadmap.md'; import CloudDetails from '@site/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/dictionaries/_snippet_dictionary_in_cloud.md'; import CloudNotSupportedBadge from '@theme/badges/CloudNotSupportedBadge'; +import ExperimentalBadge from '@theme/badges/ExperimentalBadge'; + # Dictionaries {#dictionaries} @@ -1053,7 +1055,7 @@ Dictionary を XML ファイルで構成する場合、設定は次のように ... - + ... @@ -1067,7 +1069,7 @@ Dictionary を XML ファイルで構成する場合、設定は次のように ```sql CREATE DICTIONARY dict_name (...) ... -SOURCE(SOURCE_TYPE(param1 val1 ... paramN valN)) -- ソースの設定 +SOURCE(SOURCE_TYPE(param1 val1 ... paramN valN)) -- Source configuration ... ``` @@ -1109,6 +1111,8 @@ SETTINGS(format_csv_allow_single_quotes = 0) * [Redis](#redis) * [Cassandra](#cassandra) * [PostgreSQL](#postgresql) + * [YTsaurus](#ytsaurus) + ### ローカル ファイル {#local-file} @@ -1893,6 +1897,47 @@ SOURCE(POSTGRESQL( `table` フィールドまたは `where` フィールドは、`query` フィールドと同時に使用することはできません。また、`table` フィールドまたは `query` フィールドのいずれか一方は必ず宣言する必要があります。 ::: +### YTsaurus {#ytsaurus} + + + + + +:::info +これは実験的な機能であり、今後のリリースで後方互換性のない変更が行われる可能性があります。 +YTsaurus を Dictionary ソースとして利用するには、設定 [`allow_experimental_ytsaurus_dictionary_source`](/operations/settings/settings#allow_experimental_ytsaurus_dictionary_source) を有効にします。 +::: + +設定例: + +```xml + + + http://localhost:8000 + //tmp/test + password + 1 + + +``` + +または + +```sql +SOURCE(YTSAURUS( + http_proxy_urls 'http://localhost:8000' + cypress_path '//tmp/test' + oauth_token 'password' +)) +``` + +設定フィールド: + +* `http_proxy_urls` – YTsaurus HTTP プロキシへの URL。 +* `cypress_path` – テーブルのソースとなる Cypress パス。 +* `oauth_token` – OAuth トークン。 + + ### Null {#null} ダミー(空)のディクショナリを作成するために使用できる特別なソースです。このようなディクショナリは、テスト用途や、データノードとクエリノードを分離し、ノード上に Distributed テーブルを持つ構成で役立ちます。 diff --git a/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/statements/select/offset.md b/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/statements/select/offset.md index f7c25af81f2..2ecb855352b 100644 --- a/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/statements/select/offset.md +++ b/i18n/jp/docusaurus-plugin-content-docs/current/sql-reference/statements/select/offset.md @@ -9,7 +9,11 @@ doc_type: 'reference' `OFFSET` と `FETCH` を使用すると、データを一定量ずつ取得できます。これらは、1 回のクエリで取得したい行のブロックを指定します。 ```sql -OFFSET offset_row_count {ROW | ROWS}] [FETCH {FIRST | NEXT} fetch_row_count {ROW | ROWS} {ONLY | WITH TIES}] +-- SQL Standard style: +[OFFSET offset_row_count {ROW | ROWS}] [FETCH {FIRST | NEXT} fetch_row_count {ROW | ROWS} {ONLY | WITH TIES}] + +-- MySQL/PostgreSQL style: +[LIMIT [n, ]m] [OFFSET offset_row_count] ``` `offset_row_count` または `fetch_row_count` の値には、数値またはリテラル定数を指定できます。`fetch_row_count` は省略可能で、省略した場合のデフォルト値は 1 です。 @@ -35,7 +39,7 @@ OFFSET offset_row_count {ROW | ROWS}] [FETCH {FIRST | NEXT} fetch_row_count {ROW SELECT * FROM test_fetch ORDER BY a OFFSET 1 ROW FETCH FIRST 3 ROWS ONLY; ``` -クエリと同じです +次のクエリと同じです ```sql SELECT * FROM test_fetch ORDER BY a LIMIT 3 OFFSET 1; @@ -67,7 +71,7 @@ SELECT * FROM test_fetch ORDER BY a LIMIT 3 OFFSET 1; └───┴───┘ ``` -`ONLY` オプションの使用方法: +`ONLY` オプションの使用例: ```sql SELECT * FROM test_fetch ORDER BY a OFFSET 3 ROW FETCH FIRST 3 ROWS ONLY; @@ -83,7 +87,7 @@ SELECT * FROM test_fetch ORDER BY a OFFSET 3 ROW FETCH FIRST 3 ROWS ONLY; └───┴───┘ ``` -`WITH TIES` オプションの使用方法: +`WITH TIES` オプションの使用方法: ```sql SELECT * FROM test_fetch ORDER BY a OFFSET 3 ROW FETCH FIRST 3 ROWS WITH TIES; diff --git a/i18n/jp/docusaurus-plugin-content-docs/current/use-cases/observability/clickstack/deployment/docker-compose.md b/i18n/jp/docusaurus-plugin-content-docs/current/use-cases/observability/clickstack/deployment/docker-compose.md index 93ea60836db..8e5fe1634c6 100644 --- a/i18n/jp/docusaurus-plugin-content-docs/current/use-cases/observability/clickstack/deployment/docker-compose.md +++ b/i18n/jp/docusaurus-plugin-content-docs/current/use-cases/observability/clickstack/deployment/docker-compose.md @@ -48,10 +48,10 @@ Docker Compose は、デフォルトの `otel-collector` セットアップに ### リポジトリをクローンする {#clone-the-repo} -Docker Compose を使用してデプロイするには、HyperDX リポジトリをクローンし、そのディレクトリに移動して `docker-compose up` を実行します: +Docker Compose を使用してデプロイするには、ClickStack リポジトリをクローンし、そのディレクトリに移動して `docker-compose up` を実行します: ```shell -git clone git@github.com:hyperdxio/hyperdx.git +git clone https://github.com/ClickHouse/ClickStack.git docker compose up ``` @@ -61,7 +61,7 @@ docker compose up ユーザー名と、要件を満たすパスワードを入力してユーザーを作成します。 -`Create` をクリックすると、Helm チャートでデプロイされた ClickHouse インスタンス用のデータソースが作成されます。 +`Create` をクリックすると、Docker Compose でデプロイされた ClickHouse インスタンス用のデータソースが作成されます。 :::note 既定の接続の上書き 統合された ClickHouse インスタンスへの既定の接続は上書きできます。詳細については、「[Using ClickHouse Cloud](#using-clickhouse-cloud)」を参照してください。 @@ -88,34 +88,31 @@ docker compose up ユーザーは、使用するバージョンなどのスタック設定を、環境変数ファイルで変更できます。 ```shell -user@example-host hyperdx % cat .env -# docker-compose.yml で使用 {#used-by-docker-composeyml} -# docker-compose.yml で使用 {#used-by-docker-composeyml} -HDX_IMAGE_REPO=docker.hyperdx.io -IMAGE_NAME=ghcr.io/hyperdxio/hyperdx -IMAGE_NAME_DOCKERHUB=hyperdx/hyperdx -LOCAL_IMAGE_NAME=ghcr.io/hyperdxio/hyperdx-local -LOCAL_IMAGE_NAME_DOCKERHUB=hyperdx/hyperdx-local -ALL_IN_ONE_IMAGE_NAME=ghcr.io/hyperdxio/hyperdx-all-in-one -ALL_IN_ONE_IMAGE_NAME_DOCKERHUB=hyperdx/hyperdx-all-in-one -OTEL_COLLECTOR_IMAGE_NAME=ghcr.io/hyperdxio/hyperdx-otel-collector -OTEL_COLLECTOR_IMAGE_NAME_DOCKERHUB=hyperdx/hyperdx-otel-collector -CODE_VERSION=2.0.0-beta.16 -IMAGE_VERSION_SUB_TAG=.16 -IMAGE_VERSION=2-beta +user@example-host clickstack % cat .env + +# Used by docker-compose.yml +IMAGE_NAME_DOCKERHUB=clickhouse/clickstack-all-in-one +LOCAL_IMAGE_NAME_DOCKERHUB=clickhouse/clickstack-local +ALL_IN_ONE_IMAGE_NAME_DOCKERHUB=clickhouse/clickstack-all-in-one +OTEL_COLLECTOR_IMAGE_NAME_DOCKERHUB=clickhouse/clickstack-otel-collector +CODE_VERSION=2.8.0 +IMAGE_VERSION_SUB_TAG=.8.0 +IMAGE_VERSION=2 IMAGE_NIGHTLY_TAG=2-nightly +IMAGE_LATEST_TAG=latest -# ドメイン URL の設定 {#set-up-domain-urls} -HYPERDX_API_PORT=8000 # 任意(他のサービスで使用されていないポートを指定すること) +# Set up domain URLs +HYPERDX_API_PORT=8000 #optional (should not be taken by other services) HYPERDX_APP_PORT=8080 HYPERDX_APP_URL=http://localhost HYPERDX_LOG_LEVEL=debug HYPERDX_OPAMP_PORT=4320 -# OTel/ClickHouse 設定 {#otelclickhouse-config} +# Otel/Clickhouse config HYPERDX_OTEL_EXPORTER_CLICKHOUSE_DATABASE=default ``` + ### OpenTelemetry collector の設定 {#configuring-collector} 必要に応じて OTel collector の設定を変更できます。設定の変更方法の詳細は、["Modifying configuration"](/use-cases/observability/clickstack/ingesting-data/otel-collector#modifying-otel-collector-configuration) を参照してください。 @@ -124,13 +121,13 @@ HYPERDX_OTEL_EXPORTER_CLICKHOUSE_DATABASE=default このディストリビューションは ClickHouse Cloud と併用できます。ユーザーは次の手順を実行してください: -* `docker-compose.yaml` ファイルから ClickHouse のサービスを削除します。テスト用途であれば任意で、削除しない場合はデプロイされた ClickHouse インスタンスは単に無視されますが、ローカルリソースを無駄に消費します。サービスを削除する場合は、`depends_on` など当該サービスへの参照も削除してください。 +* `docker-compose.yml` ファイルから ClickHouse のサービスを削除します。テスト用途であれば任意で、削除しない場合はデプロイされた ClickHouse インスタンスは単に無視されますが、ローカルリソースを無駄に消費します。サービスを削除する場合は、`depends_on` など当該サービスへの参照も削除してください。 * compose ファイル内で環境変数 `CLICKHOUSE_ENDPOINT`、`CLICKHOUSE_USER`、`CLICKHOUSE_PASSWORD` を設定し、OTel collector が ClickHouse Cloud インスタンスを使用するように変更します。具体的には、OTel collector サービスにこれらの環境変数を追加します: ```shell otel-collector: - image: ${OTEL_COLLECTOR_IMAGE_NAME}:${IMAGE_VERSION} + image: ${OTEL_COLLECTOR_IMAGE_NAME_DOCKERHUB}:${IMAGE_VERSION} environment: CLICKHOUSE_ENDPOINT: '' # ここに https エンドポイントを指定 CLICKHOUSE_USER: '' @@ -155,25 +152,25 @@ HYPERDX_OTEL_EXPORTER_CLICKHOUSE_DATABASE=default -これらを設定するには、`docker-compose.yaml` 内の該当するサービスを編集します: +これらを設定するには、`docker-compose.yml` 内の該当するサービスを編集します: ```yaml app: - image: ${HDX_IMAGE_REPO}/${IMAGE_NAME_DOCKERHUB}:${IMAGE_VERSION} + image: ${IMAGE_NAME_DOCKERHUB}:${IMAGE_VERSION} ports: - ${HYPERDX_API_PORT}:${HYPERDX_API_PORT} - ${HYPERDX_APP_PORT}:${HYPERDX_APP_PORT} environment: - BETA_CH_OTEL_JSON_SCHEMA_ENABLED: true # JSONを有効化 + BETA_CH_OTEL_JSON_SCHEMA_ENABLED: true # enable JSON FRONTEND_URL: ${HYPERDX_APP_URL}:${HYPERDX_APP_PORT} HYPERDX_API_KEY: ${HYPERDX_API_KEY} HYPERDX_API_PORT: ${HYPERDX_API_PORT} - # 簡潔さのため省略 + # truncated for brevity otel-collector: - image: ${HDX_IMAGE_REPO}/${OTEL_COLLECTOR_IMAGE_NAME_DOCKERHUB}:${IMAGE_VERSION} + image: ${OTEL_COLLECTOR_IMAGE_NAME_DOCKERHUB}:${IMAGE_VERSION} environment: - OTEL_AGENT_FEATURE_GATE_ARG: '--feature-gates=clickhouse.json' # JSONを有効化 + OTEL_AGENT_FEATURE_GATE_ARG: '--feature-gates=clickhouse.json' # enable JSON CLICKHOUSE_ENDPOINT: 'tcp://ch-server:9000?dial_timeout=10s' - # 簡潔さのため省略 + # truncated for brevity ``` diff --git a/i18n/ru/docusaurus-plugin-content-docs/current/about-us/beta-and-experimental-features.md b/i18n/ru/docusaurus-plugin-content-docs/current/about-us/beta-and-experimental-features.md index 429e9ead11a..b1b49389d39 100644 --- a/i18n/ru/docusaurus-plugin-content-docs/current/about-us/beta-and-experimental-features.md +++ b/i18n/ru/docusaurus-plugin-content-docs/current/about-us/beta-and-experimental-features.md @@ -94,76 +94,77 @@ doc_type: 'reference' ## Экспериментальные настройки {#experimental-settings} -| Имя | По умолчанию | -| ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------- | -| [allow_experimental_replacing_merge_with_cleanup](/operations/settings/merge-tree-settings#allow_experimental_replacing_merge_with_cleanup) | `0` | -| [allow_experimental_reverse_key](/operations/settings/merge-tree-settings#allow_experimental_reverse_key) | `0` | -| [allow_remote_fs_zero_copy_replication](/operations/settings/merge-tree-settings#allow_remote_fs_zero_copy_replication) | `0` | -| [enable_replacing_merge_with_cleanup_for_min_age_to_force_merge](/operations/settings/merge-tree-settings#enable_replacing_merge_with_cleanup_for_min_age_to_force_merge) | `0` | -| [force_read_through_cache_for_merges](/operations/settings/merge-tree-settings#force_read_through_cache_for_merges) | `0` | -| [merge_selector_algorithm](/operations/settings/merge-tree-settings#merge_selector_algorithm) | `Simple` | -| [notify_newest_block_number](/operations/settings/merge-tree-settings#notify_newest_block_number) | `0` | -| [part_moves_between_shards_delay_seconds](/operations/settings/merge-tree-settings#part_moves_between_shards_delay_seconds) | `30` | -| [part_moves_between_shards_enable](/operations/settings/merge-tree-settings#part_moves_between_shards_enable) | `0` | -| [remote_fs_zero_copy_path_compatible_mode](/operations/settings/merge-tree-settings#remote_fs_zero_copy_path_compatible_mode) | `0` | -| [remote_fs_zero_copy_zookeeper_path](/operations/settings/merge-tree-settings#remote_fs_zero_copy_zookeeper_path) | `/clickhouse/zero_copy` | -| [remove_rolled_back_parts_immediately](/operations/settings/merge-tree-settings#remove_rolled_back_parts_immediately) | `1` | -| [shared_merge_tree_virtual_parts_discovery_batch](/operations/settings/merge-tree-settings#shared_merge_tree_virtual_parts_discovery_batch) | `1` | -| [allow_experimental_kafka_offsets_storage_in_keeper](/operations/settings/settings#allow_experimental_kafka_offsets_storage_in_keeper) | `0` | -| [allow_experimental_delta_lake_writes](/operations/settings/settings#allow_experimental_delta_lake_writes) | `0` | -| [allow_experimental_materialized_postgresql_table](/operations/settings/settings#allow_experimental_materialized_postgresql_table) | `0` | -| [allow_experimental_funnel_functions](/operations/settings/settings#allow_experimental_funnel_functions) | `0` | -| [allow_experimental_nlp_functions](/operations/settings/settings#allow_experimental_nlp_functions) | `0` | -| [allow_experimental_hash_functions](/operations/settings/settings#allow_experimental_hash_functions) | `0` | -| [allow_experimental_time_series_table](/operations/settings/settings#allow_experimental_time_series_table) | `0` | -| [allow_experimental_codecs](/operations/settings/settings#allow_experimental_codecs) | `0` | -| [throw_on_unsupported_query_inside_transaction](/operations/settings/settings#throw_on_unsupported_query_inside_transaction) | `1` | -| [wait_changes_become_visible_after_commit_mode](/operations/settings/settings#wait_changes_become_visible_after_commit_mode) | `wait_unknown` | -| [implicit_transaction](/operations/settings/settings#implicit_transaction) | `0` | -| [grace_hash_join_initial_buckets](/operations/settings/settings#grace_hash_join_initial_buckets) | `1` | -| [grace_hash_join_max_buckets](/operations/settings/settings#grace_hash_join_max_buckets) | `1024` | -| [join_to_sort_minimum_perkey_rows](/operations/settings/settings#join_to_sort_minimum_perkey_rows) | `40` | -| [join_to_sort_maximum_table_rows](/operations/settings/settings#join_to_sort_maximum_table_rows) | `10000` | -| [allow_experimental_join_right_table_sorting](/operations/settings/settings#allow_experimental_join_right_table_sorting) | `0` | -| [allow_experimental_statistics](/operations/settings/settings#allow_experimental_statistics) | `0` | -| [use_statistics_cache](/operations/settings/settings#use_statistics_cache) | `0` | -| [allow_experimental_full_text_index](/operations/settings/settings#allow_experimental_full_text_index) | `0` | -| [allow_experimental_window_view](/operations/settings/settings#allow_experimental_window_view) | `0` | -| [window_view_clean_interval](/operations/settings/settings#window_view_clean_interval) | `60` | -| [window_view_heartbeat_interval](/operations/settings/settings#window_view_heartbeat_interval) | `15` | -| [wait_for_window_view_fire_signal_timeout](/operations/settings/settings#wait_for_window_view_fire_signal_timeout) | `10` | -| [stop_refreshable_materialized_views_on_startup](/operations/settings/settings#stop_refreshable_materialized_views_on_startup) | `0` | -| [allow_experimental_database_materialized_postgresql](/operations/settings/settings#allow_experimental_database_materialized_postgresql) | `0` | -| [allow_experimental_qbit_type](/operations/settings/settings#allow_experimental_qbit_type) | `0` | -| [allow_experimental_query_deduplication](/operations/settings/settings#allow_experimental_query_deduplication) | `0` | -| [allow_experimental_database_hms_catalog](/operations/settings/settings#allow_experimental_database_hms_catalog) | `0` | -| [allow_experimental_kusto_dialect](/operations/settings/settings#allow_experimental_kusto_dialect) | `0` | -| [allow_experimental_prql_dialect](/operations/settings/settings#allow_experimental_prql_dialect) | `0` | -| [enable_adaptive_memory_spill_scheduler](/operations/settings/settings#enable_adaptive_memory_spill_scheduler) | `0` | -| [allow_experimental_insert_into_iceberg](/operations/settings/settings#allow_experimental_insert_into_iceberg) | `0` | -| [allow_experimental_iceberg_compaction](/operations/settings/settings#allow_experimental_iceberg_compaction) | `0` | -| [write_full_path_in_iceberg_metadata](/operations/settings/settings#write_full_path_in_iceberg_metadata) | `0` | -| [iceberg_metadata_compression_method](/operations/settings/settings#iceberg_metadata_compression_method) | `` | -| [make_distributed_plan](/operations/settings/settings#make_distributed_plan) | `0` | -| [distributed_plan_execute_locally](/operations/settings/settings#distributed_plan_execute_locally) | `0` | -| [distributed_plan_default_shuffle_join_bucket_count](/operations/settings/settings#distributed_plan_default_shuffle_join_bucket_count) | `8` | -| [distributed_plan_default_reader_bucket_count](/operations/settings/settings#distributed_plan_default_reader_bucket_count) | `8` | -| [distributed_plan_force_exchange_kind](/operations/settings/settings#distributed_plan_force_exchange_kind) | `` | -| [distributed_plan_max_rows_to_broadcast](/operations/settings/settings#distributed_plan_max_rows_to_broadcast) | `20000` | -| [allow_experimental_ytsaurus_table_engine](/operations/settings/settings#allow_experimental_ytsaurus_table_engine) | `0` | -| [allow_experimental_ytsaurus_table_function](/operations/settings/settings#allow_experimental_ytsaurus_table_function) | `0` | -| [allow_experimental_ytsaurus_dictionary_source](/operations/settings/settings#allow_experimental_ytsaurus_dictionary_source) | `0` | -| [distributed_plan_force_shuffle_aggregation](/operations/settings/settings#distributed_plan_force_shuffle_aggregation) | `0` | -| [enable_join_runtime_filters](/operations/settings/settings#enable_join_runtime_filters) | `0` | -| [join_runtime_filter_exact_values_limit](/operations/settings/settings#join_runtime_filter_exact_values_limit) | `10000` | -| [join_runtime_bloom_filter_bytes](/operations/settings/settings#join_runtime_bloom_filter_bytes) | `524288` | -| [join_runtime_bloom_filter_hash_functions](/operations/settings/settings#join_runtime_bloom_filter_hash_functions) | `3` | -| [rewrite_in_to_join](/operations/settings/settings#rewrite_in_to_join) | `0` | -| [allow_experimental_time_series_aggregate_functions](/operations/settings/settings#allow_experimental_time_series_aggregate_functions) | `0` | -| [promql_database](/operations/settings/settings#promql_database) | `` | -| [promql_table](/operations/settings/settings#promql_table) | `` | -| [promql_evaluation_time](/operations/settings/settings#promql_evaluation_time) | `auto` | -| [allow_experimental_alias_table_engine](/operations/settings/settings#allow_experimental_alias_table_engine) | `0` | -| [use_paimon_partition_pruning](/operations/settings/settings#use_paimon_partition_pruning) | `0` | +| Имя | По умолчанию | +| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------- | +| [allow_experimental_kafka_offsets_storage_in_keeper](/operations/settings/settings#allow_experimental_kafka_offsets_storage_in_keeper) | `0` | +| [allow_experimental_delta_lake_writes](/operations/settings/settings#allow_experimental_delta_lake_writes) | `0` | +| [allow_experimental_materialized_postgresql_table](/operations/settings/settings#allow_experimental_materialized_postgresql_table) | `0` | +| [allow_experimental_funnel_functions](/operations/settings/settings#allow_experimental_funnel_functions) | `0` | +| [allow_experimental_nlp_functions](/operations/settings/settings#allow_experimental_nlp_functions) | `0` | +| [allow_experimental_hash_functions](/operations/settings/settings#allow_experimental_hash_functions) | `0` | +| [allow_experimental_time_series_table](/operations/settings/settings#allow_experimental_time_series_table) | `0` | +| [allow_experimental_codecs](/operations/settings/settings#allow_experimental_codecs) | `0` | +| [throw_on_unsupported_query_inside_transaction](/operations/settings/settings#throw_on_unsupported_query_inside_transaction) | `1` | +| [wait_changes_become_visible_after_commit_mode](/operations/settings/settings#wait_changes_become_visible_after_commit_mode) | `wait_unknown` | +| [implicit_transaction](/operations/settings/settings#implicit_transaction) | `0` | +| [grace_hash_join_initial_buckets](/operations/settings/settings#grace_hash_join_initial_buckets) | `1` | +| [grace_hash_join_max_buckets](/operations/settings/settings#grace_hash_join_max_buckets) | `1024` | +| [join_to_sort_minimum_perkey_rows](/operations/settings/settings#join_to_sort_minimum_perkey_rows) | `40` | +| [join_to_sort_maximum_table_rows](/operations/settings/settings#join_to_sort_maximum_table_rows) | `10000` | +| [allow_experimental_join_right_table_sorting](/operations/settings/settings#allow_experimental_join_right_table_sorting) | `0` | +| [allow_experimental_statistics](/operations/settings/settings#allow_experimental_statistics) | `0` | +| [use_statistics_cache](/operations/settings/settings#use_statistics_cache) | `0` | +| [allow_experimental_full_text_index](/operations/settings/settings#allow_experimental_full_text_index) | `0` | +| [allow_experimental_window_view](/operations/settings/settings#allow_experimental_window_view) | `0` | +| [window_view_clean_interval](/operations/settings/settings#window_view_clean_interval) | `60` | +| [window_view_heartbeat_interval](/operations/settings/settings#window_view_heartbeat_interval) | `15` | +| [wait_for_window_view_fire_signal_timeout](/operations/settings/settings#wait_for_window_view_fire_signal_timeout) | `10` | +| [stop_refreshable_materialized_views_on_startup](/operations/settings/settings#stop_refreshable_materialized_views_on_startup) | `0` | +| [allow_experimental_database_materialized_postgresql](/operations/settings/settings#allow_experimental_database_materialized_postgresql) | `0` | +| [allow_experimental_qbit_type](/operations/settings/settings#allow_experimental_qbit_type) | `0` | +| [allow_experimental_query_deduplication](/operations/settings/settings#allow_experimental_query_deduplication) | `0` | +| [allow_experimental_database_hms_catalog](/operations/settings/settings#allow_experimental_database_hms_catalog) | `0` | +| [allow_experimental_kusto_dialect](/operations/settings/settings#allow_experimental_kusto_dialect) | `0` | +| [allow_experimental_prql_dialect](/operations/settings/settings#allow_experimental_prql_dialect) | `0` | +| [enable_adaptive_memory_spill_scheduler](/operations/settings/settings#enable_adaptive_memory_spill_scheduler) | `0` | +| [allow_experimental_insert_into_iceberg](/operations/settings/settings#allow_experimental_insert_into_iceberg) | `0` | +| [allow_experimental_iceberg_compaction](/operations/settings/settings#allow_experimental_iceberg_compaction) | `0` | +| [write_full_path_in_iceberg_metadata](/operations/settings/settings#write_full_path_in_iceberg_metadata) | `0` | +| [iceberg_metadata_compression_method](/operations/settings/settings#iceberg_metadata_compression_method) | `` | +| [make_distributed_plan](/operations/settings/settings#make_distributed_plan) | `0` | +| [distributed_plan_execute_locally](/operations/settings/settings#distributed_plan_execute_locally) | `0` | +| [distributed_plan_default_shuffle_join_bucket_count](/operations/settings/settings#distributed_plan_default_shuffle_join_bucket_count) | `8` | +| [distributed_plan_default_reader_bucket_count](/operations/settings/settings#distributed_plan_default_reader_bucket_count) | `8` | +| [distributed_plan_force_exchange_kind](/operations/settings/settings#distributed_plan_force_exchange_kind) | `` | +| [distributed_plan_max_rows_to_broadcast](/operations/settings/settings#distributed_plan_max_rows_to_broadcast) | `20000` | +| [allow_experimental_ytsaurus_table_engine](/operations/settings/settings#allow_experimental_ytsaurus_table_engine) | `0` | +| [allow_experimental_ytsaurus_table_function](/operations/settings/settings#allow_experimental_ytsaurus_table_function) | `0` | +| [allow_experimental_ytsaurus_dictionary_source](/operations/settings/settings#allow_experimental_ytsaurus_dictionary_source) | `0` | +| [distributed_plan_force_shuffle_aggregation](/operations/settings/settings#distributed_plan_force_shuffle_aggregation) | `0` | +| [enable_join_runtime_filters](/operations/settings/settings#enable_join_runtime_filters) | `0` | +| [join_runtime_filter_exact_values_limit](/operations/settings/settings#join_runtime_filter_exact_values_limit) | `10000` | +| [join_runtime_bloom_filter_bytes](/operations/settings/settings#join_runtime_bloom_filter_bytes) | `524288` | +| [join_runtime_bloom_filter_hash_functions](/operations/settings/settings#join_runtime_bloom_filter_hash_functions) | `3` | +| [rewrite_in_to_join](/operations/settings/settings#rewrite_in_to_join) | `0` | +| [allow_experimental_time_series_aggregate_functions](/operations/settings/settings#allow_experimental_time_series_aggregate_functions) | `0` | +| [promql_database](/operations/settings/settings#promql_database) | `` | +| [promql_table](/operations/settings/settings#promql_table) | `` | +| [promql_evaluation_time](/operations/settings/settings#promql_evaluation_time) | `auto` | +| [allow_experimental_alias_table_engine](/operations/settings/settings#allow_experimental_alias_table_engine) | `0` | +| [use_paimon_partition_pruning](/operations/settings/settings#use_paimon_partition_pruning) | `0` | +| [allow_experimental_replacing_merge_with_cleanup](/operations/settings/merge-tree-settings#allow_experimental_replacing_merge_with_cleanup) | `0` | +| [allow_experimental_reverse_key](/operations/settings/merge-tree-settings#allow_experimental_reverse_key) | `0` | +| [allow_remote_fs_zero_copy_replication](/operations/settings/merge-tree-settings#allow_remote_fs_zero_copy_replication) | `0` | +| [enable_replacing_merge_with_cleanup_for_min_age_to_force_merge](/operations/settings/merge-tree-settings#enable_replacing_merge_with_cleanup_for_min_age_to_force_merge) | `0` | +| [force_read_through_cache_for_merges](/operations/settings/merge-tree-settings#force_read_through_cache_for_merges) | `0` | +| [merge_selector_algorithm](/operations/settings/merge-tree-settings#merge_selector_algorithm) | `Simple` | +| [merge_selector_enable_heuristic_to_lower_max_parts_to_merge_at_once](/operations/settings/merge-tree-settings#merge_selector_enable_heuristic_to_lower_max_parts_to_merge_at_once) | `0` | +| [notify_newest_block_number](/operations/settings/merge-tree-settings#notify_newest_block_number) | `0` | +| [part_moves_between_shards_delay_seconds](/operations/settings/merge-tree-settings#part_moves_between_shards_delay_seconds) | `30` | +| [part_moves_between_shards_enable](/operations/settings/merge-tree-settings#part_moves_between_shards_enable) | `0` | +| [remote_fs_zero_copy_path_compatible_mode](/operations/settings/merge-tree-settings#remote_fs_zero_copy_path_compatible_mode) | `0` | +| [remote_fs_zero_copy_zookeeper_path](/operations/settings/merge-tree-settings#remote_fs_zero_copy_zookeeper_path) | `/clickhouse/zero_copy` | +| [remove_rolled_back_parts_immediately](/operations/settings/merge-tree-settings#remove_rolled_back_parts_immediately) | `1` | +| [shared_merge_tree_virtual_parts_discovery_batch](/operations/settings/merge-tree-settings#shared_merge_tree_virtual_parts_discovery_batch) | `1` | {/*AUTOGENERATED_END*/ } diff --git a/i18n/ru/docusaurus-plugin-content-docs/current/about-us/history.md b/i18n/ru/docusaurus-plugin-content-docs/current/about-us/history.md index 40e641df644..6e5cb5354d9 100644 --- a/i18n/ru/docusaurus-plugin-content-docs/current/about-us/history.md +++ b/i18n/ru/docusaurus-plugin-content-docs/current/about-us/history.md @@ -8,8 +8,6 @@ title: 'История ClickHouse' doc_type: 'reference' --- - - # История ClickHouse {#clickhouse-history} ClickHouse изначально разрабатывался для работы в составе [Yandex.Metrica](https://metrica.yandex.com/), [второй по размеру платформы веб-аналитики в мире](http://w3techs.com/technologies/overview/traffic_analysis/all), и по-прежнему является её ключевым компонентом. Имея более 13 триллионов записей в базе данных и более 20 миллиардов событий ежедневно, ClickHouse позволяет на лету формировать произвольные отчёты непосредственно по неагрегированным данным. В этой статье кратко рассматриваются цели ClickHouse на ранних этапах его разработки. @@ -18,8 +16,6 @@ Yandex.Metrica динамически формирует настраиваем По состоянию на апрель 2014 года Yandex.Metrica регистрировала около 12 миллиардов событий (просмотров страниц и кликов) в день. Все эти события необходимо было хранить, чтобы формировать настраиваемые отчёты. Один запрос мог требовать сканирования миллионов строк за несколько сотен миллисекунд или сотен миллионов строк всего за несколько секунд. - - ## Использование в Yandex.Metrica и других сервисах Yandex {#usage-in-yandex-metrica-and-other-yandex-services} ClickHouse используется в Yandex.Metrica для решения нескольких задач. @@ -35,8 +31,6 @@ ClickHouse также играет ключевую роль в следующи В настоящее время в других сервисах и подразделениях Yandex — поисковых вертикалях, e-commerce, рекламе, бизнес-аналитике, мобильной разработке, персональных сервисах и других — развернуто несколько десятков установок ClickHouse. - - ## Агрегированные и неагрегированные данные {#aggregated-and-non-aggregated-data} Существует широко распространённое мнение, что для эффективного расчёта статистики необходимо агрегировать данные, так как это уменьшает объём данных. @@ -60,4 +54,4 @@ ClickHouse также играет ключевую роль в следующи Начиная с 2009 года, Yandex.Metrica также использовала специализированную OLAP-базу данных для неагрегированных данных под названием OLAPServer, которая ранее применялась для конструктора отчётов. OLAPServer хорошо работал с неагрегированными данными, но имел множество ограничений, не позволявших использовать его для всех отчётов, как того хотелось бы. Среди них — отсутствие поддержки типов данных (только числа) и невозможность инкрементально обновлять данные в режиме реального времени (это можно было делать только путём ежедневной перезаписи данных). OLAPServer — это не СУБД, а специализированная БД. -Изначальной целью создания ClickHouse было снять ограничения OLAPServer и решить задачу работы с неагрегированными данными для всех отчётов, но за прошедшие годы он вырос в универсальную систему управления базами данных, подходящую для широкого круга аналитических задач. +Изначальной целью создания ClickHouse было снять ограничения OLAPServer и решить задачу работы с неагрегированными данными для всех отчётов, но за прошедшие годы он вырос в универсальную систему управления базами данных, подходящую для широкого круга аналитических задач. \ No newline at end of file diff --git a/i18n/ru/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/azure-queue.md b/i18n/ru/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/azure-queue.md index 765b39acf7d..bc4a4455fe3 100644 --- a/i18n/ru/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/azure-queue.md +++ b/i18n/ru/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/azure-queue.md @@ -42,14 +42,15 @@ ENGINE = AzureQueue('DefaultEndpointsProtocol=http;AccountName=devstoreaccount1; SETTINGS mode = 'unordered' ``` + ## Settings {#settings} -Набор поддерживаемых настроек в основном совпадает с настройками для движка таблиц `S3Queue`, но без префикса `s3queue_`. См. [полный список настроек](../../../engines/table-engines/integrations/s3queue.md#settings). +Набор поддерживаемых настроек в основном совпадает с настройками для движка таблицы `S3Queue`, но без префикса `s3queue_`. См. [полный список настроек](../../../engines/table-engines/integrations/s3queue.md#settings). Чтобы получить список настроек, заданных для таблицы, используйте таблицу `system.azure_queue_settings`. Доступно начиная с версии 24.10. -Ниже приведены настройки, совместимые только с AzureQueue и не применимые к S3Queue. +Ниже приведены настройки, совместимые только с AzureQueue и неприменимые к S3Queue. -### `after_processing_move_connection_string` {#after_processing_move_connection_string} +### `after_processing_move_connection_string` {#after_processing_move_connection_string} Строка подключения к Azure Blob Storage, в которую будут перемещаться успешно обработанные файлы, если в качестве назначения используется другой контейнер Azure. @@ -59,7 +60,7 @@ SETTINGS mode = 'unordered' Значение по умолчанию: пустая строка. -### `after_processing_move_container` {#after_processing_move_container} +### `after_processing_move_container` {#after_processing_move_container} Имя контейнера, в который необходимо переместить успешно обработанные файлы, если целевым контейнером является другой контейнер Azure. @@ -85,6 +86,13 @@ SETTINGS after_processing_move_container = 'dst-container'; ``` + +## SELECT из движка таблицы AzureQueue {#select} + +Запросы SELECT по умолчанию запрещены для таблиц AzureQueue. Это соответствует общей модели работы очередей, в которой данные читаются один раз, а затем удаляются из очереди. SELECT запрещён, чтобы предотвратить случайную потерю данных. +Однако иногда это может быть полезно. Для этого необходимо установить настройку `stream_like_engine_allow_direct_select` в значение `True`. +Движок AzureQueue имеет специальную настройку для запросов SELECT: `commit_on_select`. Установите её в `False`, чтобы сохранить данные в очереди после чтения, или в `True`, чтобы удалить их. + ## Описание {#description} `SELECT` не особенно полезен для потокового импорта (кроме отладки), потому что каждый файл можно импортировать только один раз. Гораздо практичнее создавать потоки в реальном времени с использованием [материализованных представлений](../../../sql-reference/statements/create/view.md). Для этого: @@ -112,6 +120,7 @@ CREATE MATERIALIZED VIEW consumer TO stats SELECT * FROM stats ORDER BY key; ``` + ## Виртуальные столбцы {#virtual-columns} * `_path` — Путь к файлу. @@ -143,24 +152,24 @@ SELECT * FROM stats ORDER BY key; CREATE TABLE system.azure_queue_log ( - `hostname` LowCardinality(String) COMMENT 'Имя хоста', - `event_date` Date COMMENT 'Дата события записи данной строки журнала', - `event_time` DateTime COMMENT 'Время события записи данной строки журнала', - `database` String COMMENT 'Имя базы данных, в которой находится таблица S3Queue.', - `table` String COMMENT 'Имя таблицы S3Queue.', - `uuid` String COMMENT 'UUID таблицы S3Queue', - `file_name` String COMMENT 'Имя обрабатываемого файла', - `rows_processed` UInt64 COMMENT 'Количество обработанных строк', - `status` Enum8('Processed' = 0, 'Failed' = 1) COMMENT 'Статус обработки файла', - `processing_start_time` Nullable(DateTime) COMMENT 'Время начала обработки файла', - `processing_end_time` Nullable(DateTime) COMMENT 'Время завершения обработки файла', - `exception` String COMMENT 'Сообщение об исключении при его возникновении' + `hostname` LowCardinality(String) COMMENT 'Hostname', + `event_date` Date COMMENT 'Event date of writing this log row', + `event_time` DateTime COMMENT 'Event time of writing this log row', + `database` String COMMENT 'The name of a database where current S3Queue table lives.', + `table` String COMMENT 'The name of S3Queue table.', + `uuid` String COMMENT 'The UUID of S3Queue table', + `file_name` String COMMENT 'File name of the processing file', + `rows_processed` UInt64 COMMENT 'Number of processed rows', + `status` Enum8('Processed' = 0, 'Failed' = 1) COMMENT 'Status of the processing file', + `processing_start_time` Nullable(DateTime) COMMENT 'Time of the start of processing the file', + `processing_end_time` Nullable(DateTime) COMMENT 'Time of the end of processing the file', + `exception` String COMMENT 'Exception message if happened' ) ENGINE = MergeTree PARTITION BY toYYYYMM(event_date) ORDER BY (event_date, event_time) SETTINGS index_granularity = 8192 -COMMENT 'Содержит записи журнала с информацией о файлах, обработанных движком S3Queue.' +COMMENT 'Contains logging entries with the information files processes by S3Queue engine.' ``` @@ -172,7 +181,7 @@ FROM system.azure_queue_log LIMIT 1 FORMAT Vertical -Строка 1: +Row 1: ────── hostname: clickhouse event_date: 2024-12-16 @@ -187,6 +196,6 @@ processing_start_time: 2024-12-16 13:42:47 processing_end_time: 2024-12-16 13:42:47 exception: -Получена 1 строка. Затрачено: 0.002 сек. +1 row in set. Elapsed: 0.002 sec. ``` diff --git a/i18n/ru/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/s3queue.md b/i18n/ru/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/s3queue.md index b8090eb3032..bf52209f72e 100644 --- a/i18n/ru/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/s3queue.md +++ b/i18n/ru/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/s3queue.md @@ -64,7 +64,7 @@ SETTINGS mode = 'unordered'; ``` -Использование коллекций с именами: +Использование именованных коллекций: ```xml @@ -85,9 +85,10 @@ SETTINGS mode = 'ordered'; ``` + ## Настройки {#settings} -Чтобы получить список настроек, заданных для таблицы, используйте таблицу `system.s3_queue_settings`. Доступно, начиная с версии `24.10`. +Чтобы получить список настроек таблицы, используйте таблицу `system.s3_queue_settings`. Доступно начиная с версии `24.10`. ### Mode {#mode} @@ -98,7 +99,7 @@ SETTINGS Значение по умолчанию: `ordered` в версиях до 24.6. Начиная с 24.6 значение по умолчанию отсутствует, настройку требуется указывать вручную. Для таблиц, созданных в более ранних версиях, значение по умолчанию останется `ordered` для сохранения совместимости. -### `after_processing` {#after_processing} +### `after_processing` {#after_processing} Что делать с файлом после успешной обработки. @@ -134,7 +135,8 @@ SETTINGS Для добавления тегов необходимо указать ключ и значение тега в параметрах `after_processing_tag_key` и `after_processing_tag_value`. -### `after_processing_retries` {#after_processing_retries} + +### `after_processing_retries` {#after_processing_retries} Количество повторных попыток выполнения запрошенного действия постобработки перед тем, как прекратить попытки. @@ -144,7 +146,7 @@ SETTINGS Значение по умолчанию: `10`. -### `after_processing_move_access_key_id` {#after_processing_move_access_key_id} +### `after_processing_move_access_key_id` {#after_processing_move_access_key_id} ID ключа доступа (Access Key ID) для S3‑бакета, в который нужно переместить успешно обработанные файлы, если целевым местом назначения является другой S3‑бакет. @@ -154,9 +156,9 @@ ID ключа доступа (Access Key ID) для S3‑бакета, в кот Значение по умолчанию: пустая строка. -### `after_processing_move_prefix` {#after_processing_move_prefix} +### `after_processing_move_prefix` {#after_processing_move_prefix} -Префикс пути, в который перемещаются успешно обработанные файлы. Применимо как при перемещении в пределах того же бакета, так и в другой бакет. +Префикс пути, в который перемещаются успешно обработанные файлы. Применимо как при перемещении в пределах того же бакета, так и при перемещении в другой бакет. Возможные значения: @@ -164,7 +166,7 @@ ID ключа доступа (Access Key ID) для S3‑бакета, в кот Значение по умолчанию: пустая строка. -### `after_processing_move_secret_access_key` {#after_processing_move_secret_access_key} +### `after_processing_move_secret_access_key` {#after_processing_move_secret_access_key} Secret Access Key для S3‑бакета, в который нужно перемещать успешно обработанные файлы, если целевой ресурс — другой S3‑бакет. @@ -174,7 +176,7 @@ Secret Access Key для S3‑бакета, в который нужно пер Значение по умолчанию: пустая строка. -### `after_processing_move_uri` {#after_processing_move_uri} +### `after_processing_move_uri` {#after_processing_move_uri} URI S3-бакета, в который следует перемещать успешно обработанные файлы, если местом назначения является другой S3-бакет. @@ -184,7 +186,7 @@ URI S3-бакета, в который следует перемещать ус Значение по умолчанию: пустая строка. -### `after_processing_tag_key` {#after_processing_tag_key} +### `after_processing_tag_key` {#after_processing_tag_key} Ключ тега, который будет использоваться для пометки успешно обработанных файлов, если `after_processing='tag'`. @@ -194,7 +196,7 @@ URI S3-бакета, в который следует перемещать ус Значение по умолчанию: пустая строка. -### `after_processing_tag_value` {#after_processing_tag_value} +### `after_processing_tag_value` {#after_processing_tag_value} Значение тега, которое будет присвоено успешно обработанным файлам, если `after_processing='tag'`. @@ -213,7 +215,7 @@ URI S3-бакета, в который следует перемещать ус Значение по умолчанию: `/`. -### `s3queue_loading_retries` {#loading_retries} +### `s3queue_loading_retries` {#loading_retries} Повторять загрузку файла до указанного количества раз. По умолчанию повторы не выполняются. Возможные значения: @@ -222,13 +224,13 @@ URI S3-бакета, в который следует перемещать ус Значение по умолчанию: `0`. -### `s3queue_processing_threads_num` {#processing_threads_num} +### `s3queue_processing_threads_num` {#processing_threads_num} Количество потоков обработки. Применяется только в режиме `Unordered`. -Значение по умолчанию: количество CPU или 16. +Значение по умолчанию: число CPU или 16. -### `s3queue_parallel_inserts` {#parallel_inserts} +### `s3queue_parallel_inserts` {#parallel_inserts} По умолчанию `processing_threads_num` будет выполнять один `INSERT`, поэтому файлы будут только загружаться и парситься в несколько потоков. Но это ограничивает степень параллелизма, поэтому для лучшей пропускной способности используйте `parallel_inserts=true` — это позволит вставлять данные параллельно (но имейте в виду, что это приведёт к большему количеству создаваемых частей данных для семейства движков MergeTree). @@ -239,13 +241,13 @@ URI S3-бакета, в который следует перемещать ус Значение по умолчанию: `false`. -### `s3queue_enable_logging_to_s3queue_log` {#enable_logging_to_s3queue_log} +### `s3queue_enable_logging_to_s3queue_log` {#enable_logging_to_s3queue_log} Включает логирование в `system.s3queue_log`. Значение по умолчанию: `0`. -### `s3queue_polling_min_timeout_ms` {#polling_min_timeout_ms} +### `s3queue_polling_min_timeout_ms` {#polling_min_timeout_ms} Указывает минимальное время в миллисекундах, которое ClickHouse ожидает перед следующей попыткой опроса. @@ -255,7 +257,7 @@ URI S3-бакета, в который следует перемещать ус Значение по умолчанию: `1000`. -### `s3queue_polling_max_timeout_ms` {#polling_max_timeout_ms} +### `s3queue_polling_max_timeout_ms` {#polling_max_timeout_ms} Определяет максимальное время в миллисекундах, в течение которого ClickHouse ждёт перед запуском следующей попытки опроса. @@ -275,7 +277,7 @@ URI S3-бакета, в который следует перемещать ус Значение по умолчанию: `0`. -### `s3queue_tracked_files_limit` {#tracked_files_limit} +### `s3queue_tracked_files_limit` {#tracked_files_limit} Позволяет ограничить количество узлов ZooKeeper при использовании режима `unordered`; не влияет на режим `ordered`. Если лимит достигнут, самые старые обработанные файлы будут удалены из узла ZooKeeper и обработаны повторно. @@ -286,10 +288,10 @@ URI S3-бакета, в который следует перемещать ус Значение по умолчанию: `1000`. -### `s3queue_tracked_file_ttl_sec` {#tracked_file_ttl_sec} +### `s3queue_tracked_file_ttl_sec` {#tracked_file_ttl_sec} Максимальное время в секундах для хранения обработанных файлов в узле ZooKeeper (по умолчанию хранятся бессрочно) в режиме `unordered`; не влияет на режим `ordered`. -По истечении указанного времени файл будет загружен повторно. +По истечении указанного времени файл будет повторно импортирован. Возможные значения: @@ -297,27 +299,27 @@ URI S3-бакета, в который следует перемещать ус Значение по умолчанию: `0`. -### `s3queue_cleanup_interval_min_ms` {#cleanup_interval_min_ms} +### `s3queue_cleanup_interval_min_ms` {#cleanup_interval_min_ms} Для режима `Ordered`. Определяет минимальное значение интервала перепланирования фоновой задачи, которая отвечает за поддержание TTL отслеживаемых файлов и ограничения на их максимальное количество. Значение по умолчанию: `10000`. -### `s3queue_cleanup_interval_max_ms` {#cleanup_interval_max_ms} +### `s3queue_cleanup_interval_max_ms` {#cleanup_interval_max_ms} -Для режима `Ordered`. Определяет максимальный интервал между переназначениями фоновой задачи, которая отвечает за поддержание TTL отслеживаемых файлов и максимального набора отслеживаемых файлов. +Для режима `Ordered`. Определяет верхнюю границу интервала перепланирования фоновой задачи, которая отвечает за поддержание TTL отслеживаемых файлов и максимального числа отслеживаемых файлов. Значение по умолчанию: `30000`. ### `s3queue_buckets` {#buckets} -Для режима `Ordered`. Доступно начиная с версии `24.6`. Если существует несколько реплик таблицы `S3Queue`, каждая из которых работает с одним и тем же каталогом метаданных в keeper, значение `s3queue_buckets` должно быть не меньше количества реплик. Если также используется настройка `s3queue_processing_threads`, имеет смысл дополнительно увеличить значение `s3queue_buckets`, так как она определяет фактический уровень параллелизма обработки `S3Queue`. +Для режима `Ordered`. Доступно начиная с версии `24.6`. Если существует несколько реплик таблицы `S3Queue`, каждая из которых работает с одним и тем же каталогом метаданных в keeper, значение `s3queue_buckets` должно быть не меньше количества реплик. Если также используется настройка `s3queue_processing_threads`, имеет смысл дополнительно увеличить значение `s3queue_buckets`, так как она определяет фактический уровень параллелизма обработки в `S3Queue`. -### `use_persistent_processing_nodes` {#use_persistent_processing_nodes} +### `use_persistent_processing_nodes` {#use_persistent_processing_nodes} -По умолчанию таблица S3Queue всегда использовала эфемерные узлы обработки, что могло приводить к дублированию данных в случае, если сессия ZooKeeper истекает до того, как S3Queue зафиксирует обработанные файлы в ZooKeeper, но после того, как обработка уже началась. Эта настройка заставляет сервер исключить возможность появления дубликатов при истечении сессии Keeper. +По умолчанию таблица S3Queue всегда использовала эфемерные узлы обработки, что могло приводить к дублированию данных в случае, если сессия ZooKeeper истекает до того, как S3Queue зафиксирует обработанные файлы в ZooKeeper, но после того, как обработка уже началась. Эта настройка гарантирует исключение возможности появления дубликатов при истечении сессии Keeper. -### `persistent_processing_nodes_ttl_seconds` {#persistent_processing_nodes_ttl_seconds} +### `persistent_processing_nodes_ttl_seconds` {#persistent_processing_nodes_ttl_seconds} В случае некорректного завершения работы сервера, если включён `use_persistent_processing_nodes`, могут остаться неудалённые узлы обработки. Этот параметр определяет период времени, по истечении которого эти узлы обработки могут быть безопасно удалены. @@ -350,6 +352,7 @@ SETTINGS ... ``` + ## Упорядоченный режим (ordered) для S3Queue {#ordered-mode} Режим обработки `S3Queue` позволяет хранить меньше метаданных в ZooKeeper, но имеет ограничение: файлы, добавленные позже по времени, должны иметь имена, которые в алфавитно-цифровом порядке больше имён ранее добавленных файлов. @@ -359,13 +362,19 @@ SETTINGS Использование настройки `(s3queue_)processing_threads_num` не рекомендуется до версии `24.6`. Настройка `(s3queue_)buckets` доступна начиная с версии `24.6`. +## SELECT из движка таблиц S3Queue {#select} + +Запросы SELECT по умолчанию запрещены для таблиц S3Queue. Это соответствует общему шаблону работы очереди, когда данные читаются один раз, а затем удаляются из очереди. SELECT запрещён, чтобы предотвратить случайную потерю данных. +Однако иногда это может быть полезно. Для этого необходимо установить настройку `stream_like_engine_allow_direct_select` в `True`. +Движок S3Queue имеет специальную настройку для запросов SELECT: `commit_on_select`. Установите её в `False`, чтобы сохранять данные в очереди после чтения, или в `True`, чтобы удалять их. + ## Описание {#description} -`SELECT` мало полезен для потокового импорта (кроме отладки), потому что каждый файл можно импортировать только один раз. Более практично создавать потоки в реальном времени с помощью [материализованных представлений](../../../sql-reference/statements/create/view.md). Для этого: +`SELECT` мало полезен для потокового импорта (кроме отладки), потому что каждый файл можно импортировать только один раз. Более практично создавать потоки в реальном времени с помощью [materialized views](../../../sql-reference/statements/create/view.md). Для этого: -1. Используйте этот движок для создания таблицы, которая будет читать данные из указанного пути в S3 и рассматриваться как поток данных. +1. Используйте этот движок для создания таблицы, которая будет читать данные из указанного пути в S3 и рассматривать её как поток данных. 2. Создайте таблицу с требуемой структурой. -3. Создайте материализованное представление, которое преобразует данные из этого движка и помещает их в ранее созданную таблицу. +3. Создайте materialized view, которое преобразует данные из этого движка и помещает их в ранее созданную таблицу. Когда `MATERIALIZED VIEW` подключено к этому движку, оно начинает собирать данные в фоновом режиме. @@ -386,6 +395,7 @@ SETTINGS SELECT * FROM stats ORDER BY name; ``` + ## Виртуальные столбцы {#virtual-columns} * `_path` — Путь к файлу. @@ -440,7 +450,7 @@ SETTINGS `exception` String ) ENGINE = SystemS3Queue -COMMENT 'Содержит состояние метаданных S3Queue в памяти и текущее количество обработанных строк по каждому файлу.' │ +COMMENT 'Contains in-memory state of S3Queue metadata and currently processed rows per file.' │ └────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘ ``` @@ -451,12 +461,12 @@ COMMENT 'Содержит состояние метаданных S3Queue в п SELECT * FROM system.s3queue -Строка 1: +Row 1: ────── zookeeper_path: /clickhouse/s3queue/25ea5621-ae8c-40c7-96d0-cec959c5ab88/3b3f66a1-9866-4c2e-ba78-b6bfa154207e file_name: wikistat/original/pageviews-20150501-030000.gz rows_processed: 5068534 -status: Обработано +status: Processed processing_start_time: 2023-10-13 13:09:48 processing_end_time: 2023-10-13 13:10:31 ProfileEvents: {'ZooKeeperTransactions':3,'ZooKeeperGet':2,'ZooKeeperMulti':1,'SelectedRows':5068534,'SelectedBytes':198132283,'ContextLock':1,'S3QueueSetFileProcessingMicroseconds':2480,'S3QueueSetFileProcessedMicroseconds':9985,'S3QueuePullMicroseconds':273776,'LogTest':17} @@ -470,7 +480,7 @@ exception: ```sql SHOW CREATE TABLE system.s3queue_log -ID запроса: 0ad619c3-0f2a-4ee4-8b40-c73d86e04314 +Query id: 0ad619c3-0f2a-4ee4-8b40-c73d86e04314 ┌─statement──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐ │ CREATE TABLE system.s3queue_log @@ -493,7 +503,7 @@ SETTINGS index_granularity = 8192 │ └────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘ ``` -Чтобы использовать `system.s3queue_log`, задайте его конфигурацию в файле конфигурации сервера: +Чтобы использовать `system.s3queue_log`, укажите его конфигурацию в конфигурационном файле сервера: ```xml diff --git a/i18n/ru/docusaurus-plugin-content-docs/current/interfaces/formats.md b/i18n/ru/docusaurus-plugin-content-docs/current/interfaces/formats.md index 3a210c21ffb..22b58d7b60e 100644 --- a/i18n/ru/docusaurus-plugin-content-docs/current/interfaces/formats.md +++ b/i18n/ru/docusaurus-plugin-content-docs/current/interfaces/formats.md @@ -9,13 +9,10 @@ doc_type: 'reference' import CloudNotSupportedBadge from '@theme/badges/CloudNotSupportedBadge'; - # Форматы входных и выходных данных {#formats-for-input-and-output-data} ClickHouse поддерживает большинство известных текстовых и бинарных форматов данных. Это обеспечивает простую интеграцию практически в любой существующий конвейер данных и позволяет в полной мере использовать преимущества ClickHouse. - - ## Форматы ввода {#input-formats} Форматы ввода используются для: @@ -33,22 +30,16 @@ ClickHouse поддерживает большинство известных т Для детального разбора результатов и рекомендаций по лучшим практикам ознакомьтесь с полной [аналитикой бенчмарка](https://www.clickhouse.com/blog/clickhouse-input-format-matchup-which-is-fastest-most-efficient). Все результаты тестов доступны в онлайн-дашборде [FastFormats](https://fastformats.clickhouse.com/). - - ## Форматы вывода {#output-formats} Поддерживаемые форматы вывода используются для: - Представления результатов запроса `SELECT` - Выполнения операций `INSERT` в таблицы с файловой поддержкой - - ## Обзор форматов {#formats-overview} Поддерживаемые форматы: - - | Формат | Ввод | Вывод | | ---------------------------------------------------------------------------------------------------------- | ---- | ----- | | [TabSeparated](./formats/TabSeparated/TabSeparated.md) | ✔ | ✔ | @@ -138,12 +129,8 @@ ClickHouse поддерживает большинство известных т | [Markdown](./formats/Markdown.md) | ✗ | ✔ | | [Форма](./formats/Form.md) | ✔ | ✗ | - - Вы можете управлять некоторыми параметрами обработки форматов с помощью настроек ClickHouse. Подробнее см. раздел [Настройки](/operations/settings/settings-formats.md). - - ## Схема формата {#formatschema} Имя файла, содержащего схему формата, задаётся настройкой `format_schema`. @@ -161,8 +148,6 @@ ClickHouse поддерживает большинство известных т должно находиться в каталоге, указанном в [format_schema_path](/operations/server-configuration-parameters/settings.md/#format_schema_path) в конфигурации сервера. - - ## Пропуск ошибок {#skippingerrors} Некоторые форматы, такие как `CSV`, `TabSeparated`, `TSKV`, `JSONEachRow`, `Template`, `CustomSeparated` и `Protobuf`, могут пропускать некорректную строку при возникновении ошибки парсинга и продолжать разбор начиная со следующей строки. См. настройки [input_format_allow_errors_num](/operations/settings/settings-formats.md/#input_format_allow_errors_num) и diff --git a/i18n/ru/docusaurus-plugin-content-docs/current/operations/settings/merge-tree-settings.md b/i18n/ru/docusaurus-plugin-content-docs/current/operations/settings/merge-tree-settings.md index 4403c322b29..e1ccae1f0b4 100644 --- a/i18n/ru/docusaurus-plugin-content-docs/current/operations/settings/merge-tree-settings.md +++ b/i18n/ru/docusaurus-plugin-content-docs/current/operations/settings/merge-tree-settings.md @@ -544,7 +544,7 @@ SELECT * FROM example WHERE key = 'xxx' ORDER BY time DESC LIMIT 10; - + Определяет, должны ли настройки `min_age_to_force_merge_seconds` и `min_age_to_force_merge_on_partition_only` учитывать настройку @@ -1364,6 +1364,18 @@ min_delay_to_insert_ms = 10, `INSERT` задерживается Определяет, когда срабатывает логика по отношению к количеству частей в партиции. Чем больше коэффициент, тем позже будет реакция. +## merge_selector_enable_heuristic_to_lower_max_parts_to_merge_at_once {#merge_selector_enable_heuristic_to_lower_max_parts_to_merge_at_once} + + + + + + + +Включает эвристику для простого селектора слияний, которая будет снижать максимальное ограничение при выборе слияний. +Таким образом, число одновременных слияний увеличится, что может помочь с ошибками TOO_MANY_PARTS, +но при этом увеличится write amplification. + ## merge_selector_enable_heuristic_to_remove_small_parts_at_right {#merge_selector_enable_heuristic_to_remove_small_parts_at_right} diff --git a/i18n/ru/docusaurus-plugin-content-docs/current/operations/settings/settings.md b/i18n/ru/docusaurus-plugin-content-docs/current/operations/settings/settings.md index fd927627c92..a1bce4e9be4 100644 --- a/i18n/ru/docusaurus-plugin-content-docs/current/operations/settings/settings.md +++ b/i18n/ru/docusaurus-plugin-content-docs/current/operations/settings/settings.md @@ -10123,6 +10123,15 @@ FORMAT Null; Минимальный размер части при многочастичной загрузке в S3. +## s3_path_filter_limit {#s3_path_filter_limit} + + + + + +Максимальное количество значений `_path`, которое может быть извлечено из фильтров запроса и использовано для итерации по файлам +вместо перечисления файлов по glob-шаблону. Значение 0 означает, что настройка отключена. + ## s3_request_timeout_ms {#s3_request_timeout_ms} @@ -10687,7 +10696,8 @@ SELECT ((4 + 2) + 1, ((4 + 2) + 1) + 2) -Разрешает выполнение прямого запроса SELECT для движков Kafka, RabbitMQ, FileLog, Redis Streams и NATS. При наличии подключённых materialized views выполнение запроса SELECT запрещено, даже если этот параметр включён. +Разрешает выполнение прямого запроса SELECT для движков Kafka, RabbitMQ, FileLog, Redis Streams, S3Queue, AzureQueue и NATS. При наличии подключённых materialized views выполнение запроса SELECT запрещено, даже если этот параметр включён. +Если нет подключённых materialized views, включение этого параметра позволяет читать данные. Имейте в виду, что обычно прочитанные данные удаляются из очереди. Чтобы избежать удаления прочитанных данных, соответствующие настройки движка должны быть настроены должным образом. ## stream_like_engine_insert_queue {#stream_like_engine_insert_queue} diff --git a/i18n/ru/docusaurus-plugin-content-docs/current/operations/system-tables/index.md b/i18n/ru/docusaurus-plugin-content-docs/current/operations/system-tables/index.md index 22cb53d8490..e31d3b8ab43 100644 --- a/i18n/ru/docusaurus-plugin-content-docs/current/operations/system-tables/index.md +++ b/i18n/ru/docusaurus-plugin-content-docs/current/operations/system-tables/index.md @@ -24,23 +24,23 @@ doc_type: 'reference' | [Обзор системных таблиц](/operations/system-tables/overview) | Обзор системных таблиц и причин, по которым они полезны. | | [INFORMATION_SCHEMA](/operations/system-tables/information_schema) | Системная база данных, предоставляющая практически стандартизированное, не зависящее от конкретной СУБД представление метаданных объектов базы данных. | | [system.asynchronous_insert_log](/operations/system-tables/asynchronous_insert_log) | Системная таблица, содержащая информацию об асинхронных вставках. Каждая запись соответствует запросу вставки, помещённому в буфер асинхронных вставок. | -| [system.asynchronous_inserts](/operations/system-tables/asynchronous_inserts) | Системная таблица, содержащая информацию об асинхронных вставках в очереди, ожидающих выполнения. | -| [system.asynchronous_loader](/operations/system-tables/asynchronous_loader) | Системная таблица, содержащая информацию о последних асинхронных заданиях (например, для загружаемых таблиц) и их статусе. Таблица содержит строку для каждого задания. | -| [system.asynchronous_metric_log](/operations/system-tables/asynchronous_metric_log) | Системная таблица, содержащая исторические значения из `system.asynchronous_metrics`, которые сохраняются раз в заданный интервал времени (по умолчанию — каждую секунду) | -| [system.asynchronous_metrics](/operations/system-tables/asynchronous_metrics) | Системная таблица, содержащая метрики, периодически вычисляемые в фоновом режиме. Например, объём используемой оперативной памяти. | +| [system.asynchronous_inserts](/operations/system-tables/asynchronous_inserts) | Системная таблица, содержащая информацию об асинхронных вставках, ожидающих выполнения в очереди. | +| [system.asynchronous_loader](/operations/system-tables/asynchronous_loader) | Системная таблица, содержащая информацию о последних асинхронных заданиях (например, по загрузке таблиц) и их состоянии. В таблице содержится по одной строке для каждого задания. | +| [system.asynchronous_metric_log](/operations/system-tables/asynchronous_metric_log) | Системная таблица, содержащая исторические значения таблицы `system.asynchronous_metrics`, сохраняемые один раз за интервал времени (по умолчанию — каждую секунду) | +| [system.asynchronous_metrics](/operations/system-tables/asynchronous_metrics) | Системная таблица, содержащая метрики, которые периодически вычисляются в фоновом режиме. Например, объём используемой оперативной памяти. | | [system.azure_queue_settings](/operations/system-tables/azure_queue_settings) | Системная таблица, содержащая информацию о настройках таблиц AzureQueue. Доступна начиная с версии сервера `24.10`. | | [system.backup_log](/operations/system-tables/backup_log) | Системная таблица, содержащая записи журнала с информацией об операциях `BACKUP` и `RESTORE`. | | [system.backups](/operations/system-tables/backups) | Системная таблица, содержащая записи журнала с информацией об операциях `BACKUP` и `RESTORE`. | | [system.blob_storage_log](/operations/system-tables/blob_storage_log) | Системная таблица, содержащая записи журнала с информацией о различных операциях с blob-хранилищем, таких как загрузка и удаление объектов. | | [system.build_options](/operations/system-tables/build_options) | Системная таблица, содержащая информацию о параметрах сборки сервера ClickHouse. | | [system.clusters](/operations/system-tables/clusters) | Системная таблица, содержащая информацию о кластерах, доступных в конфигурационном файле, и серверах, описанных в них. | -| [system.codecs](/operations/system-tables/codecs) | Системная таблица, содержащая информацию о кодеках очереди. | -| [system.columns](/operations/system-tables/columns) | Системная таблица, содержащая сведения о столбцах всех таблиц | +| [system.codecs](/operations/system-tables/codecs) | Системная таблица, содержащая информацию о доступных кодеках. | +| [system.columns](/operations/system-tables/columns) | Системная таблица, содержащая сведения о столбцах во всех таблицах | | [system.contributors](/operations/system-tables/contributors) | Системная таблица, содержащая информацию об участниках. | | [system.crash_log](/operations/system-tables/crash_log) | Системная таблица, содержащая информацию о трассировках стека при фатальных ошибках. | | [system.current_roles](/operations/system-tables/current_roles) | Системная таблица, содержащая активные роли для текущего пользователя. | -| [system.dashboards](/operations/system-tables/dashboards) | Содержит запросы, используемые страницей `/dashboard`, доступной через HTTP‑интерфейс; полезно для мониторинга и диагностики неполадок. | -| [system.data_skipping_indices](/operations/system-tables/data_skipping_indices) | Системная таблица, содержащая сведения об индексах пропуска данных во всех таблицах. | +| [system.dashboards](/operations/system-tables/dashboards) | Таблица содержит запросы, используемые страницей `/dashboard`, доступной через HTTP‑интерфейс. Полезна для мониторинга и диагностики неполадок. | +| [system.data_skipping_indices](/operations/system-tables/data_skipping_indices) | Системная таблица, содержащая сведения о существующих индексах пропуска данных во всех таблицах. | | [system.data_type_families](/operations/system-tables/data_type_families) | Системная таблица, содержащая информацию о поддерживаемых типах данных | | [system.database_engines](/operations/system-tables/database_engines) | Системная таблица, содержащая список движков баз данных, поддерживаемых сервером. | | [system.database_replicas](/operations/system-tables/database_replicas) | Системная таблица, содержащая сведения о реплицируемой базе данных и её состоянии. | @@ -48,66 +48,66 @@ doc_type: 'reference' | [system.dead_letter_queue](/operations/system-tables/dead_letter_queue) | Системная таблица, содержащая информацию о сообщениях, полученных через потоковый движок и разобранных с ошибками. | | [system.delta_lake_metadata_log](/operations/system-tables/delta_lake_metadata_log) | Системная таблица, содержащая информацию о файлах метаданных, прочитанных из таблиц Delta Lake. Каждой записи соответствует корневой файл метаданных в формате JSON. | | [system.detached_parts](/operations/system-tables/detached_parts) | Системная таблица, содержащая информацию об отсоединённых частях таблиц MergeTree | -| [system.detached_tables](/operations/system-tables/detached_tables) | Системная таблица с информацией о каждой отсоединённой таблице. | +| [system.detached_tables](/operations/system-tables/detached_tables) | Системная таблица, содержащая информацию о каждой отсоединённой таблице. | | [system.dictionaries](/operations/system-tables/dictionaries) | Системная таблица, содержащая информацию о словарях | -| [system.dimensional_metrics](/operations/system-tables/dimensional_metrics) | Эта таблица содержит метрики с размерностями, которые можно мгновенно вычислить и экспортировать в формате Prometheus. Она всегда содержит актуальные данные. | +| [system.dimensional_metrics](/operations/system-tables/dimensional_metrics) | Эта таблица содержит метрики с размерностями, которые можно мгновенно вычислять и экспортировать в формате Prometheus. Данные в ней всегда актуальны. | | [system.disks](/operations/system-tables/disks) | Системная таблица, содержащая информацию о дисках, заданных в конфигурации сервера | | [system.distributed_ddl_queue](/operations/system-tables/distributed_ddl_queue) | Системная таблица, содержащая информацию о распределённых DDL-запросах (запросах с использованием предложения ON CLUSTER), которые были выполнены на кластере. | -| [system.distribution_queue](/operations/system-tables/distribution_queue) | Системная таблица, содержащая информацию о локальных файлах, поставленных в очередь на отправку в сегменты. | +| [system.distribution_queue](/operations/system-tables/distribution_queue) | Системная таблица, содержащая информацию о локальных файлах, находящихся в очереди на отправку в сегменты. | | [system.dns_cache](/operations/system-tables/dns_cache) | Системная таблица, содержащая информацию о кэшированных DNS-записях. | -| [system.dropped_tables](/operations/system-tables/dropped_tables) | Системная таблица, содержащая информацию о таблицах, для которых была выполнена команда DROP TABLE, но данные ещё не были очищены | -| [system.dropped_tables_parts](/operations/system-tables/dropped_tables_parts) | Системная таблица, содержащая информацию о частях таблиц MergeTree, удалённых и перечисленных в `system.dropped_tables` | -| [system.enabled_roles](/operations/system-tables/enabled_roles) | Системная таблица, содержащая все активные роли в данный момент, включая роль текущего пользователя и роли, назначенные текущей роли | +| [system.dropped_tables](/operations/system-tables/dropped_tables) | Системная таблица, содержащая информацию о таблицах, над которыми была выполнена команда DROP TABLE, но очистка данных ещё не произведена | +| [system.dropped_tables_parts](/operations/system-tables/dropped_tables_parts) | Системная таблица, содержащая информацию о частях таблиц семейства MergeTree для удалённых таблиц, перечисленных в `system.dropped_tables` | +| [system.enabled_roles](/operations/system-tables/enabled_roles) | Системная таблица, содержащая все активные роли на данный момент, включая текущую роль текущего пользователя и роли, назначенные этой роли | | [system.error_log](/operations/system-tables/system-error-log) | Системная таблица, содержащая историю значений ошибок из таблицы `system.errors`, периодически сбрасываемая на диск. | -| [system.errors](/operations/system-tables/errors) | Системная таблица, содержащая коды ошибок и число случаев их возникновения. | +| [system.errors](/operations/system-tables/errors) | Системная таблица, содержащая коды ошибок и количество их срабатываний. | | [system.events](/operations/system-tables/events) | Системная таблица, содержащая информацию о количестве событий, произошедших в системе. | | [system.functions](/operations/system-tables/functions) | Системная таблица, содержащая информацию об обычных и агрегатных функциях. | -| [system.grants](/operations/system-tables/grants) | Системная таблица, в которой указано, какие привилегии выданы учетным записям ClickHouse. | -| [system.graphite_retentions](/operations/system-tables/graphite_retentions) | Системная таблица, содержащая информацию о параметрах `graphite_rollup`, которые используются в таблицах с типом движка `GraphiteMergeTree`. | -| [system.histogram_metrics](/operations/system-tables/histogram_metrics) | Эта таблица содержит гистограммные метрики, которые можно мгновенно вычислять и экспортировать в формате Prometheus. Данные в ней всегда актуальны. | -| [system.iceberg_history](/operations/system-tables/iceberg_history) | История снимков системы Iceberg | +| [system.grants](/operations/system-tables/grants) | Системная таблица, показывающая, какие привилегии предоставлены учетным записям пользователей ClickHouse. | +| [system.graphite_retentions](/operations/system-tables/graphite_retentions) | Системная таблица, содержащая информацию о параметрах `graphite_rollup`, которые используются в таблицах с движком типа `GraphiteMergeTree`. | +| [system.histogram_metrics](/operations/system-tables/histogram_metrics) | Эта таблица содержит гистограммные метрики, которые можно мгновенно вычислить и экспортировать в формате Prometheus. Она всегда содержит актуальные данные. | +| [system.iceberg_history](/operations/system-tables/iceberg_history) | Системная таблица с историей снимков Iceberg | | [system.iceberg_metadata_log](/operations/system-tables/iceberg_metadata_log) | Системная таблица, содержащая информацию о файлах метаданных, прочитанных из таблиц Iceberg. Каждая запись представляет либо корневой файл метаданных, либо метаданные, извлечённые из файла Avro, либо запись файла Avro. | -| [system.instrumentation](/operations/system-tables/instrumentation) | Системная таблица с точками инструментирования | -| [system.jemalloc_bins](/operations/system-tables/jemalloc_bins) | Системная таблица, содержащая агрегированную по всем аренам информацию о выделениях памяти, выполняемых аллокатором jemalloc для различных классов размеров (bins). | +| [system.instrumentation](/operations/system-tables/instrumentation) | Системная таблица, содержащая точки инструментирования | +| [system.jemalloc_bins](/operations/system-tables/jemalloc_bins) | Системная таблица, содержащая агрегированную по всем аренам информацию о выделениях памяти, выполняемых аллокатором jemalloc для разных размерных классов (bins). | | [system.kafka_consumers](/operations/system-tables/kafka_consumers) | Системная таблица, содержащая информацию о потребителях Kafka. | -| [system.licenses](/operations/system-tables/licenses) | Системная таблица, содержащая лицензии сторонних библиотек, которые расположены в каталоге contrib в исходном коде ClickHouse. | +| [system.licenses](/operations/system-tables/licenses) | Системная таблица, содержащая лицензии сторонних библиотек, расположенных в каталоге `contrib` в исходном коде ClickHouse. | | [system.merge_tree_settings](/operations/system-tables/merge_tree_settings) | Системная таблица, содержащая информацию о настройках таблиц MergeTree. | | [system.merges](/operations/system-tables/merges) | Системная таблица, содержащая информацию о текущих слияниях и мутациях частей для таблиц семейства MergeTree. | | [system.metric_log](/operations/system-tables/metric_log) | Системная таблица, содержащая историю значений метрик из таблиц `system.metrics` и `system.events`, данные которой периодически сбрасываются на диск. | -| [system.metrics](/operations/system-tables/metrics) | Системная таблица, содержащая метрики, которые можно вычислить на лету или которые имеют текущее значение. | -| [system.moves](/operations/system-tables/moves) | Системная таблица, содержащая информацию о выполняющихся перемещениях частей данных таблиц MergeTree. Каждое перемещение части данных представлено одной строкой. | +| [system.metrics](/operations/system-tables/metrics) | Системная таблица, содержащая метрики, которые можно мгновенно вычислить или которые имеют текущее значение. | +| [system.moves](/operations/system-tables/moves) | Системная таблица, содержащая информацию о выполняющихся перемещениях частей данных таблиц MergeTree. Каждое перемещение части данных отражается одной строкой. | | [system.mutations](/operations/system-tables/mutations) | Системная таблица, содержащая информацию о мутациях таблиц MergeTree и прогрессе их выполнения. Каждая команда мутации представлена одной строкой. | | [system.numbers](/operations/system-tables/numbers) | Системная таблица, содержащая единственный столбец типа UInt64 с именем `number`, в котором хранятся почти все натуральные числа, начиная с нуля. | | [system.numbers_mt](/operations/system-tables/numbers_mt) | Системная таблица, аналогичная `system.numbers`, но чтение из неё выполняется параллельно, поэтому числа могут возвращаться в произвольном порядке. | -| [system.one](/operations/system-tables/one) | Системная таблица, содержащая одну строку с одним столбцом `dummy` типа UInt8 со значением 0. Аналогична таблице `DUAL`, используемой в других СУБД. | -| [system.opentelemetry_span_log](/operations/system-tables/opentelemetry_span_log) | Системная таблица, содержащая информацию о спанах трассировки выполненных запросов. | +| [system.one](/operations/system-tables/one) | Системная таблица, содержащая единственную строку с единственным столбцом `dummy` типа UInt8 со значением 0. Аналогична таблице `DUAL`, используемой в других СУБД. | +| [system.opentelemetry_span_log](/operations/system-tables/opentelemetry_span_log) | Системная таблица, содержащая информацию о спанах трассировки для выполненных запросов. | | [system.part_log](/operations/system-tables/part_log) | Системная таблица, содержащая информацию о событиях, произошедших с частями в таблицах семейства MergeTree, таких как добавление или слияние данных. | -| [system.parts](/operations/system-tables/parts) | Системная таблица, содержащая информацию о частях таблиц семейства MergeTree | +| [system.parts](/operations/system-tables/parts) | Системная таблица, содержащая информацию о частях таблиц MergeTree | | [system.parts_columns](/operations/system-tables/parts_columns) | Системная таблица, содержащая информацию о частях и столбцах таблиц MergeTree. | | [system.processes](/operations/system-tables/processes) | Системная таблица, предназначенная для реализации запроса `SHOW PROCESSLIST`. | -| [system.processors_profile_log](/operations/system-tables/processors_profile_log) | Системная таблица, содержащая информацию о профилировании на уровне процессоров (доступную в выводе `EXPLAIN PIPELINE`). | +| [system.processors_profile_log](/operations/system-tables/processors_profile_log) | Системная таблица, содержащая информацию профилирования на уровне процессоров (которую можно получить из вывода `EXPLAIN PIPELINE`) | | [system.projection_parts](/operations/system-tables/projection_parts) | Системная таблица, содержащая информацию о частях проекций для таблиц семейства MergeTree. | -| [system.projection_parts_columns](/operations/system-tables/projection_parts_columns) | Системная таблица, содержащая информацию о столбцах в частях проекций таблиц семейства MergeTree | -| [system.projections](/operations/system-tables/projections) | Системная таблица, содержащая информацию о имеющихся проекциях во всех таблицах. | +| [system.projection_parts_columns](/operations/system-tables/projection_parts_columns) | Системная таблица, содержащая информацию о столбцах в частях проекций для таблиц семейства MergeTree | +| [system.projections](/operations/system-tables/projections) | Системная таблица, содержащая информацию о существующих проекциях во всех таблицах. | | [system.query_cache](/operations/system-tables/query_cache) | Системная таблица, отображающая содержимое кеша запросов. | | [system.query_condition_cache](/operations/system-tables/query_condition_cache) | Системная таблица, отображающая содержимое кэша условий запросов. | | [system.query_log](/operations/system-tables/query_log) | Системная таблица, содержащая информацию о выполненных запросах, например о времени начала, длительности обработки и сообщениях об ошибках. | | [system.query_metric_log](/operations/system-tables/query_metric_log) | Системная таблица, содержащая историю значений памяти и метрик из таблицы `system.events` для отдельных запросов, данные которой периодически сбрасываются на диск. | | [system.query_thread_log](/operations/system-tables/query_thread_log) | Системная таблица, содержащая информацию о потоках, выполняющих запросы, например, имя потока, время запуска потока и продолжительность обработки запроса. | -| [system.query_views_log](/operations/system-tables/query_views_log) | Системная таблица, содержащая информацию о зависимых представлениях, которые выполняются при выполнении запроса, например о типе представления или времени его выполнения. | -| [system.quota_limits](/operations/system-tables/quota_limits) | Системная таблица, содержащая информацию о максимумах для всех интервалов каждой квоты. Одной квоте может соответствовать любое количество строк или ни одной. | -| [system.quota_usage](/operations/system-tables/quota_usage) | Системная таблица, содержащая сведения об использовании QUOTA текущим USER — сколько QUOTA уже израсходовано и сколько осталось. | +| [system.query_views_log](/operations/system-tables/query_views_log) | Системная таблица, содержащая информацию о зависимых представлениях, которые выполняются при запуске запроса, например о типе представления или времени его выполнения. | +| [system.quota_limits](/operations/system-tables/quota_limits) | Системная таблица, содержащая информацию о максимальных значениях для всех интервалов всех квот. Для одной квоты может соответствовать любое количество строк или ни одной. | +| [system.quota_usage](/operations/system-tables/quota_usage) | Системная таблица, содержащая информацию об использовании QUOTA текущим USER: сколько QUOTA уже израсходовано и сколько осталось. | | [system.quotas](/operations/system-tables/quotas) | Системная таблица, содержащая информацию о QUOTA. | | [system.quotas_usage](/operations/system-tables/quotas_usage) | Системная таблица, содержащая информацию об использовании QUOTA всеми пользователями. | -| [system.replicas](/operations/system-tables/replicas) | Системная таблица, содержащая информацию о состоянии реплицированных таблиц, находящихся на локальном сервере. Полезна для мониторинга. | +| [system.replicas](/operations/system-tables/replicas) | Системная таблица, содержащая информацию о реплицируемых таблицах, находящихся на локальном сервере, и об их состоянии. Полезна для мониторинга. | | [system.replicated_fetches](/operations/system-tables/replicated_fetches) | Системная таблица, содержащая информацию о текущих фоновых операциях загрузки данных. | -| [system.replication_queue](/operations/system-tables/replication_queue) | Системная таблица, содержащая информацию о задачах в очередях репликации, хранящихся в ClickHouse Keeper или ZooKeeper, для таблиц семейства `ReplicatedMergeTree`. | -| [system.resources](/operations/system-tables/resources) | Системная таблица, содержащая информацию о ресурсах, находящихся на локальном сервере, по одной строке на каждый ресурс. | -| [system.role_grants](/operations/system-tables/role_grants) | Системная таблица, содержащая предоставленные роли пользователям и ролям. | +| [system.replication_queue](/operations/system-tables/replication_queue) | Системная таблица, содержащая информацию о задачах в очередях репликации в ClickHouse Keeper или ZooKeeper для таблиц семейства `ReplicatedMergeTree`. | +| [system.resources](/operations/system-tables/resources) | Системная таблица, содержащая информацию о ресурсах, находящихся на локальном сервере, для каждого ресурса — по одной строке. | +| [system.role_grants](/operations/system-tables/role_grants) | Системная таблица, содержащая назначения ролей пользователям и ролям. | | [system.roles](/operations/system-tables/roles) | Системная таблица, содержащая информацию о настроенных ролях. | -| [system.row_policies](/operations/system-tables/row_policies) | Системная таблица, содержащая фильтры для отдельной таблицы, а также список ролей и/или пользователей, к которым применяется данная ROW POLICY. | +| [system.row_policies](/operations/system-tables/row_policies) | Системная таблица, содержащая фильтры для конкретной таблицы, а также список ролей и/или пользователей, которые должны использовать данную ROW POLICY. | | [system.s3_queue_settings](/operations/system-tables/s3_queue_settings) | Системная таблица, содержащая информацию о настройках таблиц S3Queue. Доступна начиная с версии сервера `24.10`. | -| [system.scheduler](/operations/system-tables/scheduler) | Системная таблица, содержащая информацию о планирующих узлах локального сервера и их состоянии. | +| [system.scheduler](/operations/system-tables/scheduler) | Системная таблица, содержащая информацию об узлах планировщика, находящихся на локальном сервере, и их состоянии. | | [system.schema_inference_cache](/operations/system-tables/schema_inference_cache) | Системная таблица, содержащая информацию обо всех кэшированных схемах файлов. | | [system.server_settings](/operations/system-tables/server_settings) | Системная таблица, содержащая сведения о глобальных настройках сервера, которые задаются в файле `config.xml`. | | [system.session_log](/operations/system-tables/session_log) | Системная таблица, содержащая сведения обо всех успешных и неуспешных входах в систему и выходах из неё. | @@ -117,21 +117,21 @@ doc_type: 'reference' | [system.settings_profiles](/operations/system-tables/settings_profiles) | Системная таблица, содержащая свойства сконфигурированных профилей настроек. | | [system.stack_trace](/operations/system-tables/stack_trace) | Системная таблица, содержащая стек‑трейсы всех потоков сервера. Позволяет разработчикам анализировать состояние сервера. | | [system.storage_policies](/operations/system-tables/storage_policies) | Системная таблица, содержащая информацию о политиках хранения и томах, определённых в конфигурации сервера. | -| [system.symbols](/operations/system-tables/symbols) | Системная таблица, полезная для экспертов по C++ и инженеров ClickHouse, содержащая сведения для анализа исполняемого файла `clickhouse`. | +| [system.symbols](/operations/system-tables/symbols) | Системная таблица, полезная для экспертов по C++ и инженеров ClickHouse, содержащая информацию для анализа исполняемого файла `clickhouse`. | | [system.table_engines](/operations/system-tables/table_engines) | Системная таблица, содержащая описания движков таблиц, поддерживаемых сервером, и их возможностей. | | [system.tables](/operations/system-tables/tables) | Системная таблица, содержащая метаданные о каждой таблице, известной серверу. | | [system.text_log](/operations/system-tables/text_log) | Системная таблица, содержащая записи журнала. | | [system.time_zones](/operations/system-tables/time_zones) | Системная таблица, содержащая список часовых поясов, поддерживаемых сервером ClickHouse. | | [system.trace_log](/operations/system-tables/trace_log) | Системная таблица, содержащая трассировки стека, собираемые профилировщиком запросов с выборочным сэмплированием. | | [system.unicode](/operations/system-tables/unicode) | Системная таблица, содержащая список символов Unicode и их свойств. | -| [system.user_processes](/operations/system-tables/user_processes) | Системная таблица, содержащая информацию, полезную для обзора использования памяти и ProfileEvents по пользователям. | +| [system.user_processes](/operations/system-tables/user_processes) | Системная таблица, содержащая информацию, полезную для обзора использования памяти и ProfileEvents пользователей. | | [system.users](/operations/system-tables/users) | Системная таблица, содержащая список учетных записей пользователей, настроенных на сервере. | -| [system.view_refreshes](/operations/system-tables/view_refreshes) | Системная таблица, содержащая информацию об объектах типа refreshable materialized view. | +| [system.view_refreshes](/operations/system-tables/view_refreshes) | Системная таблица, содержащая информацию о refreshable materialized view. | | [system.warnings](/operations/system-tables/system_warnings) | Эта таблица содержит предупреждающие сообщения о сервере ClickHouse. | -| [system.workloads](/operations/system-tables/workloads) | Системная таблица, содержащая информацию о рабочих нагрузках, выполняющихся на локальном сервере. | -| [system.zookeeper](/operations/system-tables/zookeeper) | Системная таблица, которая существует только в том случае, если настроены ClickHouse Keeper или ZooKeeper. Предоставляет данные из кластера Keeper, указанного в конфигурации. | +| [system.workloads](/operations/system-tables/workloads) | Системная таблица, содержащая информацию о рабочих нагрузках, находящихся на локальном сервере. | +| [system.zookeeper_log](/operations/system-tables/zookeeper_log) | Системная таблица, содержащая информацию о параметрах запроса к серверу ZooKeeper и его ответе. | +| [system.zookeeper](/operations/system-tables/zookeeper) | Системная таблица, существующая только при настроенных ClickHouse Keeper или ZooKeeper. Содержит данные из кластера Keeper, указанного в конфигурации. | | [system.zookeeper_connection](/operations/system-tables/zookeeper_connection) | Системная таблица, которая существует только если настроен ZooKeeper. Показывает текущие подключения к ZooKeeper (включая вспомогательные экземпляры ZooKeeper). | | [system.zookeeper_connection_log](/operations/system-tables/zookeeper_connection_log) | Показывает историю подключений к ZooKeeper (включая вспомогательные экземпляры ZooKeeper). | -| [system.zookeeper_log](/operations/system-tables/zookeeper_log) | Системная таблица, содержащая информацию о параметрах запроса к серверу ZooKeeper и ответе сервера. | {/*AUTOGENERATED_END*/ } diff --git a/i18n/ru/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/intervalLengthSum.md b/i18n/ru/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/intervalLengthSum.md index 581b3f88ae6..b1951097a60 100644 --- a/i18n/ru/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/intervalLengthSum.md +++ b/i18n/ru/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/intervalLengthSum.md @@ -86,7 +86,6 @@ SELECT id, intervalLengthSum(start, end), toTypeName(intervalLengthSum(start, en 3. Входная таблица: - ```text ┌─id─┬──────start─┬────────end─┐ │ a │ 2020-01-01 │ 2020-01-04 │ diff --git a/i18n/ru/docusaurus-plugin-content-docs/current/sql-reference/dictionaries/index.md b/i18n/ru/docusaurus-plugin-content-docs/current/sql-reference/dictionaries/index.md index 6e26c075936..650ca2bd848 100644 --- a/i18n/ru/docusaurus-plugin-content-docs/current/sql-reference/dictionaries/index.md +++ b/i18n/ru/docusaurus-plugin-content-docs/current/sql-reference/dictionaries/index.md @@ -10,6 +10,8 @@ doc_type: 'reference' import SelfManaged from '@site/i18n/ru/docusaurus-plugin-content-docs/current/_snippets/_self_managed_only_no_roadmap.md'; import CloudDetails from '@site/i18n/ru/docusaurus-plugin-content-docs/current/sql-reference/dictionaries/_snippet_dictionary_in_cloud.md'; import CloudNotSupportedBadge from '@theme/badges/CloudNotSupportedBadge'; +import ExperimentalBadge from '@theme/badges/ExperimentalBadge'; + # Словари {#dictionaries} @@ -1055,7 +1057,7 @@ SOURCE(CLICKHOUSE(... update_field 'added_time' update_lag 15)) ... - + ... @@ -1069,7 +1071,7 @@ SOURCE(CLICKHOUSE(... update_field 'added_time' update_lag 15)) ```sql CREATE DICTIONARY dict_name (...) ... -SOURCE(SOURCE_TYPE(param1 val1 ... paramN valN)) -- Конфигурация источника +SOURCE(SOURCE_TYPE(param1 val1 ... paramN valN)) -- Source configuration ... ``` @@ -1111,6 +1113,8 @@ SETTINGS(format_csv_allow_single_quotes = 0) * [Redis](#redis) * [Cassandra](#cassandra) * [PostgreSQL](#postgresql) + * [YTsaurus](#ytsaurus) + ### Локальный файл {#local-file} @@ -1895,6 +1899,48 @@ SOURCE(POSTGRESQL( Поля `table` или `where` не могут использоваться вместе с полем `query`. При этом одно из полей `table` или `query` должно быть задано. ::: +### YTsaurus {#ytsaurus} + + + + + +:::info +Это экспериментальная функция, которая может измениться в будущих релизах с нарушением обратной совместимости. +Чтобы включить использование источника словаря YTsaurus, +используйте настройку [`allow_experimental_ytsaurus_dictionary_source`](/operations/settings/settings#allow_experimental_ytsaurus_dictionary_source). +::: + +Пример настройки: + +```xml + + + http://localhost:8000 + //tmp/test + password + 1 + + +``` + +или + +```sql +SOURCE(YTSAURUS( + http_proxy_urls 'http://localhost:8000' + cypress_path '//tmp/test' + oauth_token 'password' +)) +``` + +Поля конфигурации: + +* `http_proxy_urls` – URL HTTP-прокси YTsaurus. +* `cypress_path` – путь Cypress к таблице-источнику. +* `oauth_token` – OAuth-токен. + + ### Null {#null} Специальный источник, который можно использовать для создания фиктивных (пустых) словарей. Такие словари могут быть полезны для тестов или в конфигурациях с разделением узлов данных и запросов, на узлах с distributed таблицами. diff --git a/i18n/ru/docusaurus-plugin-content-docs/current/sql-reference/statements/select/offset.md b/i18n/ru/docusaurus-plugin-content-docs/current/sql-reference/statements/select/offset.md index 8767a9962b7..254500f4713 100644 --- a/i18n/ru/docusaurus-plugin-content-docs/current/sql-reference/statements/select/offset.md +++ b/i18n/ru/docusaurus-plugin-content-docs/current/sql-reference/statements/select/offset.md @@ -9,7 +9,11 @@ doc_type: 'reference' `OFFSET` и `FETCH` позволяют извлекать данные порциями. Они задают блок строк, который вы хотите получить одним запросом. ```sql -OFFSET offset_row_count {ROW | ROWS}] [FETCH {FIRST | NEXT} fetch_row_count {ROW | ROWS} {ONLY | WITH TIES}] +-- SQL Standard style: +[OFFSET offset_row_count {ROW | ROWS}] [FETCH {FIRST | NEXT} fetch_row_count {ROW | ROWS} {ONLY | WITH TIES}] + +-- MySQL/PostgreSQL style: +[LIMIT [n, ]m] [OFFSET offset_row_count] ``` Значение `offset_row_count` или `fetch_row_count` может быть числом или литералом. Можно опустить `fetch_row_count`; по умолчанию оно равно 1. diff --git a/i18n/ru/docusaurus-plugin-content-docs/current/use-cases/observability/clickstack/deployment/docker-compose.md b/i18n/ru/docusaurus-plugin-content-docs/current/use-cases/observability/clickstack/deployment/docker-compose.md index c15d8007dd4..a17ce6732cc 100644 --- a/i18n/ru/docusaurus-plugin-content-docs/current/use-cases/observability/clickstack/deployment/docker-compose.md +++ b/i18n/ru/docusaurus-plugin-content-docs/current/use-cases/observability/clickstack/deployment/docker-compose.md @@ -48,10 +48,10 @@ Docker Compose открывает дополнительные порты для ### Клонирование репозитория {#clone-the-repo} -Чтобы развернуть с помощью Docker Compose, клонируйте репозиторий HyperDX, перейдите в каталог и выполните `docker-compose up`: +Чтобы развернуть с помощью Docker Compose, клонируйте репозиторий ClickStack, перейдите в каталог и выполните `docker-compose up`: ```shell -git clone git@github.com:hyperdxio/hyperdx.git +git clone https://github.com/ClickHouse/ClickStack.git docker compose up ``` @@ -61,7 +61,7 @@ docker compose up Создайте пользователя, указав имя пользователя и пароль, соответствующие требованиям. -При нажатии `Create` будут созданы источники данных для экземпляра ClickHouse, развернутого с помощью Helm-чарта. +При нажатии `Create` будут созданы источники данных для экземпляра ClickHouse, развернутого с помощью Docker Compose. :::note Переопределение подключения по умолчанию Вы можете переопределить подключение по умолчанию к интегрированному экземпляру ClickHouse. Подробности см. в разделе ["Использование ClickHouse Cloud"](#using-clickhouse-cloud). @@ -88,34 +88,31 @@ docker compose up Пользователи могут изменять настройки стека, например используемую версию, через файл с переменными окружения: ```shell -user@example-host hyperdx % cat .env -# Используется в docker-compose.yml {#used-by-docker-composeyml} -# Используется в docker-compose.yml {#used-by-docker-composeyml} -HDX_IMAGE_REPO=docker.hyperdx.io -IMAGE_NAME=ghcr.io/hyperdxio/hyperdx -IMAGE_NAME_DOCKERHUB=hyperdx/hyperdx -LOCAL_IMAGE_NAME=ghcr.io/hyperdxio/hyperdx-local -LOCAL_IMAGE_NAME_DOCKERHUB=hyperdx/hyperdx-local -ALL_IN_ONE_IMAGE_NAME=ghcr.io/hyperdxio/hyperdx-all-in-one -ALL_IN_ONE_IMAGE_NAME_DOCKERHUB=hyperdx/hyperdx-all-in-one -OTEL_COLLECTOR_IMAGE_NAME=ghcr.io/hyperdxio/hyperdx-otel-collector -OTEL_COLLECTOR_IMAGE_NAME_DOCKERHUB=hyperdx/hyperdx-otel-collector -CODE_VERSION=2.0.0-beta.16 -IMAGE_VERSION_SUB_TAG=.16 -IMAGE_VERSION=2-beta +user@example-host clickstack % cat .env + +# Used by docker-compose.yml +IMAGE_NAME_DOCKERHUB=clickhouse/clickstack-all-in-one +LOCAL_IMAGE_NAME_DOCKERHUB=clickhouse/clickstack-local +ALL_IN_ONE_IMAGE_NAME_DOCKERHUB=clickhouse/clickstack-all-in-one +OTEL_COLLECTOR_IMAGE_NAME_DOCKERHUB=clickhouse/clickstack-otel-collector +CODE_VERSION=2.8.0 +IMAGE_VERSION_SUB_TAG=.8.0 +IMAGE_VERSION=2 IMAGE_NIGHTLY_TAG=2-nightly +IMAGE_LATEST_TAG=latest -# Настройка URL доменов {#set-up-domain-urls} -HYPERDX_API_PORT=8000 #необязательно (не должен быть занят другими сервисами) +# Set up domain URLs +HYPERDX_API_PORT=8000 #optional (should not be taken by other services) HYPERDX_APP_PORT=8080 HYPERDX_APP_URL=http://localhost HYPERDX_LOG_LEVEL=debug HYPERDX_OPAMP_PORT=4320 -# Конфигурация OTel/ClickHouse {#otelclickhouse-config} +# Otel/Clickhouse config HYPERDX_OTEL_EXPORTER_CLICKHOUSE_DATABASE=default ``` + ### Настройка коллектора OTel {#configuring-collector} Конфигурацию коллектора OTel можно изменить при необходимости — см. раздел ["Изменение конфигурации"](/use-cases/observability/clickstack/ingesting-data/otel-collector#modifying-otel-collector-configuration). @@ -124,15 +121,15 @@ HYPERDX_OTEL_EXPORTER_CLICKHOUSE_DATABASE=default Этот дистрибутив можно использовать с ClickHouse Cloud. Пользователям следует: -* Удалить сервис ClickHouse из файла `docker-compose.yaml`. Это необязательно при тестировании, так как развернутый экземпляр ClickHouse просто будет игнорироваться, хотя и будет расходовать локальные ресурсы. При удалении сервиса убедитесь, что удалены все ссылки на него, такие как `depends_on`. +* Удалить сервис ClickHouse из файла `docker-compose.yml`. Это необязательно при тестировании, так как развернутый экземпляр ClickHouse просто будет игнорироваться, хотя и будет расходовать локальные ресурсы. При удалении сервиса убедитесь, что удалены все ссылки на него, такие как `depends_on`. -* Изменить OTel collector для использования экземпляра ClickHouse Cloud, задав переменные окружения `CLICKHOUSE_ENDPOINT`, `CLICKHOUSE_USER` и `CLICKHOUSE_PASSWORD` в файле `docker-compose.yaml`. В частности, добавьте переменные окружения в сервис OTel collector: +* Изменить OTel collector для использования экземпляра ClickHouse Cloud, задав переменные окружения `CLICKHOUSE_ENDPOINT`, `CLICKHOUSE_USER` и `CLICKHOUSE_PASSWORD` в файле `docker-compose.yml`. В частности, добавьте переменные окружения в сервис OTel collector: ```shell otel-collector: - image: ${OTEL_COLLECTOR_IMAGE_NAME}:${IMAGE_VERSION} + image: ${OTEL_COLLECTOR_IMAGE_NAME_DOCKERHUB}:${IMAGE_VERSION} environment: - CLICKHOUSE_ENDPOINT: '' # HTTPS endpoint here + CLICKHOUSE_ENDPOINT: '' # https endpoint here CLICKHOUSE_USER: '' CLICKHOUSE_PASSWORD: '' HYPERDX_OTEL_EXPORTER_CLICKHOUSE_DATABASE: ${HYPERDX_OTEL_EXPORTER_CLICKHOUSE_DATABASE} @@ -155,25 +152,25 @@ HYPERDX_OTEL_EXPORTER_CLICKHOUSE_DATABASE=default -Чтобы их задать, измените соответствующие сервисы в файле `docker-compose.yaml`: +Чтобы их задать, измените соответствующие сервисы в файле `docker-compose.yml`: ```yaml app: - image: ${HDX_IMAGE_REPO}/${IMAGE_NAME_DOCKERHUB}:${IMAGE_VERSION} + image: ${IMAGE_NAME_DOCKERHUB}:${IMAGE_VERSION} ports: - ${HYPERDX_API_PORT}:${HYPERDX_API_PORT} - ${HYPERDX_APP_PORT}:${HYPERDX_APP_PORT} environment: - BETA_CH_OTEL_JSON_SCHEMA_ENABLED: true # включение JSON + BETA_CH_OTEL_JSON_SCHEMA_ENABLED: true # enable JSON FRONTEND_URL: ${HYPERDX_APP_URL}:${HYPERDX_APP_PORT} HYPERDX_API_KEY: ${HYPERDX_API_KEY} HYPERDX_API_PORT: ${HYPERDX_API_PORT} - # сокращено для краткости + # truncated for brevity otel-collector: - image: ${HDX_IMAGE_REPO}/${OTEL_COLLECTOR_IMAGE_NAME_DOCKERHUB}:${IMAGE_VERSION} + image: ${OTEL_COLLECTOR_IMAGE_NAME_DOCKERHUB}:${IMAGE_VERSION} environment: - OTEL_AGENT_FEATURE_GATE_ARG: '--feature-gates=clickhouse.json' # включение JSON + OTEL_AGENT_FEATURE_GATE_ARG: '--feature-gates=clickhouse.json' # enable JSON CLICKHOUSE_ENDPOINT: 'tcp://ch-server:9000?dial_timeout=10s' - # сокращено для краткости + # truncated for brevity ``` diff --git a/i18n/zh/docusaurus-plugin-content-docs/current/about-us/beta-and-experimental-features.md b/i18n/zh/docusaurus-plugin-content-docs/current/about-us/beta-and-experimental-features.md index e43d53cc191..79cd39f7192 100644 --- a/i18n/zh/docusaurus-plugin-content-docs/current/about-us/beta-and-experimental-features.md +++ b/i18n/zh/docusaurus-plugin-content-docs/current/about-us/beta-and-experimental-features.md @@ -94,76 +94,77 @@ doc_type: 'reference' ## 实验性设置 {#experimental-settings} -| 名称 | 默认 | -| ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------- | -| [allow_experimental_replacing_merge_with_cleanup](/operations/settings/merge-tree-settings#allow_experimental_replacing_merge_with_cleanup) | `0` | -| [allow_experimental_reverse_key](/operations/settings/merge-tree-settings#allow_experimental_reverse_key) | `0` | -| [allow_remote_fs_zero_copy_replication](/operations/settings/merge-tree-settings#allow_remote_fs_zero_copy_replication) | `0` | -| [enable_replacing_merge_with_cleanup_for_min_age_to_force_merge](/operations/settings/merge-tree-settings#enable_replacing_merge_with_cleanup_for_min_age_to_force_merge) | `0` | -| [force_read_through_cache_for_merges](/operations/settings/merge-tree-settings#force_read_through_cache_for_merges) | `0` | -| [merge_selector_algorithm](/operations/settings/merge-tree-settings#merge_selector_algorithm) | `简单` | -| [notify_newest_block_number](/operations/settings/merge-tree-settings#notify_newest_block_number) | `0` | -| [part_moves_between_shards_delay_seconds](/operations/settings/merge-tree-settings#part_moves_between_shards_delay_seconds) | `30` | -| [part_moves_between_shards_enable](/operations/settings/merge-tree-settings#part_moves_between_shards_enable) | `0` | -| [remote_fs_zero_copy_path_compatible_mode](/operations/settings/merge-tree-settings#remote_fs_zero_copy_path_compatible_mode) | `0` | -| [remote_fs_zero_copy_zookeeper_path](/operations/settings/merge-tree-settings#remote_fs_zero_copy_zookeeper_path) | `/clickhouse/zero_copy` | -| [remove_rolled_back_parts_immediately](/operations/settings/merge-tree-settings#remove_rolled_back_parts_immediately) | `1` | -| [shared_merge_tree_virtual_parts_discovery_batch](/operations/settings/merge-tree-settings#shared_merge_tree_virtual_parts_discovery_batch) | `1` | -| [allow_experimental_kafka_offsets_storage_in_keeper](/operations/settings/settings#allow_experimental_kafka_offsets_storage_in_keeper) | `0` | -| [allow_experimental_delta_lake_writes](/operations/settings/settings#allow_experimental_delta_lake_writes) | `0` | -| [allow_experimental_materialized_postgresql_table](/operations/settings/settings#allow_experimental_materialized_postgresql_table) | `0` | -| [allow_experimental_funnel_functions](/operations/settings/settings#allow_experimental_funnel_functions) | `0` | -| [allow_experimental_nlp_functions](/operations/settings/settings#allow_experimental_nlp_functions) | `0` | -| [allow_experimental_hash_functions](/operations/settings/settings#allow_experimental_hash_functions) | `0` | -| [allow_experimental_time_series_table](/operations/settings/settings#allow_experimental_time_series_table) | `0` | -| [allow_experimental_codecs](/operations/settings/settings#allow_experimental_codecs) | `0` | -| [throw_on_unsupported_query_inside_transaction](/operations/settings/settings#throw_on_unsupported_query_inside_transaction) | `1` | -| [wait_changes_become_visible_after_commit_mode](/operations/settings/settings#wait_changes_become_visible_after_commit_mode) | `wait_unknown` | -| [implicit_transaction](/operations/settings/settings#implicit_transaction) | `0` | -| [grace_hash_join_initial_buckets](/operations/settings/settings#grace_hash_join_initial_buckets) | `1` | -| [grace_hash_join_max_buckets](/operations/settings/settings#grace_hash_join_max_buckets) | `1024` | -| [join_to_sort_minimum_perkey_rows](/operations/settings/settings#join_to_sort_minimum_perkey_rows) | `40` | -| [join_to_sort_maximum_table_rows](/operations/settings/settings#join_to_sort_maximum_table_rows) | `10000` | -| [allow_experimental_join_right_table_sorting](/operations/settings/settings#allow_experimental_join_right_table_sorting) | `0` | -| [allow_experimental_statistics](/operations/settings/settings#allow_experimental_statistics) | `0` | -| [use_statistics_cache](/operations/settings/settings#use_statistics_cache) | `0` | -| [allow_experimental_full_text_index](/operations/settings/settings#allow_experimental_full_text_index) | `0` | -| [allow_experimental_window_view](/operations/settings/settings#allow_experimental_window_view) | `0` | -| [window_view_clean_interval](/operations/settings/settings#window_view_clean_interval) | `60` | -| [window_view_heartbeat_interval](/operations/settings/settings#window_view_heartbeat_interval) | `15` | -| [wait_for_window_view_fire_signal_timeout](/operations/settings/settings#wait_for_window_view_fire_signal_timeout) | `10` | -| [stop_refreshable_materialized_views_on_startup](/operations/settings/settings#stop_refreshable_materialized_views_on_startup) | `0` | -| [allow_experimental_database_materialized_postgresql](/operations/settings/settings#allow_experimental_database_materialized_postgresql) | `0` | -| [allow_experimental_qbit_type](/operations/settings/settings#allow_experimental_qbit_type) | `0` | -| [allow_experimental_query_deduplication](/operations/settings/settings#allow_experimental_query_deduplication) | `0` | -| [allow_experimental_database_hms_catalog](/operations/settings/settings#allow_experimental_database_hms_catalog) | `0` | -| [allow_experimental_kusto_dialect](/operations/settings/settings#allow_experimental_kusto_dialect) | `0` | -| [allow_experimental_prql_dialect](/operations/settings/settings#allow_experimental_prql_dialect) | `0` | -| [enable_adaptive_memory_spill_scheduler](/operations/settings/settings#enable_adaptive_memory_spill_scheduler) | `0` | -| [allow_experimental_insert_into_iceberg](/operations/settings/settings#allow_experimental_insert_into_iceberg) | `0` | -| [allow_experimental_iceberg_compaction](/operations/settings/settings#allow_experimental_iceberg_compaction) | `0` | -| [write_full_path_in_iceberg_metadata](/operations/settings/settings#write_full_path_in_iceberg_metadata) | `0` | -| [iceberg_metadata_compression_method](/operations/settings/settings#iceberg_metadata_compression_method) | `` | -| [make_distributed_plan](/operations/settings/settings#make_distributed_plan) | `0` | -| [distributed_plan_execute_locally](/operations/settings/settings#distributed_plan_execute_locally) | `0` | -| [distributed_plan_default_shuffle_join_bucket_count](/operations/settings/settings#distributed_plan_default_shuffle_join_bucket_count) | `8` | -| [distributed_plan_default_reader_bucket_count](/operations/settings/settings#distributed_plan_default_reader_bucket_count) | `8` | -| [distributed_plan_force_exchange_kind](/operations/settings/settings#distributed_plan_force_exchange_kind) | `` | -| [distributed_plan_max_rows_to_broadcast](/operations/settings/settings#distributed_plan_max_rows_to_broadcast) | `20000` | -| [allow_experimental_ytsaurus_table_engine](/operations/settings/settings#allow_experimental_ytsaurus_table_engine) | `0` | -| [allow_experimental_ytsaurus_table_function](/operations/settings/settings#allow_experimental_ytsaurus_table_function) | `0` | -| [allow_experimental_ytsaurus_dictionary_source](/operations/settings/settings#allow_experimental_ytsaurus_dictionary_source) | `0` | -| [distributed_plan_force_shuffle_aggregation](/operations/settings/settings#distributed_plan_force_shuffle_aggregation) | `0` | -| [enable_join_runtime_filters](/operations/settings/settings#enable_join_runtime_filters) | `0` | -| [join_runtime_filter_exact_values_limit](/operations/settings/settings#join_runtime_filter_exact_values_limit) | `10000` | -| [join_runtime_bloom_filter_bytes](/operations/settings/settings#join_runtime_bloom_filter_bytes) | `524288` | -| [join_runtime_bloom_filter_hash_functions](/operations/settings/settings#join_runtime_bloom_filter_hash_functions) | `3` | -| [rewrite_in_to_join](/operations/settings/settings#rewrite_in_to_join) | `0` | -| [allow_experimental_time_series_aggregate_functions](/operations/settings/settings#allow_experimental_time_series_aggregate_functions) | `0` | -| [promql_database](/operations/settings/settings#promql_database) | `` | -| [promql_table](/operations/settings/settings#promql_table) | `` | -| [promql_evaluation_time](/operations/settings/settings#promql_evaluation_time) | `auto` | -| [allow_experimental_alias_table_engine](/operations/settings/settings#allow_experimental_alias_table_engine) | `0` | -| [use_paimon_partition_pruning](/operations/settings/settings#use_paimon_partition_pruning) | `0` | +| 名称 | 默认 | +| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------- | +| [allow_experimental_kafka_offsets_storage_in_keeper](/operations/settings/settings#allow_experimental_kafka_offsets_storage_in_keeper) | `0` | +| [allow_experimental_delta_lake_writes](/operations/settings/settings#allow_experimental_delta_lake_writes) | `0` | +| [allow_experimental_materialized_postgresql_table](/operations/settings/settings#allow_experimental_materialized_postgresql_table) | `0` | +| [allow_experimental_funnel_functions](/operations/settings/settings#allow_experimental_funnel_functions) | `0` | +| [allow_experimental_nlp_functions](/operations/settings/settings#allow_experimental_nlp_functions) | `0` | +| [allow_experimental_hash_functions](/operations/settings/settings#allow_experimental_hash_functions) | `0` | +| [allow_experimental_time_series_table](/operations/settings/settings#allow_experimental_time_series_table) | `0` | +| [allow_experimental_codecs](/operations/settings/settings#allow_experimental_codecs) | `0` | +| [throw_on_unsupported_query_inside_transaction](/operations/settings/settings#throw_on_unsupported_query_inside_transaction) | `1` | +| [wait_changes_become_visible_after_commit_mode](/operations/settings/settings#wait_changes_become_visible_after_commit_mode) | `wait_unknown` | +| [implicit_transaction](/operations/settings/settings#implicit_transaction) | `0` | +| [grace_hash_join_initial_buckets](/operations/settings/settings#grace_hash_join_initial_buckets) | `1` | +| [grace_hash_join_max_buckets](/operations/settings/settings#grace_hash_join_max_buckets) | `1024` | +| [join_to_sort_minimum_perkey_rows](/operations/settings/settings#join_to_sort_minimum_perkey_rows) | `40` | +| [join_to_sort_maximum_table_rows](/operations/settings/settings#join_to_sort_maximum_table_rows) | `10000` | +| [allow_experimental_join_right_table_sorting](/operations/settings/settings#allow_experimental_join_right_table_sorting) | `0` | +| [allow_experimental_statistics](/operations/settings/settings#allow_experimental_statistics) | `0` | +| [use_statistics_cache](/operations/settings/settings#use_statistics_cache) | `0` | +| [allow_experimental_full_text_index](/operations/settings/settings#allow_experimental_full_text_index) | `0` | +| [allow_experimental_window_view](/operations/settings/settings#allow_experimental_window_view) | `0` | +| [window_view_clean_interval](/operations/settings/settings#window_view_clean_interval) | `60` | +| [window_view_heartbeat_interval](/operations/settings/settings#window_view_heartbeat_interval) | `15` | +| [wait_for_window_view_fire_signal_timeout](/operations/settings/settings#wait_for_window_view_fire_signal_timeout) | `10` | +| [stop_refreshable_materialized_views_on_startup](/operations/settings/settings#stop_refreshable_materialized_views_on_startup) | `0` | +| [allow_experimental_database_materialized_postgresql](/operations/settings/settings#allow_experimental_database_materialized_postgresql) | `0` | +| [allow_experimental_qbit_type](/operations/settings/settings#allow_experimental_qbit_type) | `0` | +| [allow_experimental_query_deduplication](/operations/settings/settings#allow_experimental_query_deduplication) | `0` | +| [allow_experimental_database_hms_catalog](/operations/settings/settings#allow_experimental_database_hms_catalog) | `0` | +| [allow_experimental_kusto_dialect](/operations/settings/settings#allow_experimental_kusto_dialect) | `0` | +| [allow_experimental_prql_dialect](/operations/settings/settings#allow_experimental_prql_dialect) | `0` | +| [enable_adaptive_memory_spill_scheduler](/operations/settings/settings#enable_adaptive_memory_spill_scheduler) | `0` | +| [allow_experimental_insert_into_iceberg](/operations/settings/settings#allow_experimental_insert_into_iceberg) | `0` | +| [allow_experimental_iceberg_compaction](/operations/settings/settings#allow_experimental_iceberg_compaction) | `0` | +| [write_full_path_in_iceberg_metadata](/operations/settings/settings#write_full_path_in_iceberg_metadata) | `0` | +| [iceberg_metadata_compression_method](/operations/settings/settings#iceberg_metadata_compression_method) | `` | +| [make_distributed_plan](/operations/settings/settings#make_distributed_plan) | `0` | +| [distributed_plan_execute_locally](/operations/settings/settings#distributed_plan_execute_locally) | `0` | +| [distributed_plan_default_shuffle_join_bucket_count](/operations/settings/settings#distributed_plan_default_shuffle_join_bucket_count) | `8` | +| [distributed_plan_default_reader_bucket_count](/operations/settings/settings#distributed_plan_default_reader_bucket_count) | `8` | +| [distributed_plan_force_exchange_kind](/operations/settings/settings#distributed_plan_force_exchange_kind) | `` | +| [distributed_plan_max_rows_to_broadcast](/operations/settings/settings#distributed_plan_max_rows_to_broadcast) | `20000` | +| [allow_experimental_ytsaurus_table_engine](/operations/settings/settings#allow_experimental_ytsaurus_table_engine) | `0` | +| [allow_experimental_ytsaurus_table_function](/operations/settings/settings#allow_experimental_ytsaurus_table_function) | `0` | +| [allow_experimental_ytsaurus_dictionary_source](/operations/settings/settings#allow_experimental_ytsaurus_dictionary_source) | `0` | +| [distributed_plan_force_shuffle_aggregation](/operations/settings/settings#distributed_plan_force_shuffle_aggregation) | `0` | +| [enable_join_runtime_filters](/operations/settings/settings#enable_join_runtime_filters) | `0` | +| [join_runtime_filter_exact_values_limit](/operations/settings/settings#join_runtime_filter_exact_values_limit) | `10000` | +| [join_runtime_bloom_filter_bytes](/operations/settings/settings#join_runtime_bloom_filter_bytes) | `524288` | +| [join_runtime_bloom_filter_hash_functions](/operations/settings/settings#join_runtime_bloom_filter_hash_functions) | `3` | +| [rewrite_in_to_join](/operations/settings/settings#rewrite_in_to_join) | `0` | +| [allow_experimental_time_series_aggregate_functions](/operations/settings/settings#allow_experimental_time_series_aggregate_functions) | `0` | +| [promql_database](/operations/settings/settings#promql_database) | `` | +| [promql_table](/operations/settings/settings#promql_table) | `` | +| [promql_evaluation_time](/operations/settings/settings#promql_evaluation_time) | `auto` | +| [allow_experimental_alias_table_engine](/operations/settings/settings#allow_experimental_alias_table_engine) | `0` | +| [use_paimon_partition_pruning](/operations/settings/settings#use_paimon_partition_pruning) | `0` | +| [allow_experimental_replacing_merge_with_cleanup](/operations/settings/merge-tree-settings#allow_experimental_replacing_merge_with_cleanup) | `0` | +| [allow_experimental_reverse_key](/operations/settings/merge-tree-settings#allow_experimental_reverse_key) | `0` | +| [allow_remote_fs_zero_copy_replication](/operations/settings/merge-tree-settings#allow_remote_fs_zero_copy_replication) | `0` | +| [enable_replacing_merge_with_cleanup_for_min_age_to_force_merge](/operations/settings/merge-tree-settings#enable_replacing_merge_with_cleanup_for_min_age_to_force_merge) | `0` | +| [force_read_through_cache_for_merges](/operations/settings/merge-tree-settings#force_read_through_cache_for_merges) | `0` | +| [merge_selector_algorithm](/operations/settings/merge-tree-settings#merge_selector_algorithm) | `Simple` | +| [merge_selector_enable_heuristic_to_lower_max_parts_to_merge_at_once](/operations/settings/merge-tree-settings#merge_selector_enable_heuristic_to_lower_max_parts_to_merge_at_once) | `0` | +| [notify_newest_block_number](/operations/settings/merge-tree-settings#notify_newest_block_number) | `0` | +| [part_moves_between_shards_delay_seconds](/operations/settings/merge-tree-settings#part_moves_between_shards_delay_seconds) | `30` | +| [part_moves_between_shards_enable](/operations/settings/merge-tree-settings#part_moves_between_shards_enable) | `0` | +| [remote_fs_zero_copy_path_compatible_mode](/operations/settings/merge-tree-settings#remote_fs_zero_copy_path_compatible_mode) | `0` | +| [remote_fs_zero_copy_zookeeper_path](/operations/settings/merge-tree-settings#remote_fs_zero_copy_zookeeper_path) | `/clickhouse/zero_copy` | +| [remove_rolled_back_parts_immediately](/operations/settings/merge-tree-settings#remove_rolled_back_parts_immediately) | `1` | +| [shared_merge_tree_virtual_parts_discovery_batch](/operations/settings/merge-tree-settings#shared_merge_tree_virtual_parts_discovery_batch) | `1` | {/*AUTOGENERATED_END*/ } diff --git a/i18n/zh/docusaurus-plugin-content-docs/current/about-us/history.md b/i18n/zh/docusaurus-plugin-content-docs/current/about-us/history.md index d8a1d1081a3..dd0f2da768a 100644 --- a/i18n/zh/docusaurus-plugin-content-docs/current/about-us/history.md +++ b/i18n/zh/docusaurus-plugin-content-docs/current/about-us/history.md @@ -8,8 +8,6 @@ title: 'ClickHouse 历史' doc_type: 'reference' --- - - # ClickHouse 历史 {#clickhouse-history} ClickHouse 最初是为支撑 [Yandex.Metrica](https://metrica.yandex.com/)、[全球第二大 Web 分析平台](http://w3techs.com/technologies/overview/traffic_analysis/all) 而开发的,并且至今仍是其核心组件。数据库中包含超过 13 万亿条记录,每天新增超过 200 亿个事件,ClickHouse 允许直接基于未聚合数据即时生成自定义报表。本文将简要介绍 ClickHouse 在早期开发阶段的目标。 @@ -18,8 +16,6 @@ Yandex.Metrica 会基于点击和会话按需生成自定义报表,用户可 截至 2014 年 4 月,Yandex.Metrica 每天跟踪大约 120 亿个事件(页面浏览和点击)。为了构建自定义报表,所有这些事件都需要被存储。单个查询可能需要在几百毫秒内扫描数百万行,或者在几秒内扫描数亿行数据。 - - ## 在 Yandex.Metrica 和其他 Yandex 服务中的使用 {#usage-in-yandex-metrica-and-other-yandex-services} ClickHouse 在 Yandex.Metrica 中被用于多个场景。 @@ -35,8 +31,6 @@ ClickHouse 还在以下流程中发挥关键作用: 目前,在其他 Yandex 服务和部门中也部署了数十个 ClickHouse 集群:搜索垂直业务、电子商务、广告、商业分析、移动开发、个人服务等。 - - ## 聚合和非聚合数据 {#aggregated-and-non-aggregated-data} 有一种广泛流传的观点认为,要高效地进行统计计算,必须对数据进行聚合,因为这可以减少数据量。 @@ -60,4 +54,4 @@ Yandex.Metrica 有一个用于数据聚合的专用系统,称为 Metrage,大 从 2009 年开始,Yandex.Metrica 还使用了一个用于非聚合数据的专用 OLAP 数据库,称为 OLAPServer,此前主要用于报表构建器。 OLAPServer 在处理非聚合数据方面表现良好,但存在许多限制,无法按预期用于所有报表。这些限制包括:不支持多种数据类型(仅支持数字),以及无法对数据进行实时增量更新(只能通过每日重写数据来完成)。OLAPServer 不是一个 DBMS,而是一个专用数据库。 -ClickHouse 的初始目标是消除 OLAPServer 的这些限制,并解决在所有报表中处理非聚合数据的问题,但经过多年的发展,它已经成长为一个通用的数据库管理系统,适用于广泛的分析型任务。 +ClickHouse 的初始目标是消除 OLAPServer 的这些限制,并解决在所有报表中处理非聚合数据的问题,但经过多年的发展,它已经成长为一个通用的数据库管理系统,适用于广泛的分析型任务。 \ No newline at end of file diff --git a/i18n/zh/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/azure-queue.md b/i18n/zh/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/azure-queue.md index 74f731a576c..0b5e710da3f 100644 --- a/i18n/zh/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/azure-queue.md +++ b/i18n/zh/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/azure-queue.md @@ -41,14 +41,15 @@ ENGINE = AzureQueue('DefaultEndpointsProtocol=http;AccountName=devstoreaccount1; SETTINGS mode = 'unordered' ``` + ## Settings {#settings} 支持的设置大多与 `S3Queue` 表引擎相同,只是没有 `s3queue_` 前缀。参见[完整的设置列表](../../../engines/table-engines/integrations/s3queue.md#settings)。 要获取为该表配置的设置列表,请使用 `system.azure_queue_settings` 表。从 `24.10` 版本起可用。 -下面是仅与 AzureQueue 兼容且不适用于 S3Queue 的设置。 +下面是仅与 AzureQueue 兼容、而不适用于 S3Queue 的设置。 -### `after_processing_move_connection_string` {#after_processing_move_connection_string} +### `after_processing_move_connection_string` {#after_processing_move_connection_string} 当目标是另一个 Azure 容器时,用于将已成功处理的文件移动到该容器的 Azure Blob Storage 连接字符串。 @@ -58,7 +59,7 @@ SETTINGS mode = 'unordered' 默认值:空字符串。 -### `after_processing_move_container` {#after_processing_move_container} +### `after_processing_move_container` {#after_processing_move_container} 当目标是另一个 Azure 容器时,用于指定成功处理后文件要移动到的容器名称。 @@ -84,6 +85,13 @@ SETTINGS after_processing_move_container = 'dst-container'; ``` + +## 从 AzureQueue 表引擎中执行 SELECT {#select} + +在 AzureQueue 表上默认禁止执行 SELECT 查询。这遵循常见的队列模式,即数据只被读取一次,然后从队列中移除。禁止 SELECT 是为了防止意外数据丢失。 +不过,在某些情况下直接执行 SELECT 可能会很有用。要实现这一点,需要将设置 `stream_like_engine_allow_direct_select` 设为 `True`。 +AzureQueue 引擎针对 SELECT 查询有一个特殊设置:`commit_on_select`。将其设为 `False` 可在读取后保留队列中的数据,设为 `True` 则会在读取后将其移除。 + ## 描述 {#description} `SELECT` 对于流式导入并不是特别有用(除非用于调试),因为每个文件只能被导入一次。更实际的做法是使用[物化视图](../../../sql-reference/statements/create/view.md)来创建实时管道。为此: @@ -111,6 +119,7 @@ CREATE MATERIALIZED VIEW consumer TO stats SELECT * FROM stats ORDER BY key; ``` + ## 虚拟列 {#virtual-columns} * `_path` — 文件路径。 @@ -120,11 +129,11 @@ SELECT * FROM stats ORDER BY key; ## 自省 {#introspection} -通过表设置 `enable_logging_to_queue_log=1` 为该表启用日志记录。 +通过表设置 `enable_logging_to_queue_log=1` 启用该表的日志记录功能。 自省功能与 [S3Queue 表引擎](/engines/table-engines/integrations/s3queue#introspection) 相同,但有以下几个明显差异: -1. 对于服务器版本 >= 25.1,使用 `system.azure_queue` 表示队列的内存状态。对于更早的版本,使用 `system.s3queue`(其中也会包含 `azure` 表的信息)。 +1. 对于服务器版本 >= 25.1,使用 `system.azure_queue` 用于表示队列的内存状态。对于更早的版本,使用 `system.s3queue`(其中也会包含 `azure` 表的信息)。 2. 在主 ClickHouse 配置中启用 `system.azure_queue_log`,例如: ```xml @@ -142,24 +151,24 @@ SELECT * FROM stats ORDER BY key; CREATE TABLE system.azure_queue_log ( - `hostname` LowCardinality(String) COMMENT '主机名', - `event_date` Date COMMENT '写入此日志行的事件日期', - `event_time` DateTime COMMENT '写入此日志行的事件时间', - `database` String COMMENT '当前 S3Queue 表所在的数据库名称。', - `table` String COMMENT 'S3Queue 表的名称。', - `uuid` String COMMENT 'S3Queue 表的 UUID', - `file_name` String COMMENT '正在处理的文件名', - `rows_processed` UInt64 COMMENT '已处理的行数', - `status` Enum8('Processed' = 0, 'Failed' = 1) COMMENT '文件处理状态', - `processing_start_time` Nullable(DateTime) COMMENT '文件处理开始时间', - `processing_end_time` Nullable(DateTime) COMMENT '文件处理结束时间', - `exception` String COMMENT '异常消息(如有发生)' + `hostname` LowCardinality(String) COMMENT 'Hostname', + `event_date` Date COMMENT 'Event date of writing this log row', + `event_time` DateTime COMMENT 'Event time of writing this log row', + `database` String COMMENT 'The name of a database where current S3Queue table lives.', + `table` String COMMENT 'The name of S3Queue table.', + `uuid` String COMMENT 'The UUID of S3Queue table', + `file_name` String COMMENT 'File name of the processing file', + `rows_processed` UInt64 COMMENT 'Number of processed rows', + `status` Enum8('Processed' = 0, 'Failed' = 1) COMMENT 'Status of the processing file', + `processing_start_time` Nullable(DateTime) COMMENT 'Time of the start of processing the file', + `processing_end_time` Nullable(DateTime) COMMENT 'Time of the end of processing the file', + `exception` String COMMENT 'Exception message if happened' ) ENGINE = MergeTree PARTITION BY toYYYYMM(event_date) ORDER BY (event_date, event_time) SETTINGS index_granularity = 8192 -COMMENT '包含 S3Queue 引擎处理文件信息的日志条目。' +COMMENT 'Contains logging entries with the information files processes by S3Queue engine.' ``` @@ -171,7 +180,7 @@ FROM system.azure_queue_log LIMIT 1 FORMAT Vertical -第 1 行: +Row 1: ────── hostname: clickhouse event_date: 2024-12-16 @@ -186,6 +195,6 @@ processing_start_time: 2024-12-16 13:42:47 processing_end_time: 2024-12-16 13:42:47 exception: -返回 1 行。用时:0.002 秒。 +1 row in set. Elapsed: 0.002 sec. ``` diff --git a/i18n/zh/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/s3queue.md b/i18n/zh/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/s3queue.md index 690d01860c6..c35fd297c1e 100644 --- a/i18n/zh/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/s3queue.md +++ b/i18n/zh/docusaurus-plugin-content-docs/current/engines/table-engines/integrations/s3queue.md @@ -83,6 +83,7 @@ SETTINGS mode = 'ordered'; ``` + ## 设置 {#settings} 要获取为该表配置的设置列表,请查询 `system.s3_queue_settings` 系统表。自 `24.10` 版本起可用。 @@ -96,7 +97,7 @@ SETTINGS 默认值:在 24.6 之前的版本中默认为 `ordered`。从 24.6 开始不再提供默认值,该设置必须手动指定。对于在更早版本中创建的表,为了兼容性其默认值仍为 `Ordered`。 -### `after_processing` {#after_processing} +### `after_processing` {#after_processing} 如何在文件成功处理后进行后续操作。 @@ -132,7 +133,8 @@ SETTINGS 标记操作需要提供标签键和值,分别通过 `after_processing_tag_key` 和 `after_processing_tag_value` 配置。 -### `after_processing_retries` {#after_processing_retries} + +### `after_processing_retries` {#after_processing_retries} 在放弃之前,对所请求的后处理操作进行重试的次数。 @@ -142,9 +144,9 @@ SETTINGS 默认值:`10`。 -### `after_processing_move_access_key_id` {#after_processing_move_access_key_id} +### `after_processing_move_access_key_id` {#after_processing_move_access_key_id} -如果目标是另一个 S3 bucket,则该选项为将成功处理的文件移动到目标 S3 bucket 所使用的 Access Key ID。 +如果目标是另一个 S3 bucket,则该选项指定用于将成功处理的文件移动到目标 S3 bucket 的 Access Key ID。 可能的取值: @@ -162,7 +164,7 @@ SETTINGS 默认值:空字符串。 -### `after_processing_move_secret_access_key` {#after_processing_move_secret_access_key} +### `after_processing_move_secret_access_key` {#after_processing_move_secret_access_key} 当目标是另一个 S3 bucket 时,用于将成功处理的文件移动到该目标 bucket 的 Secret Access Key。 @@ -172,7 +174,7 @@ SETTINGS 默认值:空字符串。 -### `after_processing_move_uri` {#after_processing_move_uri} +### `after_processing_move_uri` {#after_processing_move_uri} 当目标是另一个 S3 bucket 时,用于存放已成功处理文件的 S3 bucket 的 URI。 @@ -182,7 +184,7 @@ SETTINGS 默认值:空字符串。 -### `after_processing_tag_key` {#after_processing_tag_key} +### `after_processing_tag_key` {#after_processing_tag_key} 当 `after_processing='tag'` 时,用于给成功处理的文件打标签的标签键。 @@ -192,7 +194,7 @@ SETTINGS 默认值:空字符串。 -### `after_processing_tag_value` {#after_processing_tag_value} +### `after_processing_tag_value` {#after_processing_tag_value} 当 `after_processing='tag'` 时,为成功处理的文件设置标签时使用的标签值。 @@ -202,7 +204,7 @@ SETTINGS 默认值:空字符串。 -### `keeper_path` {#keeper_path} +### `keeper_path` {#keeper_path} ZooKeeper 中的路径可以通过表引擎设置单独指定;如果未指定,则默认路径由全局配置中提供的路径和表的 UUID 组成。 可能的取值: @@ -211,25 +213,25 @@ ZooKeeper 中的路径可以通过表引擎设置单独指定;如果未指定 默认值:`/`。 -### `s3queue_loading_retries` {#loading_retries} +### `s3queue_loading_retries` {#loading_retries} -文件加载最多重试指定的次数。默认情况下,不进行重试。 +对文件加载操作最多重试指定的次数。默认情况下,不进行重试。 可能的取值: * 正整数。 默认值:`0`。 -### `s3queue_processing_threads_num` {#processing_threads_num} +### `s3queue_processing_threads_num` {#processing_threads_num} -用于执行处理的线程数。仅适用于 `Unordered` 模式。 +用于处理的线程数。仅适用于 `Unordered` 模式。 默认值:CPU 数量或 16。 -### `s3queue_parallel_inserts` {#parallel_inserts} +### `s3queue_parallel_inserts` {#parallel_inserts} 默认情况下,`processing_threads_num` 只会产生一个 `INSERT`,因此只是以多线程方式下载文件并进行解析。 -但这会限制并行度,因此为获得更高吞吐量,应使用 `parallel_inserts=true`,这将允许并行插入数据(但请注意,这会导致为 MergeTree 系列表引擎生成更多数据片段)。 +但这会限制并行度,因此为获得更高吞吐量,应使用 `parallel_inserts=true`,这将允许并行插入数据(但请注意,这会导致为 MergeTree 系列表引擎生成更多分区片段)。 :::note `INSERT` 的触发会受 `max_process*_before_commit` 相关设置约束。 @@ -237,13 +239,13 @@ ZooKeeper 中的路径可以通过表引擎设置单独指定;如果未指定 默认值:`false`。 -### `s3queue_enable_logging_to_s3queue_log` {#enable_logging_to_s3queue_log} +### `s3queue_enable_logging_to_s3queue_log` {#enable_logging_to_s3queue_log} 启用将日志记录写入 `system.s3queue_log`。 默认值:`0`。 -### `s3queue_polling_min_timeout_ms` {#polling_min_timeout_ms} +### `s3queue_polling_min_timeout_ms` {#polling_min_timeout_ms} 指定 ClickHouse 在进行下一次轮询尝试之前等待的最短时间(以毫秒为单位)。 @@ -253,7 +255,7 @@ ZooKeeper 中的路径可以通过表引擎设置单独指定;如果未指定 默认值:`1000`。 -### `s3queue_polling_max_timeout_ms` {#polling_max_timeout_ms} +### `s3queue_polling_max_timeout_ms` {#polling_max_timeout_ms} 定义 ClickHouse 在发起下一次轮询尝试之前的最大等待时间(以毫秒为单位)。 @@ -263,9 +265,9 @@ ZooKeeper 中的路径可以通过表引擎设置单独指定;如果未指定 默认值:`10000`。 -### `s3queue_polling_backoff_ms` {#polling_backoff_ms} +### `s3queue_polling_backoff_ms` {#polling_backoff_ms} -确定在未发现新文件时,需要加到上一次轮询间隔上的额外等待时间。下一次轮询会在上一次间隔与该退避值之和或最大间隔(取二者中较小值)之后触发。 +确定在未发现新文件时,需要加到上一次轮询间隔上的额外等待时间。下一次轮询会在上一次间隔与该退避时间之和或最大间隔(取二者中较小值)之后触发。 可能的取值: @@ -284,7 +286,7 @@ ZooKeeper 中的路径可以通过表引擎设置单独指定;如果未指定 默认值:`1000`。 -### `s3queue_tracked_file_ttl_sec` {#tracked_file_ttl_sec} +### `s3queue_tracked_file_ttl_sec` {#tracked_file_ttl_sec} 在“unordered”模式下,在 ZooKeeper 节点中保留已处理文件的最长时间(以秒为单位,默认永久保存)。对“ordered”模式无效。 在经过指定秒数后,该文件会被重新导入。 @@ -295,27 +297,27 @@ ZooKeeper 中的路径可以通过表引擎设置单独指定;如果未指定 默认值:`0`。 -### `s3queue_cleanup_interval_min_ms` {#cleanup_interval_min_ms} +### `s3queue_cleanup_interval_min_ms` {#cleanup_interval_min_ms} -用于 `Ordered` 模式。定义负责维护已跟踪文件 TTL 和最大已跟踪文件集合的后台任务在重新调度间隔上的最小值。 +用于 `Ordered` 模式。定义负责维护已跟踪文件生存时间 (TTL) 和最大已跟踪文件集合的后台任务的重新调度间隔下限。 默认值:`10000`。 -### `s3queue_cleanup_interval_max_ms` {#cleanup_interval_max_ms} +### `s3queue_cleanup_interval_max_ms` {#cleanup_interval_max_ms} -用于 “Ordered” 模式。定义重新调度后台任务的时间间隔的最大上限,该后台任务负责维护已跟踪文件的 TTL,以及已跟踪文件集合的最大大小。 +用于 “Ordered” 模式。定义后台任务重新调度时间间隔的上限,该后台任务负责维护已跟踪文件的生存时间 (TTL),以及已跟踪文件集合的最大大小。 默认值:`30000`。 ### `s3queue_buckets` {#buckets} -用于 Ordered 模式。从 `24.6` 版本开始可用。如果存在多个 S3Queue 表副本,并且它们都使用 Keeper 中相同的元数据目录,那么 `s3queue_buckets` 的值至少要等于副本数量。如果同时使用了 `s3queue_processing_threads` 设置,那么进一步增大 `s3queue_buckets` 的值是合理的,因为它决定了 `S3Queue` 处理的实际并行度。 +用于 Ordered 模式。自 `24.6` 版本起可用。如果存在多个 S3Queue 表副本,并且它们都使用 Keeper 中相同的元数据目录,那么 `s3queue_buckets` 的值至少应等于副本数量。如果同时使用了 `s3queue_processing_threads` 设置,那么将 `s3queue_buckets` 的值进一步增大是有意义的,因为它决定了 `S3Queue` 处理的实际并行度。 -### `use_persistent_processing_nodes` {#use_persistent_processing_nodes} +### `use_persistent_processing_nodes` {#use_persistent_processing_nodes} -默认情况下,S3Queue 表始终使用临时处理节点。如果在 S3Queue 将已处理文件提交到 ZooKeeper 之前、但在其开始处理之后,ZooKeeper 会话过期,就可能导致数据重复。此设置会强制服务器在 Keeper 会话过期的情况下消除产生重复数据的可能性。 +默认情况下,S3Queue 表一直使用临时处理节点。如果在 S3Queue 将已处理文件提交到 ZooKeeper 之前、但在其开始处理之后,ZooKeeper 会话过期,就可能导致数据重复。此设置会强制服务器在 Keeper 会话过期时避免出现重复数据。 -### `persistent_processing_nodes_ttl_seconds` {#persistent_processing_nodes_ttl_seconds} +### `persistent_processing_nodes_ttl_seconds` {#persistent_processing_nodes_ttl_seconds} 在服务器异常终止的情况下,如果启用了 `use_persistent_processing_nodes`,就有可能出现尚未被移除的处理节点(processing nodes)。此设置用于定义一个时间段,在该时间段内,这些处理节点可以被安全清理。 @@ -323,7 +325,7 @@ ZooKeeper 中的路径可以通过表引擎设置单独指定;如果未指定 ## 与 S3 相关的设置 {#s3-settings} -该引擎支持所有 S3 相关设置。有关 S3 设置的更多信息,请参阅[此处](../../../engines/table-engines/integrations/s3.md)。 +该引擎支持所有与 S3 相关的设置。有关 S3 设置的更多信息,请参阅[此处](../../../engines/table-engines/integrations/s3.md)。 ## 基于角色的 S3 访问 {#s3-role-based-access} @@ -348,6 +350,7 @@ SETTINGS ... ``` + ## S3Queue 有序模式 {#ordered-mode} `S3Queue` 处理模式可以在 ZooKeeper 中存储更少的元数据,但有一个限制:按时间更晚添加的文件,其名称在字母数字顺序上必须更大。 @@ -358,6 +361,12 @@ SETTINGS 不建议在 `24.6` 版本之前使用 `(s3queue_)processing_threads_num` 设置。 `(s3queue_)buckets` 设置从 `24.6` 版本开始可用。 +## 从 S3Queue 表引擎中执行 SELECT 查询 {#select} + +默认情况下,S3Queue 表禁止执行 SELECT 查询。这符合常见的队列模式:数据只被读取一次,随后从队列中移除。禁止 SELECT 是为了防止意外数据丢失。 +但在某些情况下,执行 SELECT 查询可能是有用的。要实现这一点,需要将设置 `stream_like_engine_allow_direct_select` 设为 `True`。 +S3Queue 引擎为 SELECT 查询提供了一个特殊设置:`commit_on_select`。将其设为 `False` 可以在读取后保留队列中的数据,将其设为 `True` 则会在读取后移除数据。 + ## 描述 {#description} `SELECT` 对于流式导入并不是特别有用(除调试外),因为每个文件只能被导入一次。更实用的做法是使用[物化视图](../../../sql-reference/statements/create/view.md)来创建实时数据流。为此: @@ -385,6 +394,7 @@ SETTINGS SELECT * FROM stats ORDER BY name; ``` + ## 虚拟列 {#virtual-columns} * `_path` — 文件路径。 @@ -416,7 +426,7 @@ SETTINGS * 服务器异常终止。 -2. 在多个服务器上配置了 `S3Queue` 且它们在 zookeeper 中指向同一路径,并使用 `Ordered` 模式时,`s3queue_loading_retries` 将不起作用。该问题很快将得到修复。 +2. 在多个服务器上配置了 `S3Queue` 且它们在 zookeeper 中指向同一路径,并使用 `Ordered` 模式时,`s3queue_loading_retries` 将不会生效。该问题将在后续版本中修复。 ## 自省 {#introspection} @@ -439,7 +449,7 @@ SETTINGS `exception` String ) ENGINE = SystemS3Queue -COMMENT '包含 S3Queue 元数据的内存状态以及每个文件当前处理的行数。' │ +COMMENT 'Contains in-memory state of S3Queue metadata and currently processed rows per file.' │ └────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘ ``` @@ -462,9 +472,9 @@ ProfileEvents: {'ZooKeeperTransactions':3,'ZooKeeperGet':2,'ZooKeeperMul exception: ``` -2. `system.s3queue_log`。持久化表。包含与 `system.s3queue` 相同的信息,但记录的是 `processed` 和 `failed` 文件。 +2. `system.s3queue_log`。持久化表。包含与 `system.s3queue` 相同的信息,但仅针对 `processed` 和 `failed` 状态的文件。 -该表具有以下结构: +该表的结构如下: ```sql SHOW CREATE TABLE system.s3queue_log @@ -492,7 +502,7 @@ SETTINGS index_granularity = 8192 │ └────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘ ``` -要使用 `system.s3queue_log`,需要在服务器配置文件中为其添加相应配置: +要使用 `system.s3queue_log`,需要在服务器配置文件中定义其配置: ```xml diff --git a/i18n/zh/docusaurus-plugin-content-docs/current/interfaces/formats.md b/i18n/zh/docusaurus-plugin-content-docs/current/interfaces/formats.md index f03425fe5b2..b7813b85be0 100644 --- a/i18n/zh/docusaurus-plugin-content-docs/current/interfaces/formats.md +++ b/i18n/zh/docusaurus-plugin-content-docs/current/interfaces/formats.md @@ -9,13 +9,10 @@ doc_type: 'reference' import CloudNotSupportedBadge from '@theme/badges/CloudNotSupportedBadge'; - # 输入和输出数据的格式 {#formats-for-input-and-output-data} ClickHouse 支持大多数已知的文本和二进制数据格式,从而可以轻松集成到几乎任何现有的数据管道中,充分发挥 ClickHouse 的优势。 - - ## 输入格式 {#input-formats} 输入格式用于: @@ -34,22 +31,16 @@ ClickHouse 支持大多数已知的文本和二进制数据格式,从而可以 请阅读完整的[基准分析](https://www.clickhouse.com/blog/clickhouse-input-format-matchup-which-is-fastest-most-efficient)。 要查看完整测试结果,请访问 [FastFormats](https://fastformats.clickhouse.com/) 在线仪表盘。 - - ## 输出格式 {#output-formats} 支持的输出格式用于: - 组织 `SELECT` 查询的结果 - 向以文件为后端的表执行 `INSERT` 操作 - - ## 格式概览 {#formats-overview} 受支持的格式有: - - | 格式 | 输入 | 输出 | | ---------------------------------------------------------------------------------------------------------- | -- | -- | | [TabSeparated](./formats/TabSeparated/TabSeparated.md) | ✔ | ✔ | @@ -139,12 +130,8 @@ ClickHouse 支持大多数已知的文本和二进制数据格式,从而可以 | [Markdown](./formats/Markdown.md) | ✗ | ✔ | | [表单](./formats/Form.md) | ✔ | ✗ | - - 你可以通过 ClickHouse 的设置来控制某些格式处理参数。欲了解更多信息,请参阅[设置](/operations/settings/settings-formats.md)部分。 - - ## 格式模式 {#formatschema} 包含格式模式的文件名由设置 `format_schema` 指定。 @@ -161,8 +148,6 @@ ClickHouse 支持大多数已知的文本和二进制数据格式,从而可以 如果通过 [HTTP 接口](/interfaces/http.md) 进行数据输入或输出,则格式模式中指定的文件名 必须位于服务器配置中由 [format_schema_path](/operations/server-configuration-parameters/settings.md/#format_schema_path) 指定的目录中。 - - ## 跳过错误 {#skippingerrors} 某些格式,例如 `CSV`、`TabSeparated`、`TSKV`、`JSONEachRow`、`Template`、`CustomSeparated` 和 `Protobuf`,在发生解析错误时可以跳过有问题的行,并从下一行的开头继续解析。参见 [input_format_allow_errors_num](/operations/settings/settings-formats.md/#input_format_allow_errors_num) 和 diff --git a/i18n/zh/docusaurus-plugin-content-docs/current/operations/settings/merge-tree-settings.md b/i18n/zh/docusaurus-plugin-content-docs/current/operations/settings/merge-tree-settings.md index c04a5e0018b..927a5958f0d 100644 --- a/i18n/zh/docusaurus-plugin-content-docs/current/operations/settings/merge-tree-settings.md +++ b/i18n/zh/docusaurus-plugin-content-docs/current/operations/settings/merge-tree-settings.md @@ -510,7 +510,7 @@ Dynamic 数据类型的序列化版本,为兼容性所必需。 - + 用于控制 `min_age_to_force_merge_seconds` 和 `min_age_to_force_merge_on_partition_only` 是否遵循 @@ -1262,6 +1262,17 @@ MergeTree 表中 PROJECTION 的最大数量。 控制该逻辑相对于分区中分区片段数量的触发时机。因子越大,响应就越滞后。 +## merge_selector_enable_heuristic_to_lower_max_parts_to_merge_at_once {#merge_selector_enable_heuristic_to_lower_max_parts_to_merge_at_once} + + + + + + + +为 simple merge selector 启用启发式算法,以降低合并选择时的最大限制。 +这将增加并发合并的数量,有助于缓解 TOO_MANY_PARTS 错误,但同时也会提高写放大效应。 + ## merge_selector_enable_heuristic_to_remove_small_parts_at_right {#merge_selector_enable_heuristic_to_remove_small_parts_at_right} diff --git a/i18n/zh/docusaurus-plugin-content-docs/current/operations/settings/settings.md b/i18n/zh/docusaurus-plugin-content-docs/current/operations/settings/settings.md index c22e8b375ba..ea5dc2f8702 100644 --- a/i18n/zh/docusaurus-plugin-content-docs/current/operations/settings/settings.md +++ b/i18n/zh/docusaurus-plugin-content-docs/current/operations/settings/settings.md @@ -10085,6 +10085,15 @@ S3 分块上传的最大分块编号。 在向 S3 执行分段上传时,每个上传分段的最小大小。 +## s3_path_filter_limit {#s3_path_filter_limit} + + + + + +从查询过滤条件中提取 `_path` 值用于文件遍历(替代 glob 列举)的最大数量。 +0 表示禁用。 + ## s3_request_timeout_ms {#s3_request_timeout_ms} @@ -10647,7 +10656,8 @@ SELECT ((4 + 2) + 1, ((4 + 2) + 1) + 2) -允许对 Kafka、RabbitMQ、FileLog、Redis Streams 和 NATS 引擎执行直接 SELECT 查询。如果存在附加的 materialized view,即使启用了此设置,也不允许执行 SELECT 查询。 +允许对 Kafka、RabbitMQ、FileLog、Redis Streams、S3Queue、AzureQueue 和 NATS 引擎执行直接 SELECT 查询。如果存在附加的 materialized view,即使启用了此设置,也不允许执行 SELECT 查询。 +如果没有附加的 materialized view,启用此设置后可以读取数据。请注意,已读取的数据通常会从队列中删除。为避免删除已读取的数据,应正确配置相关引擎的设置。 ## stream_like_engine_insert_queue {#stream_like_engine_insert_queue} diff --git a/i18n/zh/docusaurus-plugin-content-docs/current/operations/system-tables/index.md b/i18n/zh/docusaurus-plugin-content-docs/current/operations/system-tables/index.md index df3491499a7..adbc577d4e6 100644 --- a/i18n/zh/docusaurus-plugin-content-docs/current/operations/system-tables/index.md +++ b/i18n/zh/docusaurus-plugin-content-docs/current/operations/system-tables/index.md @@ -18,119 +18,119 @@ doc_type: 'reference' {/*AUTOGENERATED_START*/ } -| 页面 | 说明 | -| ----------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------- | -| [系统表概览](/operations/system-tables/overview) | 系统表概览:它们是什么以及为何有用。 | -| [INFORMATION_SCHEMA](/operations/system-tables/information_schema) | 提供对数据库对象元数据的几乎标准化、与 DBMS 无关的视图的系统数据库。 | -| [system.asynchronous_insert_log](/operations/system-tables/asynchronous_insert_log) | 包含异步插入相关信息的系统表。每条记录对应一条被缓冲用于异步插入的插入查询。 | -| [system.asynchronous_inserts](/operations/system-tables/asynchronous_inserts) | 包含队列中待处理异步插入信息的系统表。 | -| [system.asynchronous_loader](/operations/system-tables/asynchronous_loader) | 一张系统表,包含最近异步作业(例如正在加载的表)的信息和状态。该表中每个作业对应一行。 | -| [system.asynchronous_metric_log](/operations/system-tables/asynchronous_metric_log) | 包含 `system.asynchronous_metrics` 历史值的系统表,这些值按照时间间隔保存(默认每个时间间隔为一秒) | -| [system.asynchronous_metrics](/operations/system-tables/asynchronous_metrics) | 包含后台定期计算得到的各类指标的系统表,例如当前正在使用的 RAM 量。 | -| [system.azure_queue_settings](/operations/system-tables/azure_queue_settings) | 包含 AzureQueue 表设置相关信息的系统表。从服务器版本 `24.10` 起提供。 | -| [system.backup_log](/operations/system-tables/backup_log) | 包含 `BACKUP` 和 `RESTORE` 操作相关日志条目的系统表。 | -| [system.backups](/operations/system-tables/backups) | 包含有关 `BACKUP` 和 `RESTORE` 操作的日志记录的系统表。 | -| [system.blob_storage_log](/operations/system-tables/blob_storage_log) | 包含日志条目的系统表,用于记录各种 blob 存储操作(如上传和删除)的相关信息。 | -| [system.build_options](/operations/system-tables/build_options) | 包含 ClickHouse 服务器构建选项相关信息的系统表。 | -| [system.clusters](/operations/system-tables/clusters) | 包含配置文件中可用集群及其所定义服务器信息的系统表。 | -| [system.codecs](/operations/system-tables/codecs) | 用于存储队列中编解码器相关信息的系统表。 | -| [system.columns](/operations/system-tables/columns) | 包含所有表的列信息的系统表 | -| [system.contributors](/operations/system-tables/contributors) | 包含贡献者信息的系统表。 | -| [system.crash_log](/operations/system-tables/crash_log) | 用于存储致命错误堆栈跟踪信息的系统表。 | -| [system.current_roles](/operations/system-tables/current_roles) | 包含当前用户已启用角色的系统表。 | -| [system.dashboards](/operations/system-tables/dashboards) | 包含 `/dashboard` 页面所使用的查询,该页面可通过 HTTP 接口访问;这些查询可用于监控和故障排查。 | -| [system.data_skipping_indices](/operations/system-tables/data_skipping_indices) | 用于存储所有表中已存在的数据跳过索引信息的系统表。 | -| [system.data_type_families](/operations/system-tables/data_type_families) | 包含受支持数据类型信息的系统表 | -| [system.database_engines](/operations/system-tables/database_engines) | 包含服务器支持的数据库引擎列表的系统表。 | -| [system.database_replicas](/operations/system-tables/database_replicas) | 包含复制数据库相关信息及其状态的系统表。 | -| [system.databases](/operations/system-tables/databases) | 包含当前用户可访问数据库信息的系统表。 | -| [system.dead_letter_queue](/operations/system-tables/dead_letter_queue) | 包含通过流式引擎接收并在解析时出错的消息信息的系统表。 | -| [system.delta_lake_metadata_log](/operations/system-tables/delta_lake_metadata_log) | 包含从 Delta Lake 表读取的元数据文件信息的系统表。每条记录对应一个根级元数据 JSON 文件。 | -| [system.detached_parts](/operations/system-tables/detached_parts) | 包含 MergeTree 表中已分离分区片段信息的系统表 | -| [system.detached_tables](/operations/system-tables/detached_tables) | 包含每个已分离表相关信息的系统表。 | -| [system.dictionaries](/operations/system-tables/dictionaries) | 包含字典信息的系统表 | -| [system.dimensional_metrics](/operations/system-tables/dimensional_metrics) | 此表包含可即时计算并以 Prometheus 格式导出的维度指标,且始终保持最新。 | -| [system.disks](/operations/system-tables/disks) | 包含在服务器配置中定义的磁盘信息的系统表 | -| [system.distributed_ddl_queue](/operations/system-tables/distributed_ddl_queue) | 包含已在集群上执行的分布式 DDL 查询(使用 ON CLUSTER 子句的查询)信息的系统表。 | -| [system.distribution_queue](/operations/system-tables/distribution_queue) | 包含处于队列中、等待发送到各分片的本地文件信息的系统表。 | -| [system.dns_cache](/operations/system-tables/dns_cache) | 包含已缓存的 DNS 记录信息的系统表。 | -| [system.dropped_tables](/operations/system-tables/dropped_tables) | 包含那些已执行 `DROP TABLE` 但尚未完成数据清理的表信息的系统表 | -| [system.dropped_tables_parts](/operations/system-tables/dropped_tables_parts) | 一个系统表,包含 `system.dropped_tables` 中 MergeTree 已删除表的分区片段相关信息 | -| [system.enabled_roles](/operations/system-tables/enabled_roles) | 系统表,包含当前所有处于激活状态的角色,其中包括当前用户的当前角色,以及授予该角色的其他角色 | -| [system.error_log](/operations/system-tables/system-error-log) | 一个系统表,用于保存 `system.errors` 表中的错误值历史,并会定期刷新到磁盘。 | -| [system.errors](/operations/system-tables/errors) | 记录错误代码及其触发次数的系统表。 | -| [system.events](/operations/system-tables/events) | 包含系统中已发生事件数量信息的系统表。 | -| [system.functions](/operations/system-tables/functions) | 包含普通函数和聚合函数信息的系统表。 | -| [system.grants](/operations/system-tables/grants) | 用于显示授予各 ClickHouse 用户账号的权限的系统表。 | -| [system.graphite_retentions](/operations/system-tables/graphite_retentions) | 包含 `graphite_rollup` 参数信息的系统表,这些参数用于使用 `GraphiteMergeTree` 引擎的表。 | -| [system.histogram_metrics](/operations/system-tables/histogram_metrics) | 该表包含可实时计算并以 Prometheus 格式导出的直方图指标,并且始终保持最新状态。 | -| [system.iceberg_history](/operations/system-tables/iceberg_history) | 系统 Iceberg 快照历史 | -| [system.iceberg_metadata_log](/operations/system-tables/iceberg_metadata_log) | 包含从 Iceberg 表中读取的元数据文件相关信息的系统表。每条记录表示一个根元数据文件、一份从 Avro 文件中提取的元数据,或某个 Avro 文件中的一条记录。 | -| [system.instrumentation](/operations/system-tables/instrumentation) | 包含插桩点的系统表 | -| [system.jemalloc_bins](/operations/system-tables/jemalloc_bins) | 包含通过 jemalloc 内存分配器在不同大小类(bins)上进行的内存分配信息的系统表,这些信息汇总自所有 arena。 | -| [system.kafka_consumers](/operations/system-tables/kafka_consumers) | 包含 Kafka 消费者相关信息的系统表。 | -| [system.licenses](/operations/system-tables/licenses) | 用于存储 ClickHouse 源码中 `contrib` 目录下第三方库许可证信息的系统表。 | -| [system.merge_tree_settings](/operations/system-tables/merge_tree_settings) | 存储 MergeTree 表设置信息的系统表。 | -| [system.merges](/operations/system-tables/merges) | 包含有关当前正在为 MergeTree 系列表执行的合并和数据部件变更操作的信息的系统表。 | -| [system.metric_log](/operations/system-tables/metric_log) | 系统表,用于保存 `system.metrics` 和 `system.events` 表中的指标值历史记录,会定期被刷写到磁盘。 | -| [system.metrics](/operations/system-tables/metrics) | 包含可即时计算或具有当前值的指标的系统表。 | -| [system.moves](/operations/system-tables/moves) | 包含 MergeTree 表正在执行的数据分片移动信息的系统表。每次数据分片移动在表中对应一行记录。 | -| [system.mutations](/operations/system-tables/mutations) | 包含有关 MergeTree 表变更及其进度信息的系统表。每条变更命令对应一行。 | -| [system.numbers](/operations/system-tables/numbers) | 包含一个名为 `number` 的 UInt64 类型列的系统表,其中存储了从零开始的几乎所有自然数。 | -| [system.numbers_mt](/operations/system-tables/numbers_mt) | 类似于 `system.numbers` 的系统表,但读取是并行的,数字可以以任意顺序返回。 | -| [system.one](/operations/system-tables/one) | 包含一行且仅有一个名为 `dummy` 的 UInt8 列(其值为 0)的系统表。类似于其他 DBMS 中的 `DUAL` 表。 | -| [system.opentelemetry_span_log](/operations/system-tables/opentelemetry_span_log) | 存储已执行查询的 trace span 信息的系统表。 | -| [system.part_log](/operations/system-tables/part_log) | 包含有关 MergeTree 系列表中数据分区片段上发生事件信息的系统表,例如数据的新增或合并。 | -| [system.parts](/operations/system-tables/parts) | 包含 MergeTree 分区片段相关信息的系统表 | -| [system.parts_columns](/operations/system-tables/parts_columns) | 包含 MergeTree 表分区片段及列信息的系统表。 | -| [system.processes](/operations/system-tables/processes) | 用于实现 `SHOW PROCESSLIST` 查询的系统表。 | -| [system.processors_profile_log](/operations/system-tables/processors_profile_log) | 包含处理器级性能分析信息的系统表(可在 `EXPLAIN PIPELINE` 中查看) | -| [system.projection_parts](/operations/system-tables/projection_parts) | 用于存储 MergeTree 系列表的投影分区片段信息的系统表。 | -| [system.projection_parts_columns](/operations/system-tables/projection_parts_columns) | 包含 MergeTree 系列表的投影分区片段中各列信息的系统表 | -| [system.projections](/operations/system-tables/projections) | 包含所有表中已定义 PROJECTION 信息的系统表。 | -| [system.query_cache](/operations/system-tables/query_cache) | 显示查询缓存内容的系统表。 | -| [system.query_condition_cache](/operations/system-tables/query_condition_cache) | 显示查询条件缓存内容的系统表。 | -| [system.query_log](/operations/system-tables/query_log) | 包含已执行查询相关信息的系统表,例如开始时间、处理时长、错误消息。 | -| [system.query_metric_log](/operations/system-tables/query_metric_log) | 包含针对单个查询的、来自 `system.events` 表的内存和指标值历史记录的系统表,并会定期将数据刷新到磁盘。 | -| [system.query_thread_log](/operations/system-tables/query_thread_log) | 包含执行查询的线程相关信息的系统表,例如线程名称、线程开始时间以及查询处理的持续时间。 | -| [system.query_views_log](/operations/system-tables/query_views_log) | 在执行查询时包含已执行的依赖视图信息的系统表,例如视图类型或执行时间。 | -| [system.quota_limits](/operations/system-tables/quota_limits) | 包含所有配额各个时间区间最大值信息的系统表。对于一个配额,可以对应任意数量的行,也可以没有行。 | -| [system.quota_usage](/operations/system-tables/quota_usage) | 包含当前用户 QUOTA 使用情况信息的系统表,例如已使用了多少 QUOTA,以及还剩多少 QUOTA。 | -| [system.quotas](/operations/system-tables/quotas) | 包含 QUOTA 相关信息的系统表。 | -| [system.quotas_usage](/operations/system-tables/quotas_usage) | 记录所有用户 QUOTA 使用情况的系统表。 | -| [system.replicas](/operations/system-tables/replicas) | 包含本地服务器上副本表信息及其状态的系统表,可用于监控。 | -| [system.replicated_fetches](/operations/system-tables/replicated_fetches) | 包含当前正在运行的后台获取任务信息的系统表。 | -| [system.replication_queue](/operations/system-tables/replication_queue) | 包含有关 `ReplicatedMergeTree` 系列表在 ClickHouse Keeper 或 ZooKeeper 中的复制队列任务信息的系统表。 | -| [system.resources](/operations/system-tables/resources) | 包含本地服务器上各资源信息的系统表,每个资源占一行。 | -| [system.role_grants](/operations/system-tables/role_grants) | 包含授予用户和角色的角色权限信息的系统表。 | -| [system.roles](/operations/system-tables/roles) | 包含已配置角色信息的系统表。 | -| [system.row_policies](/operations/system-tables/row_policies) | 一个系统表,用于存储针对某个特定表的过滤条件,以及应当使用此 ROW POLICY 的角色和/或用户列表。 | -| [system.s3_queue_settings](/operations/system-tables/s3_queue_settings) | 包含 S3Queue 表设置信息的系统表。自服务器 24.10 版本起可用。 | -| [system.scheduler](/operations/system-tables/scheduler) | 包含本地服务器上各调度节点信息和状态的系统表。 | -| [system.schema_inference_cache](/operations/system-tables/schema_inference_cache) | 包含所有已缓存文件 schema 信息的系统表。 | -| [system.server_settings](/operations/system-tables/server_settings) | 包含在 `config.xml` 中指定的服务器全局设置信息的系统表。 | -| [system.session_log](/operations/system-tables/session_log) | 记录所有登录与登出成功或失败事件信息的系统表。 | -| [system.settings](/operations/system-tables/settings) | 包含当前用户的会话设置信息的系统表。 | -| [system.settings_changes](/operations/system-tables/settings_changes) | 记录先前 ClickHouse 版本中设置变更信息的系统表。 | -| [system.settings_profile_elements](/operations/system-tables/settings_profile_elements) | 用于描述设置配置文件内容的系统表:包括该设置适用的约束、角色和用户,以及父设置配置文件。 | -| [system.settings_profiles](/operations/system-tables/settings_profiles) | 包含已配置设置配置文件各属性的系统表。 | -| [system.stack_trace](/operations/system-tables/stack_trace) | 包含所有服务器线程堆栈跟踪信息的系统表。便于开发者检查服务器状态。 | -| [system.storage_policies](/operations/system-tables/storage_policies) | 包含服务器配置中定义的存储策略和卷信息的系统表。 | -| [system.symbols](/operations/system-tables/symbols) | 这是一个对 C++ 专家和 ClickHouse 工程师有用的系统表,包含用于对 `clickhouse` 可执行文件进行内省的信息。 | -| [system.table_engines](/operations/system-tables/table_engines) | 包含服务器所支持的表引擎及其支持特性的系统表。 | -| [system.tables](/operations/system-tables/tables) | 包含服务器已知的每个表的元数据的系统表。 | -| [system.text_log](/operations/system-tables/text_log) | 用于存储日志记录条目的系统表。 | -| [system.time_zones](/operations/system-tables/time_zones) | 一个系统表,其中包含 ClickHouse 服务器所支持的时区列表。 | -| [system.trace_log](/operations/system-tables/trace_log) | 存储由采样查询分析器收集的堆栈跟踪的系统表。 | -| [system.unicode](/operations/system-tables/unicode) | 包含 Unicode 字符及其属性的系统表。 | -| [system.user_processes](/operations/system-tables/user_processes) | 包含用户内存使用情况和 ProfileEvents 总体概览信息的系统表。 | -| [system.users](/operations/system-tables/users) | 包含服务器上已配置的用户账户列表的系统表。 | -| [system.view_refreshes](/operations/system-tables/view_refreshes) | 包含可刷新materialized view相关信息的系统表。 | -| [system.warnings](/operations/system-tables/system_warnings) | 此表包含关于 ClickHouse 服务器的警告信息。 | -| [system.workloads](/operations/system-tables/workloads) | 用于存储本地服务器上工作负载信息的系统表。 | -| [system.zookeeper](/operations/system-tables/zookeeper) | 仅在配置了 ClickHouse Keeper 或 ZooKeeper 时才存在的系统表。它暴露来自配置中定义的 Keeper 集群的数据。 | -| [system.zookeeper_connection](/operations/system-tables/zookeeper_connection) | 仅在配置了 ZooKeeper 时才存在的系统表。显示当前与 ZooKeeper 的连接(包括辅助 ZooKeeper 实例)。 | -| [system.zookeeper_connection_log](/operations/system-tables/zookeeper_connection_log) | 显示 ZooKeeper 连接历史(包括辅助 ZooKeeper 实例)。 | -| [system.zookeeper_log](/operations/system-tables/zookeeper_log) | 包含有关向 ZooKeeper 服务器发起请求的参数及服务器响应信息的系统表。 | +| 页面 | 说明 | +| ----------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------ | +| [系统表概览](/operations/system-tables/overview) | 系统表概览:介绍系统表是什么以及为什么有用。 | +| [INFORMATION_SCHEMA](/operations/system-tables/information_schema) | 提供一个几乎标准化、与 DBMS 无关的数据库对象元数据视图的系统数据库。 | +| [system.asynchronous_insert_log](/operations/system-tables/asynchronous_insert_log) | 包含异步插入相关信息的系统表。每条记录对应一条被缓冲到异步插入中的插入查询。 | +| [system.asynchronous_inserts](/operations/system-tables/asynchronous_inserts) | 包含队列中待处理异步插入信息的系统表。 | +| [system.asynchronous_loader](/operations/system-tables/asynchronous_loader) | 一张系统表,包含最近异步作业(例如正在加载的表)的信息和状态。该表中每个作业对应一行。 | +| [system.asynchronous_metric_log](/operations/system-tables/asynchronous_metric_log) | 包含 `system.asynchronous_metrics` 历史值的系统表,这些值按照时间间隔保存(默认每个时间间隔为一秒) | +| [system.asynchronous_metrics](/operations/system-tables/asynchronous_metrics) | 包含后台定期计算得到的各类指标的系统表,例如当前正在使用的 RAM 量。 | +| [system.azure_queue_settings](/operations/system-tables/azure_queue_settings) | 包含 AzureQueue 表设置信息的系统表。自服务器 24.10 版本起可用。 | +| [system.backup_log](/operations/system-tables/backup_log) | 包含 `BACKUP` 和 `RESTORE` 操作相关日志条目的系统表。 | +| [system.backups](/operations/system-tables/backups) | 包含 `BACKUP` 和 `RESTORE` 操作相关日志条目的系统表。 | +| [system.blob_storage_log](/operations/system-tables/blob_storage_log) | 包含日志条目的系统表,用于记录各种 blob 存储操作(如上传和删除)的相关信息。 | +| [system.build_options](/operations/system-tables/build_options) | 包含 ClickHouse 服务器构建选项相关信息的系统表。 | +| [system.clusters](/operations/system-tables/clusters) | 包含配置文件中可用集群及其中定义的服务器信息的系统表。 | +| [system.codecs](/operations/system-tables/codecs) | 包含队列中编解码器信息的系统表。 | +| [system.columns](/operations/system-tables/columns) | 包含所有表各列信息的系统表 | +| [system.contributors](/operations/system-tables/contributors) | 包含贡献者信息的系统表。 | +| [system.crash_log](/operations/system-tables/crash_log) | 用于存储致命错误堆栈跟踪信息的系统表。 | +| [system.current_roles](/operations/system-tables/current_roles) | 包含当前用户已启用角色的系统表。 | +| [system.dashboards](/operations/system-tables/dashboards) | 包含 `/dashboard` 页面所使用的查询,该页面可通过 HTTP 接口访问。这些查询可用于监控和故障排查。 | +| [system.data_skipping_indices](/operations/system-tables/data_skipping_indices) | 用于存储所有表中已存在的数据跳过索引信息的系统表。 | +| [system.data_type_families](/operations/system-tables/data_type_families) | 包含受支持数据类型信息的系统表 | +| [system.database_engines](/operations/system-tables/database_engines) | 包含服务器支持的数据库引擎列表的系统表。 | +| [system.database_replicas](/operations/system-tables/database_replicas) | 包含复制型数据库相关信息及其状态的系统表。 | +| [system.databases](/operations/system-tables/databases) | 包含当前用户可用数据库信息的系统表。 | +| [system.dead_letter_queue](/operations/system-tables/dead_letter_queue) | 包含通过流式引擎接收、在解析时发生错误的消息相关信息的系统表。 | +| [system.delta_lake_metadata_log](/operations/system-tables/delta_lake_metadata_log) | 包含从 Delta Lake 表读取的元数据文件信息的系统表。每条记录对应一个根级元数据 JSON 文件。 | +| [system.detached_parts](/operations/system-tables/detached_parts) | 包含 MergeTree 表中已分离的分区片段相关信息的系统表 | +| [system.detached_tables](/operations/system-tables/detached_tables) | 包含每个已分离的表信息的系统表。 | +| [system.dictionaries](/operations/system-tables/dictionaries) | 包含字典信息的系统表 | +| [system.dimensional_metrics](/operations/system-tables/dimensional_metrics) | 该表包含可实时计算并以 Prometheus 格式导出的维度指标,并且始终保持最新状态。 | +| [system.disks](/operations/system-tables/disks) | 包含在服务器配置中定义的磁盘信息的系统表 | +| [system.distributed_ddl_queue](/operations/system-tables/distributed_ddl_queue) | 包含已在集群上执行的分布式 DDL 查询信息的系统表(其中的查询使用 ON CLUSTER 子句)。 | +| [system.distribution_queue](/operations/system-tables/distribution_queue) | 包含队列中待发送到各分片的本地文件信息的系统表。 | +| [system.dns_cache](/operations/system-tables/dns_cache) | 包含已缓存的 DNS 记录信息的系统表。 | +| [system.dropped_tables](/operations/system-tables/dropped_tables) | 包含已执行 `DROP TABLE` 操作但尚未完成数据清理的表相关信息的系统表 | +| [system.dropped_tables_parts](/operations/system-tables/dropped_tables_parts) | 包含 `system.dropped_tables` 中 MergeTree 已删除表分区片段信息的系统表 | +| [system.enabled_roles](/operations/system-tables/enabled_roles) | 系统表,包含当前所有处于激活状态的角色,其中包括当前用户的当前角色,以及授予该角色的其他角色 | +| [system.error_log](/operations/system-tables/system-error-log) | 系统表,用于保存 `system.errors` 表中的错误值历史记录,并会定期被刷写到磁盘。 | +| [system.errors](/operations/system-tables/errors) | 包含错误代码及其触发次数信息的系统表。 | +| [system.events](/operations/system-tables/events) | 包含系统中各类事件发生次数信息的系统表。 | +| [system.functions](/operations/system-tables/functions) | 包含普通函数和聚合函数信息的系统表。 | +| [system.grants](/operations/system-tables/grants) | 用于显示授予各 ClickHouse 用户账号的权限的系统表。 | +| [system.graphite_retentions](/operations/system-tables/graphite_retentions) | 包含 `graphite_rollup` 参数信息的系统表,这些参数用于 `GraphiteMergeTree` 类型引擎的表中。 | +| [system.histogram_metrics](/operations/system-tables/histogram_metrics) | 此表包含可即时计算并以 Prometheus 格式导出的直方图指标,且始终保持最新。 | +| [system.iceberg_history](/operations/system-tables/iceberg_history) | 系统 Iceberg 快照历史记录 | +| [system.iceberg_metadata_log](/operations/system-tables/iceberg_metadata_log) | 包含从 Iceberg 表中读取的元数据文件相关信息的系统表。每条记录表示一个根级元数据文件、一份从 Avro 文件中提取的元数据,或某个 Avro 文件中的一个条目。 | +| [system.instrumentation](/operations/system-tables/instrumentation) | 包含插桩点信息的系统表 | +| [system.jemalloc_bins](/operations/system-tables/jemalloc_bins) | 包含通过 jemalloc 内存分配器在不同大小类别(bins)的内存分配信息的系统表,这些信息汇总自所有 arena。 | +| [system.kafka_consumers](/operations/system-tables/kafka_consumers) | 包含 Kafka 消费者相关信息的系统表。 | +| [system.licenses](/operations/system-tables/licenses) | 用于存储 ClickHouse 源码中 `contrib` 目录下第三方库许可证信息的系统表。 | +| [system.merge_tree_settings](/operations/system-tables/merge_tree_settings) | 存储 MergeTree 表设置信息的系统表。 | +| [system.merges](/operations/system-tables/merges) | 包含当前正在进行的 MergeTree 系列表数据分片合并和分片变更操作相关信息的系统表。 | +| [system.metric_log](/operations/system-tables/metric_log) | 系统表,用于保存 `system.metrics` 和 `system.events` 表中的指标值历史,并会定期刷新到磁盘。 | +| [system.metrics](/operations/system-tables/metrics) | 包含可即时计算或反映当前值的指标的系统表。 | +| [system.moves](/operations/system-tables/moves) | 包含 MergeTree 表正在执行的数据部件移动信息的系统表。每次数据部件移动在表中对应一行记录。 | +| [system.mutations](/operations/system-tables/mutations) | 包含 MergeTree 表变更及其执行进度信息的系统表。每条变更命令在表中对应一行。 | +| [system.numbers](/operations/system-tables/numbers) | 仅包含一个名为 `number` 的 UInt64 列的系统表,其中存储了从零开始的几乎所有自然数。 | +| [system.numbers_mt](/operations/system-tables/numbers_mt) | 类似于 `system.numbers` 的系统表,但读取操作是并行执行的,数字可以以任意顺序返回。 | +| [system.one](/operations/system-tables/one) | 包含一行数据且仅有一个名为 `dummy`、值为 0 的 UInt8 列的系统表。类似于其他 DBMS 中的 `DUAL` 表。 | +| [system.opentelemetry_span_log](/operations/system-tables/opentelemetry_span_log) | 存储已执行查询的 trace span 信息的系统表。 | +| [system.part_log](/operations/system-tables/part_log) | 包含有关 MergeTree 系列表中数据分区片段相关事件信息的系统表,例如数据的新增或合并。 | +| [system.parts](/operations/system-tables/parts) | 包含 MergeTree 表分区片段相关信息的系统表 | +| [system.parts_columns](/operations/system-tables/parts_columns) | 包含 MergeTree 表分区片段及列相关信息的系统表。 | +| [system.processes](/operations/system-tables/processes) | 用于实现 `SHOW PROCESSLIST` 查询的系统表。 | +| [system.processors_profile_log](/operations/system-tables/processors_profile_log) | 包含处理器级别性能分析信息的系统表(可通过 `EXPLAIN PIPELINE` 查看) | +| [system.projection_parts](/operations/system-tables/projection_parts) | 包含 MergeTree 系列表投影分区片段信息的系统表。 | +| [system.projection_parts_columns](/operations/system-tables/projection_parts_columns) | 包含 MergeTree 系列表投影分区片段中列信息的系统表 | +| [system.projections](/operations/system-tables/projections) | 包含所有表中已存在 PROJECTION 信息的系统表。 | +| [system.query_cache](/operations/system-tables/query_cache) | 显示查询缓存内容的系统表。 | +| [system.query_condition_cache](/operations/system-tables/query_condition_cache) | 显示查询条件缓存内容的系统表。 | +| [system.query_log](/operations/system-tables/query_log) | 包含已执行查询相关信息的系统表,例如开始时间、处理时长、错误消息。 | +| [system.query_metric_log](/operations/system-tables/query_metric_log) | 包含针对单个查询的、来自 `system.events` 表的内存和指标值历史记录的系统表,并会定期将数据刷写到磁盘。 | +| [system.query_thread_log](/operations/system-tables/query_thread_log) | 包含执行查询的线程相关信息的系统表,例如线程名称、线程开始时间以及查询处理的持续时间。 | +| [system.query_views_log](/operations/system-tables/query_views_log) | 包含在执行查询时被执行的依赖视图信息的系统表,例如视图类型或执行时间。 | +| [system.quota_limits](/operations/system-tables/quota_limits) | 包含所有配额在各个时间区间最大值信息的系统表。对于一个配额,可以对应任意数量的行,也可以没有行。 | +| [system.quota_usage](/operations/system-tables/quota_usage) | 包含当前用户 QUOTA 使用情况信息的系统表,例如已使用了多少 QUOTA,以及还剩多少 QUOTA。 | +| [system.quotas](/operations/system-tables/quotas) | 包含 QUOTA 相关信息的系统表。 | +| [system.quotas_usage](/operations/system-tables/quotas_usage) | 包含所有用户 QUOTA 使用情况信息的系统表。 | +| [system.replicas](/operations/system-tables/replicas) | 包含本地服务器上复制表信息及其状态的系统表,可用于监控。 | +| [system.replicated_fetches](/operations/system-tables/replicated_fetches) | 包含当前正在运行的后台拉取任务信息的系统表。 | +| [system.replication_queue](/operations/system-tables/replication_queue) | 包含 `ReplicatedMergeTree` 系列表在 ClickHouse Keeper 或 ZooKeeper 中存储的复制队列任务信息的系统表。 | +| [system.resources](/operations/system-tables/resources) | 包含本地服务器上各资源信息的系统表,每个资源对应一行。 | +| [system.role_grants](/operations/system-tables/role_grants) | 包含授予用户和角色的角色授权信息的系统表。 | +| [system.roles](/operations/system-tables/roles) | 包含已配置角色信息的系统表。 | +| [system.row_policies](/operations/system-tables/row_policies) | 一个系统表,用于存储针对某个特定表的过滤条件,以及应使用此 ROW POLICY 的角色和/或用户列表。 | +| [system.s3_queue_settings](/operations/system-tables/s3_queue_settings) | 包含 S3Queue 表设置信息的系统表。自服务器 24.10 版本起可用。 | +| [system.scheduler](/operations/system-tables/scheduler) | 包含本地服务器上各调度节点的信息和状态的系统表。 | +| [system.schema_inference_cache](/operations/system-tables/schema_inference_cache) | 包含所有已缓存文件的 schema 信息的系统表。 | +| [system.server_settings](/operations/system-tables/server_settings) | 包含在 `config.xml` 中指定的服务器全局设置信息的系统表。 | +| [system.session_log](/operations/system-tables/session_log) | 包含所有成功和失败的登录与登出事件信息的系统表。 | +| [system.settings](/operations/system-tables/settings) | 包含当前用户的会话设置信息的系统表。 | +| [system.settings_changes](/operations/system-tables/settings_changes) | 记录历史 ClickHouse 版本中设置变更信息的系统表。 | +| [system.settings_profile_elements](/operations/system-tables/settings_profile_elements) | 用于描述设置配置文件内容的系统表:包括该设置所适用的约束、角色和用户,以及父设置配置文件。 | +| [system.settings_profiles](/operations/system-tables/settings_profiles) | 包含已配置设置配置文件属性信息的系统表。 | +| [system.stack_trace](/operations/system-tables/stack_trace) | 包含所有服务器线程堆栈跟踪信息的系统表。便于开发者检查服务器状态。 | +| [system.storage_policies](/operations/system-tables/storage_policies) | 包含服务器配置中定义的存储策略和卷信息的系统表。 | +| [system.symbols](/operations/system-tables/symbols) | 对 C++ 专家和 ClickHouse 工程师有用的系统表,包含用于自省 `clickhouse` 二进制文件的信息。 | +| [system.table_engines](/operations/system-tables/table_engines) | 包含服务器所支持的表引擎及其支持功能说明的系统表。 | +| [system.tables](/operations/system-tables/tables) | 包含服务器已知各表元数据的系统表。 | +| [system.text_log](/operations/system-tables/text_log) | 用于存储日志记录条目的系统表。 | +| [system.time_zones](/operations/system-tables/time_zones) | 包含 ClickHouse 服务器所支持时区列表的系统表。 | +| [system.trace_log](/operations/system-tables/trace_log) | 包含由采样查询分析器收集的堆栈跟踪信息的系统表。 | +| [system.unicode](/operations/system-tables/unicode) | 包含 Unicode 字符列表及其属性的系统表。 | +| [system.user_processes](/operations/system-tables/user_processes) | 用于概览用户内存使用情况和 ProfileEvents 信息的系统表。 | +| [system.users](/operations/system-tables/users) | 包含服务器上已配置的用户账户列表的系统表。 | +| [system.view_refreshes](/operations/system-tables/view_refreshes) | 包含可刷新 materialized view 相关信息的系统表。 | +| [system.warnings](/operations/system-tables/system_warnings) | 此表包含关于 ClickHouse 服务器的警告信息。 | +| [system.workloads](/operations/system-tables/workloads) | 包含本地服务器上各工作负载信息的系统表。 | +| [system.zookeeper_log](/operations/system-tables/zookeeper_log) | 包含有关向 ZooKeeper 服务器发起请求的参数及其响应信息的系统表。 | +| [system.zookeeper](/operations/system-tables/zookeeper) | 仅在配置了 ClickHouse Keeper 或 ZooKeeper 时才存在的系统表。它提供对配置中定义的 Keeper 集群数据的访问。 | +| [system.zookeeper_connection](/operations/system-tables/zookeeper_connection) | 仅在配置了 ZooKeeper 时才存在的系统表。显示当前与 ZooKeeper 的连接(包括辅助 ZooKeeper 实例)。 | +| [system.zookeeper_connection_log](/operations/system-tables/zookeeper_connection_log) | 显示 ZooKeeper 连接的历史记录(包括辅助 ZooKeeper 实例)。 | {/*AUTOGENERATED_END*/ } diff --git a/i18n/zh/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/intervalLengthSum.md b/i18n/zh/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/intervalLengthSum.md index 1b9878f3a08..a677080f461 100644 --- a/i18n/zh/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/intervalLengthSum.md +++ b/i18n/zh/docusaurus-plugin-content-docs/current/sql-reference/aggregate-functions/reference/intervalLengthSum.md @@ -86,7 +86,6 @@ SELECT id, intervalLengthSum(start, end), toTypeName(intervalLengthSum(start, en 3. 输入表: - ```text ┌─id─┬──────开始─┬────────结束─┐ │ a │ 2020-01-01 │ 2020-01-04 │ diff --git a/i18n/zh/docusaurus-plugin-content-docs/current/sql-reference/dictionaries/index.md b/i18n/zh/docusaurus-plugin-content-docs/current/sql-reference/dictionaries/index.md index 1c4241e5ed9..bb6e65d6c84 100644 --- a/i18n/zh/docusaurus-plugin-content-docs/current/sql-reference/dictionaries/index.md +++ b/i18n/zh/docusaurus-plugin-content-docs/current/sql-reference/dictionaries/index.md @@ -10,6 +10,8 @@ doc_type: 'reference' import SelfManaged from '@site/i18n/zh/docusaurus-plugin-content-docs/current/_snippets/_self_managed_only_no_roadmap.md'; import CloudDetails from '@site/i18n/zh/docusaurus-plugin-content-docs/current/sql-reference/dictionaries/_snippet_dictionary_in_cloud.md'; import CloudNotSupportedBadge from '@theme/badges/CloudNotSupportedBadge'; +import ExperimentalBadge from '@theme/badges/ExperimentalBadge'; + # 字典 {#dictionaries} @@ -1052,7 +1054,7 @@ SOURCE(CLICKHOUSE(... update_field 'added_time' update_lag 15)) ... - + ... @@ -1066,7 +1068,7 @@ SOURCE(CLICKHOUSE(... update_field 'added_time' update_lag 15)) ```sql CREATE DICTIONARY dict_name (...) ... -SOURCE(SOURCE_TYPE(param1 val1 ... paramN valN)) -- 数据源配置 +SOURCE(SOURCE_TYPE(param1 val1 ... paramN valN)) -- Source configuration ... ``` @@ -1107,6 +1109,8 @@ SETTINGS(format_csv_allow_single_quotes = 0) * [Redis](#redis) * [Cassandra](#cassandra) * [PostgreSQL](#postgresql) + * [YTsaurus](#ytsaurus) + ### 本地文件 {#local-file} @@ -1891,6 +1895,48 @@ SOURCE(POSTGRESQL( `table` 或 `where` 字段不能与 `query` 字段同时使用。同时,`table` 和 `query` 字段中必须至少声明一个。 ::: +### YTsaurus {#ytsaurus} + + + + + +:::info +这是一个实验性特性,将来版本中可能会发生不向后兼容的变更。 +通过设置 [`allow_experimental_ytsaurus_dictionary_source`](/operations/settings/settings#allow_experimental_ytsaurus_dictionary_source) +来启用 YTsaurus 字典源。 +::: + +设置示例: + +```xml + + + http://localhost:8000 + //tmp/test + password + 1 + + +``` + +或 + +```sql +SOURCE(YTSAURUS( + http_proxy_urls 'http://localhost:8000' + cypress_path '//tmp/test' + oauth_token 'password' +)) +``` + +设置字段: + +* `http_proxy_urls` – 指向 YTsaurus HTTP 代理的 URL。 +* `cypress_path` – 指向表数据源的 Cypress 路径。 +* `oauth_token` – OAuth 令牌。 + + ### Null {#null} 一种特殊的数据源,可用于创建占位(空)字典。此类字典在测试场景中,或在数据节点与查询节点分离且这些节点上使用分布式表的环境中会很有用。 diff --git a/i18n/zh/docusaurus-plugin-content-docs/current/sql-reference/statements/select/offset.md b/i18n/zh/docusaurus-plugin-content-docs/current/sql-reference/statements/select/offset.md index 00fa64d0e2f..b803f8990c2 100644 --- a/i18n/zh/docusaurus-plugin-content-docs/current/sql-reference/statements/select/offset.md +++ b/i18n/zh/docusaurus-plugin-content-docs/current/sql-reference/statements/select/offset.md @@ -9,7 +9,11 @@ doc_type: 'reference' `OFFSET` 和 `FETCH` 可用于按批次检索数据。它们用于指定希望通过单条查询获取的一段行数据。 ```sql -OFFSET offset_row_count {ROW | ROWS}] [FETCH {FIRST | NEXT} fetch_row_count {ROW | ROWS} {ONLY | WITH TIES}] +-- SQL Standard style: +[OFFSET offset_row_count {ROW | ROWS}] [FETCH {FIRST | NEXT} fetch_row_count {ROW | ROWS} {ONLY | WITH TIES}] + +-- MySQL/PostgreSQL style: +[LIMIT [n, ]m] [OFFSET offset_row_count] ``` `offset_row_count` 或 `fetch_row_count` 的值可以是数字或字面常量。可以省略 `fetch_row_count`;默认情况下,它为 1。 @@ -35,7 +39,7 @@ OFFSET offset_row_count {ROW | ROWS}] [FETCH {FIRST | NEXT} fetch_row_count {ROW SELECT * FROM test_fetch ORDER BY a OFFSET 1 ROW FETCH FIRST 3 ROWS ONLY; ``` -与该查询完全一致 +与下列查询完全等价 ```sql SELECT * FROM test_fetch ORDER BY a LIMIT 3 OFFSET 1; @@ -67,7 +71,7 @@ SELECT * FROM test_fetch ORDER BY a LIMIT 3 OFFSET 1; └───┴───┘ ``` -`ONLY` 选项的使用方法: +`ONLY` 选项的用法: ```sql SELECT * FROM test_fetch ORDER BY a OFFSET 3 ROW FETCH FIRST 3 ROWS ONLY; diff --git a/i18n/zh/docusaurus-plugin-content-docs/current/use-cases/observability/clickstack/deployment/docker-compose.md b/i18n/zh/docusaurus-plugin-content-docs/current/use-cases/observability/clickstack/deployment/docker-compose.md index d0b531f16e0..fa6d5eb70ff 100644 --- a/i18n/zh/docusaurus-plugin-content-docs/current/use-cases/observability/clickstack/deployment/docker-compose.md +++ b/i18n/zh/docusaurus-plugin-content-docs/current/use-cases/observability/clickstack/deployment/docker-compose.md @@ -48,10 +48,10 @@ import JSONSupport from '@site/i18n/zh/docusaurus-plugin-content-docs/current/us ### 克隆仓库 {#clone-the-repo} -要使用 Docker Compose 进行部署,先克隆 HyperDX 仓库,进入该目录并运行 `docker-compose up`: +要使用 Docker Compose 进行部署,先克隆 ClickStack 仓库,进入该目录并运行 `docker-compose up`: ```shell -git clone git@github.com:hyperdxio/hyperdx.git +git clone https://github.com/ClickHouse/ClickStack.git docker compose up ``` @@ -61,7 +61,7 @@ docker compose up 创建一个用户,并提供满足要求的用户名和密码。 -点击 `Create` 后,会为通过 Helm 图表部署的 ClickHouse 实例自动创建数据源。 +点击 `Create` 后,会为通过 Docker Compose 部署的 ClickHouse 实例自动创建数据源。 :::note 覆盖默认连接 您可以替换到集成 ClickHouse 实例的默认连接。有关详细信息,请参阅 ["Using ClickHouse Cloud"](#using-clickhouse-cloud)。 @@ -88,34 +88,31 @@ docker compose up 用户可以通过环境变量文件来修改该栈的设置,例如使用的版本。 ```shell -user@example-host hyperdx % cat .env -# 供 docker-compose.yml 使用 {#used-by-docker-composeyml} -# 供 docker-compose.yml 使用 {#used-by-docker-composeyml} -HDX_IMAGE_REPO=docker.hyperdx.io -IMAGE_NAME=ghcr.io/hyperdxio/hyperdx -IMAGE_NAME_DOCKERHUB=hyperdx/hyperdx -LOCAL_IMAGE_NAME=ghcr.io/hyperdxio/hyperdx-local -LOCAL_IMAGE_NAME_DOCKERHUB=hyperdx/hyperdx-local -ALL_IN_ONE_IMAGE_NAME=ghcr.io/hyperdxio/hyperdx-all-in-one -ALL_IN_ONE_IMAGE_NAME_DOCKERHUB=hyperdx/hyperdx-all-in-one -OTEL_COLLECTOR_IMAGE_NAME=ghcr.io/hyperdxio/hyperdx-otel-collector -OTEL_COLLECTOR_IMAGE_NAME_DOCKERHUB=hyperdx/hyperdx-otel-collector -CODE_VERSION=2.0.0-beta.16 -IMAGE_VERSION_SUB_TAG=.16 -IMAGE_VERSION=2-beta +user@example-host clickstack % cat .env + +# Used by docker-compose.yml +IMAGE_NAME_DOCKERHUB=clickhouse/clickstack-all-in-one +LOCAL_IMAGE_NAME_DOCKERHUB=clickhouse/clickstack-local +ALL_IN_ONE_IMAGE_NAME_DOCKERHUB=clickhouse/clickstack-all-in-one +OTEL_COLLECTOR_IMAGE_NAME_DOCKERHUB=clickhouse/clickstack-otel-collector +CODE_VERSION=2.8.0 +IMAGE_VERSION_SUB_TAG=.8.0 +IMAGE_VERSION=2 IMAGE_NIGHTLY_TAG=2-nightly +IMAGE_LATEST_TAG=latest -# 配置域名 URL {#set-up-domain-urls} -HYPERDX_API_PORT=8000 # 可选(不应被其他服务占用) +# Set up domain URLs +HYPERDX_API_PORT=8000 #optional (should not be taken by other services) HYPERDX_APP_PORT=8080 HYPERDX_APP_URL=http://localhost HYPERDX_LOG_LEVEL=debug HYPERDX_OPAMP_PORT=4320 -# OTel/ClickHouse 配置 {#otelclickhouse-config} +# Otel/Clickhouse config HYPERDX_OTEL_EXPORTER_CLICKHOUSE_DATABASE=default ``` + ### 配置 OpenTelemetry collector {#configuring-collector} 如有需要,可以修改 OTel collector 的配置——请参阅[“修改配置”](/use-cases/observability/clickstack/ingesting-data/otel-collector#modifying-otel-collector-configuration)。 @@ -124,13 +121,13 @@ HYPERDX_OTEL_EXPORTER_CLICKHOUSE_DATABASE=default 此发行版可以与 ClickHouse Cloud 一起使用。用户应当: -* 从 `docker-compose.yaml` 文件中移除 ClickHouse 服务。如果只是测试,这一步是可选的,因为已部署的 ClickHouse 实例只是会被忽略——不过仍会占用本地资源。如果移除该服务,请确保同时移除对该服务的所有引用,例如 `depends_on`。 +* 从 `docker-compose.yml` 文件中移除 ClickHouse 服务。如果只是测试,这一步是可选的,因为已部署的 ClickHouse 实例只是会被忽略——不过仍会占用本地资源。如果移除该服务,请确保同时移除对该服务的所有引用,例如 `depends_on`。 * 通过在 Compose 文件中设置环境变量 `CLICKHOUSE_ENDPOINT`、`CLICKHOUSE_USER` 和 `CLICKHOUSE_PASSWORD`,修改 OTel collector 以使用 ClickHouse Cloud 实例。具体来说,将这些环境变量添加到 OTel collector 服务中: ```shell otel-collector: - image: ${OTEL_COLLECTOR_IMAGE_NAME}:${IMAGE_VERSION} + image: ${OTEL_COLLECTOR_IMAGE_NAME_DOCKERHUB}:${IMAGE_VERSION} environment: CLICKHOUSE_ENDPOINT: '' # https endpoint here CLICKHOUSE_USER: '' @@ -155,25 +152,25 @@ HYPERDX_OTEL_EXPORTER_CLICKHOUSE_DATABASE=default -要进行这些设置,请修改 `docker-compose.yaml` 中相关的服务: +要进行这些设置,请修改 `docker-compose.yml` 中相关的服务: ```yaml app: - image: ${HDX_IMAGE_REPO}/${IMAGE_NAME_DOCKERHUB}:${IMAGE_VERSION} + image: ${IMAGE_NAME_DOCKERHUB}:${IMAGE_VERSION} ports: - ${HYPERDX_API_PORT}:${HYPERDX_API_PORT} - ${HYPERDX_APP_PORT}:${HYPERDX_APP_PORT} environment: - BETA_CH_OTEL_JSON_SCHEMA_ENABLED: true # 启用 JSON + BETA_CH_OTEL_JSON_SCHEMA_ENABLED: true # enable JSON FRONTEND_URL: ${HYPERDX_APP_URL}:${HYPERDX_APP_PORT} HYPERDX_API_KEY: ${HYPERDX_API_KEY} HYPERDX_API_PORT: ${HYPERDX_API_PORT} - # 为简洁起见省略部分内容 + # truncated for brevity otel-collector: - image: ${HDX_IMAGE_REPO}/${OTEL_COLLECTOR_IMAGE_NAME_DOCKERHUB}:${IMAGE_VERSION} + image: ${OTEL_COLLECTOR_IMAGE_NAME_DOCKERHUB}:${IMAGE_VERSION} environment: - OTEL_AGENT_FEATURE_GATE_ARG: '--feature-gates=clickhouse.json' # 启用 JSON + OTEL_AGENT_FEATURE_GATE_ARG: '--feature-gates=clickhouse.json' # enable JSON CLICKHOUSE_ENDPOINT: 'tcp://ch-server:9000?dial_timeout=10s' - # 为简洁起见省略部分内容 + # truncated for brevity ```