Fail shards early when we can detect a type missmatch #79869
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not-napoleon
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elasticmachine
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csoulios
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Nov 9, 2021
| @@ -1368,3 +1368,67 @@ huge size: | |||
| - match: { aggregations.str_terms.buckets.1.doc_count: 2 } | |||
| - match: { aggregations.str_terms.buckets.2.key: c } | |||
| - match: { aggregations.str_terms.buckets.2.doc_count: 3 } | |||
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|
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| --- | |||
| Value type missmatch fails shard: | |||
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Typo: mismatch (not missmatch)
| field: ip | ||
| value_type: ip | ||
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| - match: { _shards.failed: 1 } |
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I think this is a special case of the problem, because valuetype_test_1 contains no documents. Wouldn't it be ok to silently skip its shards instead of failing them?
Also, would it make sense to add a test where the index may contain documents?
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So, there are two problems with silently skipping shards that don't have docs that I can think of. First, we don't know that until later in the process, and by that time we don't have an obvious way to check if we have a conflict. So we'd need to carry some "has type conflict" flag and fail if that's true and we have docs. Seems clunky. It also adds some leniency and unpredictability. If the query changes to include docs on those shards, now the aggregation starts failing. Seems confusing.
Furthermore, if there are no matching docs on the shard, failing it doesn't change the results. It just lets the user know there's a potential problem. More information is better.
And, finally, yes, it makes sense to add a test with docs in both indices. Will push one up shortly. Thanks!
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@elasticmachine run elasticsearch-ci/part-2 |
weizijun
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Nov 30, 2021
* upstream/master: (150 commits) Fix ComposableIndexTemplate equals when composed_of is null (elastic#80864) Optimize DLS bitset building for matchAll query (elastic#81030) URL option for BaseRunAsSuperuserCommand (elastic#81025) Less Verbose Serialization of Snapshot Failure in SLM Metadata (elastic#80942) Fix shadowed vars pt7 (elastic#80996) Fail shards early when we can detect a type missmatch (elastic#79869) Delegate Ref Counting to ByteBuf in Netty Transport (elastic#81096) Clarify `unassigned.reason` docs (elastic#81017) Strip blocks from settings for reindex targets (elastic#80887) Split off the values supplier for ScriptDocValues (elastic#80635) [ML] Switch message and detail for model snapshot deprecations (elastic#81108) [DOCS] Update xrefs for snapshot restore docs (elastic#81023) [ML] Updates visiblity of validate API (elastic#81061) Track histogram of transport handling times (elastic#80581) [ML] Fix datafeed preview with remote indices (elastic#81099) [ML] Fix acceptable model snapshot versions in ML deprecation checker (elastic#81060) [ML] Add logging for failing PyTorch test (elastic#81044) Extending the timeout waiting for snapshot to be ready (elastic#81018) [ML] Fix incorrect logging of unexpected model size error (elastic#81089) [ML] Make inference timeout test more reliable (elastic#81094) ... # Conflicts: # server/src/main/java/org/elasticsearch/index/mapper/NumberFieldMapper.java
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* upstream/master: (55 commits) Fix ComposableIndexTemplate equals when composed_of is null (elastic#80864) Optimize DLS bitset building for matchAll query (elastic#81030) URL option for BaseRunAsSuperuserCommand (elastic#81025) Less Verbose Serialization of Snapshot Failure in SLM Metadata (elastic#80942) Fix shadowed vars pt7 (elastic#80996) Fail shards early when we can detect a type missmatch (elastic#79869) Delegate Ref Counting to ByteBuf in Netty Transport (elastic#81096) Clarify `unassigned.reason` docs (elastic#81017) Strip blocks from settings for reindex targets (elastic#80887) Split off the values supplier for ScriptDocValues (elastic#80635) [ML] Switch message and detail for model snapshot deprecations (elastic#81108) [DOCS] Update xrefs for snapshot restore docs (elastic#81023) [ML] Updates visiblity of validate API (elastic#81061) Track histogram of transport handling times (elastic#80581) [ML] Fix datafeed preview with remote indices (elastic#81099) [ML] Fix acceptable model snapshot versions in ML deprecation checker (elastic#81060) [ML] Add logging for failing PyTorch test (elastic#81044) Extending the timeout waiting for snapshot to be ready (elastic#81018) [ML] Fix incorrect logging of unexpected model size error (elastic#81089) [ML] Make inference timeout test more reliable (elastic#81094) ...
weizijun
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Nov 30, 2021
* upstream/master: (55 commits) Fix ComposableIndexTemplate equals when composed_of is null (elastic#80864) Optimize DLS bitset building for matchAll query (elastic#81030) URL option for BaseRunAsSuperuserCommand (elastic#81025) Less Verbose Serialization of Snapshot Failure in SLM Metadata (elastic#80942) Fix shadowed vars pt7 (elastic#80996) Fail shards early when we can detect a type missmatch (elastic#79869) Delegate Ref Counting to ByteBuf in Netty Transport (elastic#81096) Clarify `unassigned.reason` docs (elastic#81017) Strip blocks from settings for reindex targets (elastic#80887) Split off the values supplier for ScriptDocValues (elastic#80635) [ML] Switch message and detail for model snapshot deprecations (elastic#81108) [DOCS] Update xrefs for snapshot restore docs (elastic#81023) [ML] Updates visiblity of validate API (elastic#81061) Track histogram of transport handling times (elastic#80581) [ML] Fix datafeed preview with remote indices (elastic#81099) [ML] Fix acceptable model snapshot versions in ML deprecation checker (elastic#81060) [ML] Add logging for failing PyTorch test (elastic#81044) Extending the timeout waiting for snapshot to be ready (elastic#81018) [ML] Fix incorrect logging of unexpected model size error (elastic#81089) [ML] Make inference timeout test more reliable (elastic#81094) ...
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Resolves #72276
Generally speaking, we can't detect field type mismatches between different shards until reduce time, which then causes us to fail the whole aggregation. There is an exception though when the user has specified a value type. Since the value type gets pushed out to all the shards, we can detect on the shard if the field type doesn't match the specified value type, and fail only that shard allowing for a partial result on the aggregation. In the case where the user supplies a script as well, we don't fail the shard, because it's possible the script changes the type (this was a pattern before runtime fields)