Add local metadata caching

awswrangler/_config.py

@@ -29,6 +29,8 @@ class _ConfigArg(NamedTuple):
     "database": _ConfigArg(dtype=str, nullable=True),
     "max_cache_query_inspections": _ConfigArg(dtype=int, nullable=False),
     "max_cache_seconds": _ConfigArg(dtype=int, nullable=False),
+    "max_remote_cache_entries": _ConfigArg(dtype=int, nullable=False),
+    "max_local_cache_entries": _ConfigArg(dtype=int, nullable=False),
     "s3_block_size": _ConfigArg(dtype=int, nullable=False, enforced=True),
     "workgroup": _ConfigArg(dtype=str, nullable=False, enforced=True),
     # Endpoints URLs
@@ -226,6 +228,35 @@ def max_cache_seconds(self) -> int:
     def max_cache_seconds(self, value: int) -> None:
         self._set_config_value(key="max_cache_seconds", value=value)
 
+    @property
+    def max_local_cache_entries(self) -> int:
+        """Property max_local_cache_entries."""
+        return cast(int, self["max_local_cache_entries"])
+
+    @max_local_cache_entries.setter
+    def max_local_cache_entries(self, value: int) -> None:
+        try:
+            max_remote_cache_entries = cast(int, self["max_remote_cache_entries"])
+        except AttributeError:
+            max_remote_cache_entries = 50
+        if value < max_remote_cache_entries:
+            _logger.warning(
+                "max_remote_cache_entries shouldn't be greater than max_local_cache_entries. "
+                "Therefore max_remote_cache_entries will be set to %s as well.",
+                value,
+            )
+            self._set_config_value(key="max_remote_cache_entries", value=value)
+        self._set_config_value(key="max_local_cache_entries", value=value)
+
+    @property
+    def max_remote_cache_entries(self) -> int:
+        """Property max_remote_cache_entries."""
+        return cast(int, self["max_remote_cache_entries"])
+
+    @max_remote_cache_entries.setter
+    def max_remote_cache_entries(self, value: int) -> None:
+        self._set_config_value(key="max_remote_cache_entries", value=value)
+
     @property
     def s3_block_size(self) -> int:
         """Property s3_block_size."""

awswrangler/athena/_read.py

@@ -20,6 +20,7 @@
     _get_query_metadata,
     _get_s3_output,
     _get_workgroup_config,
+    _LocalMetadataCacheManager,
     _QueryMetadata,
     _start_query_execution,
     _WorkGroupConfig,
@@ -96,33 +97,37 @@ def _compare_query_string(sql: str, other: str) -> bool:
     return False
 
 
-def _get_last_query_executions(
-    boto3_session: Optional[boto3.Session] = None, workgroup: Optional[str] = None
-) -> Iterator[List[Dict[str, Any]]]:
+def _get_last_query_infos(
+    max_remote_cache_entries: int,
+    boto3_session: Optional[boto3.Session] = None,
+    workgroup: Optional[str] = None,
+) -> List[Dict[str, Any]]:
     """Return an iterator of `query_execution_info`s run by the workgroup in Athena."""
     client_athena: boto3.client = _utils.client(service_name="athena", session=boto3_session)
-    args: Dict[str, Union[str, Dict[str, int]]] = {"PaginationConfig": {"MaxItems": 50, "PageSize": 50}}
+    page_size = 50
+    args: Dict[str, Union[str, Dict[str, int]]] = {
+        "PaginationConfig": {"MaxItems": max_remote_cache_entries, "PageSize": page_size}
+    }
     if workgroup is not None:
         args["WorkGroup"] = workgroup
     paginator = client_athena.get_paginator("list_query_executions")
+    uncached_ids = []
     for page in paginator.paginate(**args):
         _logger.debug("paginating Athena's queries history...")
         query_execution_id_list: List[str] = page["QueryExecutionIds"]
-        execution_data = client_athena.batch_get_query_execution(QueryExecutionIds=query_execution_id_list)
-        yield execution_data.get("QueryExecutions")
-
-
-def _sort_successful_executions_data(query_executions: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
-    """
-    Sorts `_get_last_query_executions`'s results based on query Completion DateTime.
-
-    This is useful to guarantee LRU caching rules.
-    """
-    filtered: List[Dict[str, Any]] = []
-    for query in query_executions:
-        if (query["Status"].get("State") == "SUCCEEDED") and (query.get("StatementType") in ["DDL", "DML"]):
-            filtered.append(query)
-    return sorted(filtered, key=lambda e: str(e["Status"]["CompletionDateTime"]), reverse=True)
+        for query_execution_id in query_execution_id_list:
+            if query_execution_id not in _cache_manager:
+                uncached_ids.append(query_execution_id)
+    if uncached_ids:
+        new_execution_data = []
+        for i in range(0, len(uncached_ids), page_size):
+            new_execution_data.extend(
+                client_athena.batch_get_query_execution(QueryExecutionIds=uncached_ids[i : i + page_size]).get(
+                    "QueryExecutions"
+                )
+            )
+        _cache_manager.update_cache(new_execution_data)
+    return _cache_manager.sorted_successful_generator()
 
 
 def _parse_select_query_from_possible_ctas(possible_ctas: str) -> Optional[str]:
@@ -150,6 +155,7 @@ def _check_for_cached_results(
     workgroup: Optional[str],
     max_cache_seconds: int,
     max_cache_query_inspections: int,
+    max_remote_cache_entries: int,
 ) -> _CacheInfo:
     """
     Check whether `sql` has been run before, within the `max_cache_seconds` window, by the `workgroup`.
@@ -162,45 +168,41 @@ def _check_for_cached_results(
     comparable_sql: str = _prepare_query_string_for_comparison(sql)
     current_timestamp: datetime.datetime = datetime.datetime.now(datetime.timezone.utc)
     _logger.debug("current_timestamp: %s", current_timestamp)
-    for query_executions in _get_last_query_executions(boto3_session=boto3_session, workgroup=workgroup):
-        _logger.debug("len(query_executions): %s", len(query_executions))
-        cached_queries: List[Dict[str, Any]] = _sort_successful_executions_data(query_executions=query_executions)
-        _logger.debug("len(cached_queries): %s", len(cached_queries))
-        for query_info in cached_queries:
-            query_execution_id: str = query_info["QueryExecutionId"]
-            query_timestamp: datetime.datetime = query_info["Status"]["CompletionDateTime"]
-            _logger.debug("query_timestamp: %s", query_timestamp)
-
-            if (current_timestamp - query_timestamp).total_seconds() > max_cache_seconds:
-                return _CacheInfo(
-                    has_valid_cache=False, query_execution_id=query_execution_id, query_execution_payload=query_info
-                )
-
-            statement_type: Optional[str] = query_info.get("StatementType")
-            if statement_type == "DDL" and query_info["Query"].startswith("CREATE TABLE"):
-                parsed_query: Optional[str] = _parse_select_query_from_possible_ctas(possible_ctas=query_info["Query"])
-                if parsed_query is not None:
-                    if _compare_query_string(sql=comparable_sql, other=parsed_query):
-                        return _CacheInfo(
-                            has_valid_cache=True,
-                            file_format="parquet",
-                            query_execution_id=query_execution_id,
-                            query_execution_payload=query_info,
-                        )
-            elif statement_type == "DML" and not query_info["Query"].startswith("INSERT"):
-                if _compare_query_string(sql=comparable_sql, other=query_info["Query"]):
+    for query_info in _get_last_query_infos(
+        max_remote_cache_entries=max_remote_cache_entries,
+        boto3_session=boto3_session,
+        workgroup=workgroup,
+    ):
+        query_execution_id: str = query_info["QueryExecutionId"]
+        query_timestamp: datetime.datetime = query_info["Status"]["CompletionDateTime"]
+        _logger.debug("query_timestamp: %s", query_timestamp)
+        if (current_timestamp - query_timestamp).total_seconds() > max_cache_seconds:
+            return _CacheInfo(
+                has_valid_cache=False, query_execution_id=query_execution_id, query_execution_payload=query_info
+            )
+        statement_type: Optional[str] = query_info.get("StatementType")
+        if statement_type == "DDL" and query_info["Query"].startswith("CREATE TABLE"):
+            parsed_query: Optional[str] = _parse_select_query_from_possible_ctas(possible_ctas=query_info["Query"])
+            if parsed_query is not None:
+                if _compare_query_string(sql=comparable_sql, other=parsed_query):
                     return _CacheInfo(
                         has_valid_cache=True,
-                        file_format="csv",
+                        file_format="parquet",
                         query_execution_id=query_execution_id,
                         query_execution_payload=query_info,
                     )
-
-            num_executions_inspected += 1
-            _logger.debug("num_executions_inspected: %s", num_executions_inspected)
-            if num_executions_inspected >= max_cache_query_inspections:
-                return _CacheInfo(has_valid_cache=False)
-
+        elif statement_type == "DML" and not query_info["Query"].startswith("INSERT"):
+            if _compare_query_string(sql=comparable_sql, other=query_info["Query"]):
+                return _CacheInfo(
+                    has_valid_cache=True,
+                    file_format="csv",
+                    query_execution_id=query_execution_id,
+                    query_execution_payload=query_info,
+                )
+        num_executions_inspected += 1
+        _logger.debug("num_executions_inspected: %s", num_executions_inspected)
+        if num_executions_inspected >= max_cache_query_inspections:
+            return _CacheInfo(has_valid_cache=False)
     return _CacheInfo(has_valid_cache=False)
 
 
@@ -302,6 +304,7 @@ def _resolve_query_with_cache(
         boto3_session=session,
         categories=categories,
         query_execution_payload=cache_info.query_execution_payload,
+        metadata_cache_manager=_cache_manager,
     )
     if cache_info.file_format == "parquet":
         return _fetch_parquet_result(
@@ -380,6 +383,7 @@ def _resolve_query_without_cache_ctas(
             query_execution_id=query_id,
             boto3_session=boto3_session,
             categories=categories,
+            metadata_cache_manager=_cache_manager,
         )
     except exceptions.QueryFailed as ex:
         msg: str = str(ex)
@@ -439,6 +443,7 @@ def _resolve_query_without_cache_regular(
         query_execution_id=query_id,
         boto3_session=boto3_session,
         categories=categories,
+        metadata_cache_manager=_cache_manager,
     )
     return _fetch_csv_result(
         query_metadata=query_metadata,
@@ -532,6 +537,8 @@ def read_sql_query(
     boto3_session: Optional[boto3.Session] = None,
     max_cache_seconds: int = 0,
     max_cache_query_inspections: int = 50,
+    max_remote_cache_entries: int = 50,
+    max_local_cache_entries: int = 100,
     data_source: Optional[str] = None,
     params: Optional[Dict[str, Any]] = None,
 ) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]:
@@ -678,6 +685,15 @@ def read_sql_query(
         Max number of queries that will be inspected from the history to try to find some result to reuse.
         The bigger the number of inspection, the bigger will be the latency for not cached queries.
         Only takes effect if max_cache_seconds > 0.
+    max_remote_cache_entries : int
+        Max number of queries that will be retrieved from AWS for cache inspection.
+        The bigger the number of inspection, the bigger will be the latency for not cached queries.
+        Only takes effect if max_cache_seconds > 0 and default value is 50.
+    max_local_cache_entries : int
+        Max number of queries for which metadata will be cached locally. This will reduce the latency and also
+        enables keeping more than `max_remote_cache_entries` available for the cache. This value should not be
+        smaller than max_remote_cache_entries.
+        Only takes effect if max_cache_seconds > 0 and default value is 100.
     data_source : str, optional
         Data Source / Catalog name. If None, 'AwsDataCatalog' will be used by default.
     params: Dict[str, any], optional
@@ -718,12 +734,17 @@ def read_sql_query(
     for key, value in params.items():
         sql = sql.replace(f":{key};", str(value))
 
+    if max_remote_cache_entries > max_local_cache_entries:
+        max_remote_cache_entries = max_local_cache_entries
+
+    _cache_manager.max_cache_size = max_local_cache_entries
     cache_info: _CacheInfo = _check_for_cached_results(
         sql=sql,
         boto3_session=session,
         workgroup=workgroup,
         max_cache_seconds=max_cache_seconds,
         max_cache_query_inspections=max_cache_query_inspections,
+        max_remote_cache_entries=max_remote_cache_entries,
     )
     _logger.debug("cache_info:\n%s", cache_info)
     if cache_info.has_valid_cache is True:
@@ -774,6 +795,8 @@ def read_sql_table(
     boto3_session: Optional[boto3.Session] = None,
     max_cache_seconds: int = 0,
     max_cache_query_inspections: int = 50,
+    max_remote_cache_entries: int = 50,
+    max_local_cache_entries: int = 100,
     data_source: Optional[str] = None,
 ) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]:
     """Extract the full table AWS Athena and return the results as a Pandas DataFrame.
@@ -914,6 +937,15 @@ def read_sql_table(
         Max number of queries that will be inspected from the history to try to find some result to reuse.
         The bigger the number of inspection, the bigger will be the latency for not cached queries.
         Only takes effect if max_cache_seconds > 0.
+    max_remote_cache_entries : int
+        Max number of queries that will be retrieved from AWS for cache inspection.
+        The bigger the number of inspection, the bigger will be the latency for not cached queries.
+        Only takes effect if max_cache_seconds > 0 and default value is 50.
+    max_local_cache_entries : int
+        Max number of queries for which metadata will be cached locally. This will reduce the latency and also
+        enables keeping more than `max_remote_cache_entries` available for the cache. This value should not be
+        smaller than max_remote_cache_entries.
+        Only takes effect if max_cache_seconds > 0 and default value is 100.
     data_source : str, optional
         Data Source / Catalog name. If None, 'AwsDataCatalog' will be used by default.
 
@@ -947,4 +979,9 @@ def read_sql_table(
         boto3_session=boto3_session,
         max_cache_seconds=max_cache_seconds,
         max_cache_query_inspections=max_cache_query_inspections,
+        max_remote_cache_entries=max_remote_cache_entries,
+        max_local_cache_entries=max_local_cache_entries,
     )
+
+
+_cache_manager = _LocalMetadataCacheManager()

awswrangler/athena/_utils.py

@@ -1,11 +1,13 @@
 """Utilities Module for Amazon Athena."""
 import csv
+import datetime
 import logging
 import pprint
 import time
 import warnings
 from decimal import Decimal
-from typing import Any, Dict, Generator, List, NamedTuple, Optional, Union, cast
+from heapq import heappop, heappush
+from typing import Any, Dict, Generator, List, NamedTuple, Optional, Tuple, Union, cast
 
 import boto3
 import botocore.exceptions
@@ -39,6 +41,71 @@ class _WorkGroupConfig(NamedTuple):
     kms_key: Optional[str]
 
 
+class _LocalMetadataCacheManager:
+    def __init__(self) -> None:
+        self._cache: Dict[str, Any] = dict()
+        self._pqueue: List[Tuple[datetime.datetime, str]] = []
+        self._max_cache_size = 100
+
+    def update_cache(self, items: List[Dict[str, Any]]) -> None:
+        """
+        Update the local metadata cache with new query metadata.
+
+        Parameters
+        ----------
+        items : List[Dict[str, Any]]
+            List of query execution metadata which is returned by boto3 `batch_get_query_execution()`.
+
+        Returns
+        -------
+        None
+            None.
+        """
+        if self._pqueue:
+            oldest_item = self._cache[self._pqueue[0][1]]
+            items = list(
+                filter(lambda x: x["Status"]["SubmissionDateTime"] > oldest_item["Status"]["SubmissionDateTime"], items)
+            )
+
+        cache_oversize = len(self._cache) + len(items) - self._max_cache_size
+        for _ in range(cache_oversize):
+            _, query_execution_id = heappop(self._pqueue)
+            del self._cache[query_execution_id]
+
+        for item in items[: self._max_cache_size]:
+            heappush(self._pqueue, (item["Status"]["SubmissionDateTime"], item["QueryExecutionId"]))
+            self._cache[item["QueryExecutionId"]] = item
+
+    def sorted_successful_generator(self) -> List[Dict[str, Any]]:
+        """
+        Sorts the entries in the local cache based on query Completion DateTime.
+
+        This is useful to guarantee LRU caching rules.
+
+        Returns
+        -------
+        List[Dict[str, Any]]
+            Returns successful DDL and DML queries sorted by query completion time.
+        """
+        filtered: List[Dict[str, Any]] = []
+        for query in self._cache.values():
+            if (query["Status"].get("State") == "SUCCEEDED") and (query.get("StatementType") in ["DDL", "DML"]):
+                filtered.append(query)
+        return sorted(filtered, key=lambda e: str(e["Status"]["CompletionDateTime"]), reverse=True)
+
+    def __contains__(self, key: str) -> bool:
+        return key in self._cache
+
+    @property
+    def max_cache_size(self) -> int:
+        """Property max_cache_size."""
+        return self._max_cache_size
+
+    @max_cache_size.setter
+    def max_cache_size(self, value: int) -> None:
+        self._max_cache_size = value
+
+
 def _get_s3_output(s3_output: Optional[str], wg_config: _WorkGroupConfig, boto3_session: boto3.Session) -> str:
     if wg_config.enforced and wg_config.s3_output is not None:
         return wg_config.s3_output
@@ -171,6 +238,7 @@ def _get_query_metadata(  # pylint: disable=too-many-statements
     boto3_session: boto3.Session,
     categories: Optional[List[str]] = None,
     query_execution_payload: Optional[Dict[str, Any]] = None,
+    metadata_cache_manager: Optional[_LocalMetadataCacheManager] = None,
 ) -> _QueryMetadata:
     """Get query metadata."""
     if (query_execution_payload is not None) and (query_execution_payload["Status"]["State"] in _QUERY_FINAL_STATES):
@@ -224,6 +292,8 @@ def _get_query_metadata(  # pylint: disable=too-many-statements
     athena_statistics: Dict[str, Union[int, str]] = _query_execution_payload.get("Statistics", {})
     manifest_location: Optional[str] = str(athena_statistics.get("DataManifestLocation"))
 
+    if metadata_cache_manager is not None and query_execution_id not in metadata_cache_manager:
+        metadata_cache_manager.update_cache(items=[_query_execution_payload])
     query_metadata: _QueryMetadata = _QueryMetadata(
         execution_id=query_execution_id,
         dtype=dtype,