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feat: Implementation of run partition query (#1080)
* feat: Implementation of run partition query * Comments incorporated * Comments incorporated * Comments incorporated
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,133 @@ | ||
| # Copyright 2024 Google LLC All rights reserved. | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
| from concurrent.futures import ThreadPoolExecutor | ||
| from dataclasses import dataclass | ||
| from queue import Queue | ||
| from typing import Any, TYPE_CHECKING | ||
| from threading import Lock, Event | ||
|
|
||
| if TYPE_CHECKING: | ||
| from google.cloud.spanner_v1.database import BatchSnapshot | ||
|
|
||
| QUEUE_SIZE_PER_WORKER = 32 | ||
| MAX_PARALLELISM = 16 | ||
|
|
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|
|
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| class PartitionExecutor: | ||
| """ | ||
| Executor that executes single partition on a separate thread and inserts | ||
| rows in the queue | ||
| """ | ||
|
|
||
| def __init__(self, batch_snapshot, partition_id, merged_result_set): | ||
| self._batch_snapshot: BatchSnapshot = batch_snapshot | ||
| self._partition_id = partition_id | ||
| self._merged_result_set: MergedResultSet = merged_result_set | ||
| self._queue: Queue[PartitionExecutorResult] = merged_result_set._queue | ||
|
|
||
| def run(self): | ||
| results = None | ||
| try: | ||
| results = self._batch_snapshot.process_query_batch(self._partition_id) | ||
| for row in results: | ||
| if self._merged_result_set._metadata is None: | ||
| self._set_metadata(results) | ||
| self._queue.put(PartitionExecutorResult(data=row)) | ||
| # Special case: The result set did not return any rows. | ||
| # Push the metadata to the merged result set. | ||
| if self._merged_result_set._metadata is None: | ||
| self._set_metadata(results) | ||
| except Exception as ex: | ||
| if self._merged_result_set._metadata is None: | ||
| self._set_metadata(results, True) | ||
| self._queue.put(PartitionExecutorResult(exception=ex)) | ||
| finally: | ||
| # Emit a special 'is_last' result to ensure that the MergedResultSet | ||
| # is not blocked on a queue that never receives any more results. | ||
| self._queue.put(PartitionExecutorResult(is_last=True)) | ||
|
|
||
| def _set_metadata(self, results, is_exception=False): | ||
| self._merged_result_set.metadata_lock.acquire() | ||
| try: | ||
| if not is_exception: | ||
| self._merged_result_set._metadata = results.metadata | ||
| finally: | ||
| self._merged_result_set.metadata_lock.release() | ||
| self._merged_result_set.metadata_event.set() | ||
|
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||
|
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| @dataclass | ||
| class PartitionExecutorResult: | ||
| data: Any = None | ||
| exception: Exception = None | ||
| is_last: bool = False | ||
|
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||
|
|
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| class MergedResultSet: | ||
| """ | ||
| Executes multiple partitions on different threads and then combines the | ||
| results from multiple queries using a synchronized queue. The order of the | ||
| records in the MergedResultSet is not guaranteed. | ||
| """ | ||
|
|
||
| def __init__(self, batch_snapshot, partition_ids, max_parallelism): | ||
| self._exception = None | ||
| self._metadata = None | ||
| self.metadata_event = Event() | ||
| self.metadata_lock = Lock() | ||
|
|
||
| partition_ids_count = len(partition_ids) | ||
| self._finished_count_down_latch = partition_ids_count | ||
| parallelism = min(MAX_PARALLELISM, partition_ids_count) | ||
| if max_parallelism != 0: | ||
| parallelism = min(partition_ids_count, max_parallelism) | ||
| self._queue = Queue(maxsize=QUEUE_SIZE_PER_WORKER * parallelism) | ||
|
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| partition_executors = [] | ||
| for partition_id in partition_ids: | ||
| partition_executors.append( | ||
| PartitionExecutor(batch_snapshot, partition_id, self) | ||
| ) | ||
| executor = ThreadPoolExecutor(max_workers=parallelism) | ||
| for partition_executor in partition_executors: | ||
| executor.submit(partition_executor.run) | ||
| executor.shutdown(False) | ||
|
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| def __iter__(self): | ||
| return self | ||
|
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| def __next__(self): | ||
| if self._exception is not None: | ||
| raise self._exception | ||
| while True: | ||
| partition_result = self._queue.get() | ||
| if partition_result.is_last: | ||
| self._finished_count_down_latch -= 1 | ||
| if self._finished_count_down_latch == 0: | ||
| raise StopIteration | ||
| elif partition_result.exception is not None: | ||
| self._exception = partition_result.exception | ||
| raise self._exception | ||
| else: | ||
| return partition_result.data | ||
|
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||
| @property | ||
| def metadata(self): | ||
| self.metadata_event.wait() | ||
| return self._metadata | ||
|
|
||
| @property | ||
| def stats(self): | ||
| # TODO: Implement | ||
| return None |
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