mirror of https://github.com/mongodb/mongo
111 lines
4.7 KiB
Python
111 lines
4.7 KiB
Python
# Copyright (C) 2022-present MongoDB, Inc.
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the Server Side Public License, version 1,
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# as published by MongoDB, Inc.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# Server Side Public License for more details.
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#
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# You should have received a copy of the Server Side Public License
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# along with this program. If not, see
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# <http://www.mongodb.com/licensing/server-side-public-license>.
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#
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# As a special exception, the copyright holders give permission to link the
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# code of portions of this program with the OpenSSL library under certain
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# conditions as described in each individual source file and distribute
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# linked combinations including the program with the OpenSSL library. You
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# must comply with the Server Side Public License in all respects for
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# all of the code used other than as permitted herein. If you modify file(s)
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# with this exception, you may extend this exception to your version of the
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# file(s), but you are not obligated to do so. If you do not wish to do so,
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# delete this exception statement from your version. If you delete this
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# exception statement from all source files in the program, then also delete
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# it in the license file.
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#
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"""Cost Model Calibrator entry point."""
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import dataclasses
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import os
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import csv
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import asyncio
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from typing import Mapping, Sequence
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from cost_estimator import ExecutionStats, ModelParameters
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from data_generator import DataGenerator
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from database_instance import DatabaseInstance
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import abt_calibrator
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import workload_execution
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from workload_execution import Query, QueryParameters
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import parameters_extractor
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from calibration_settings import distributions, main_config
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__all__ = []
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def save_to_csv(parameters: Mapping[str, Sequence[ModelParameters]], filepath: str) -> None:
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"""Save model input parameters to a csv file."""
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abt_type_name = 'abt_type'
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fieldnames = [
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abt_type_name, *[f.name for f in dataclasses.fields(ExecutionStats)],
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*[f.name for f in dataclasses.fields(QueryParameters)]
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]
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with open(filepath, 'w', newline='') as csvfile:
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writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
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writer.writeheader()
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for abt_type, type_params_list in parameters.items():
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for type_params in type_params_list:
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fields = dataclasses.asdict(type_params.execution_stats) | dataclasses.asdict(
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type_params.query_params)
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fields[abt_type_name] = abt_type
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writer.writerow(fields)
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async def main():
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"""Entry point function."""
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script_directory = os.path.abspath(os.path.dirname(__file__))
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os.chdir(script_directory)
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# 1. Database Instance provides connectivity to a MongoDB instance, it loads data optionally
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# from the dump on creating and stores data optionally to the dump on closing.
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with DatabaseInstance(main_config.database) as database:
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# 2. Data generation (optional), generates random data and populates collections with it.
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generator = DataGenerator(database, main_config.data_generator)
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await generator.populate_collections()
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# 3. Collecting data for calibration (optional).
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# It runs the pipelines and stores explains to the database.
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requests = []
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for val in distributions['string_choice'].get_values():
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keys_length = len(val) + 2
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for i in range(1, 5):
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requests.append(
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Query(pipeline=[{'$match': {f'choice{i}': val}}],
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keys_length_in_bytes=keys_length))
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await workload_execution.execute(database, main_config.workload_execution,
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generator.collection_infos, requests)
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# Calibration phase (optional).
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# Reads the explains stored on the previous step (this run and/or previous runs),
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# aparses the explains, nd calibrates the cost model for the ABT nodes.
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models = await abt_calibrator.calibrate(
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main_config.abt_calibrator, database,
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['IndexScan', 'Seek', 'PhysicalScan', 'ValueScan', 'CoScan', 'Scan'])
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for abt, model in models.items():
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print(abt)
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print(model)
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parameters = await parameters_extractor.extract_parameters(main_config.abt_calibrator,
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database, [])
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save_to_csv(parameters, 'parameters.csv')
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print("DONE!")
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if __name__ == '__main__':
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loop = asyncio.get_event_loop()
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loop.run_until_complete(main())
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