CI Benchmarking with CircleCI Runner and OpenSearch Dashboard (EB 1088) (#9723)
Summary: CircleCI runner based benchmarking. A runner is a dedicate machine configured for CircleCI to perform work on. Our work is a repeatable benchmark, the `benchmark-linux` job in `config.yml` A runner, in CircleCI terminology, is a machine that is managed by the client (us) rather than running on CircleCI resources in the cloud. This means that we define and configure the iron, and that therefore the performance is repeatable and predictable. Which is what we need for performance regression benchmarking. On a time schedule (or on commit, during branch development) benchmarks are set off on the runner, and then a script is run `benchmark_log_tool.py` which parses the benchmark output and pushes it into a pre-configured OpenSearch document connected to an OpenSearch dashboard. Members of the team can examine benchmark performance changes on the dashboard. As time progresses we can add different benchmarks to the suite which gets run. Pull Request resolved: https://github.com/facebook/rocksdb/pull/9723 Reviewed By: pdillinger Differential Revision: D35555626 Pulled By: jay-zhuang fbshipit-source-id: c6a905ca04494495c3784cfbb991f5ab90c807eemain
Alan Paxton
3 years ago
committed by
Facebook GitHub Bot
parent
560906ab33
commit
2f4a0ffef8
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#!/usr/bin/env python3 |
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# Copyright (c) 2011-present, Facebook, Inc. All rights reserved. |
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# This source code is licensed under both the GPLv2 (found in the |
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# COPYING file in the root directory) and Apache 2.0 License |
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# (found in the LICENSE.Apache file in the root directory). |
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|
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'''Access the results of benchmark runs |
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Send these results on to OpenSearch graphing service |
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''' |
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|
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import argparse |
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import itertools |
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import os |
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import re |
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import sys |
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import requests |
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from dateutil import parser |
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import logging |
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logging.basicConfig(level=logging.DEBUG) |
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class Configuration: |
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opensearch_user = os.environ['ES_USER'] |
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opensearch_pass = os.environ['ES_PASS'] |
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|
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class BenchmarkResultException(Exception): |
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def __init__(self, message, content): |
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super().__init__(self, message) |
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self.content = content |
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class BenchmarkUtils: |
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expected_keys = ['ops_sec', 'mb_sec', 'total_size_gb', 'level0_size_gb', 'sum_gb', 'write_amplification', |
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'write_mbps', 'usec_op', 'percentile_50', 'percentile_75', |
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'percentile_99', 'percentile_99.9', 'percentile_99.99', 'uptime', |
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'stall_time', 'stall_percent', 'test_name', 'test_date', 'rocksdb_version', |
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'job_id', 'timestamp'] |
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metric_keys = ['ops_sec', 'mb_sec', 'total_size_gb', 'level0_size_gb', 'sum_gb', 'write_amplification', |
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'write_mbps', 'usec_op', 'percentile_50', 'percentile_75', |
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'percentile_99', 'percentile_99.9', 'percentile_99.99', 'uptime', |
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'stall_time', 'stall_percent'] |
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|
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def sanity_check(row): |
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if not 'test_name' in row: |
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return False |
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if row['test_name'] == '': |
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return False |
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if not 'test_date' in row: |
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return False |
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if not 'ops_sec' in row: |
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return False |
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try: |
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v = int(row['ops_sec']) |
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except (ValueError, TypeError): |
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return False |
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return True |
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def conform_opensearch(row): |
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(dt, _) = parser.parse(row['test_date'], fuzzy_with_tokens=True) |
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row['test_date'] = dt.isoformat() |
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return dict((key.replace('.', '_'), value) |
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for (key, value) in row.items()) |
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class ResultParser: |
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def __init__(self, field="(\w|[+-:.])+", intrafield="(\s)+", separator="\t"): |
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self.field = re.compile(field) |
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self.intra = re.compile(intrafield) |
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self.sep = re.compile(separator) |
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|
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def line(self, l_in: str): |
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'''Parse a line into items |
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Being clever about separators |
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''' |
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l = l_in |
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row = [] |
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while l != '': |
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match_item = self.field.match(l) |
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if match_item: |
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item = match_item.group(0) |
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row.append(item) |
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l = l[len(item):] |
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else: |
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match_intra = self.intra.match(l) |
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if match_intra: |
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intra = match_intra.group(0) |
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# Count the separators |
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# If there are >1 then generate extra blank fields |
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# White space with no true separators fakes up a single separator |
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tabbed = self.sep.split(intra) |
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sep_count = len(tabbed) - 1 |
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if sep_count == 0: |
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sep_count = 1 |
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for i in range(sep_count-1): |
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row.append('') |
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l = l[len(intra):] |
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else: |
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raise BenchmarkResultException( |
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'Invalid TSV line', f"{l_in} at {l}") |
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return row |
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def parse(self, lines): |
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'''Parse something that iterates lines''' |
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rows = [self.line(line) for line in lines] |
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header = rows[0] |
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width = len(header) |
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records = [{k: v for (k, v) in itertools.zip_longest( |
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header, row[:width])} for row in rows[1:]] |
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return records |
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def load_report_from_tsv(filename: str): |
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file = open(filename, 'r') |
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contents = file.readlines() |
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file.close() |
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parser = ResultParser() |
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report = parser.parse(contents) |
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logging.debug(f"Loaded TSV Report: {report}") |
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return report |
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def push_report_to_opensearch(report, esdocument): |
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sanitized = [BenchmarkUtils.conform_opensearch(row) |
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for row in report if BenchmarkUtils.sanity_check(row)] |
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logging.debug(f"upload {len(sanitized)} benchmarks to opensearch") |
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for single_benchmark in sanitized: |
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logging.debug(f"upload benchmark: {single_benchmark}") |
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response = requests.post( |
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esdocument, |
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json=single_benchmark, auth=(os.environ['ES_USER'], os.environ['ES_PASS'])) |
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logging.debug( |
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f"Sent to OpenSearch, status: {response.status_code}, result: {response.text}") |
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response.raise_for_status() |
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def main(): |
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'''Tool for fetching, parsing and uploading benchmark results to OpenSearch / ElasticSearch |
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This tool will |
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(1) Open a local tsv benchmark report file |
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(2) Upload to OpenSearch document, via https/JSON |
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''' |
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parser = argparse.ArgumentParser( |
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description='CircleCI benchmark scraper.') |
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# --tsvfile is the name of the file to read results from |
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# --esdocument is the ElasticSearch document to push these results into |
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# |
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parser.add_argument('--tsvfile', default='build_tools/circle_api_scraper_input.txt', |
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help='File from which to read tsv report') |
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parser.add_argument('--esdocument', help='ElasticSearch/OpenSearch document URL to upload report into') |
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args = parser.parse_args() |
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logging.debug(f"Arguments: {args}") |
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reports = load_report_from_tsv(args.tsvfile) |
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push_report_to_opensearch(reports, args.esdocument) |
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if __name__ == '__main__': |
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sys.exit(main()) |
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