mirror of https://github.com/grpc/grpc.git
The C based gRPC (C++, Python, Ruby, Objective-C, PHP, C#)
https://grpc.io/
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257 lines
10 KiB
257 lines
10 KiB
#!/usr/bin/env python2.7 |
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# Copyright 2017, Google Inc. |
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# All rights reserved. |
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# |
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# Redistribution and use in source and binary forms, with or without |
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# modification, are permitted provided that the following conditions are |
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# met: |
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# |
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# * Redistributions of source code must retain the above copyright |
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# notice, this list of conditions and the following disclaimer. |
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# * Redistributions in binary form must reproduce the above |
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# copyright notice, this list of conditions and the following disclaimer |
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# in the documentation and/or other materials provided with the |
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# distribution. |
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# * Neither the name of Google Inc. nor the names of its |
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# contributors may be used to endorse or promote products derived from |
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# this software without specific prior written permission. |
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# |
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS |
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# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT |
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# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR |
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# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT |
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# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, |
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# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT |
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# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, |
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# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY |
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# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT |
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# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE |
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
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import cgi |
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import multiprocessing |
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import os |
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import subprocess |
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import sys |
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import argparse |
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import python_utils.jobset as jobset |
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import python_utils.start_port_server as start_port_server |
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flamegraph_dir = os.path.join(os.path.expanduser('~'), 'FlameGraph') |
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os.chdir(os.path.join(os.path.dirname(sys.argv[0]), '../..')) |
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if not os.path.exists('reports'): |
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os.makedirs('reports') |
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port_server_port = 32766 |
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start_port_server.start_port_server(port_server_port) |
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def fnize(s): |
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out = '' |
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for c in s: |
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if c in '<>, /': |
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if len(out) and out[-1] == '_': continue |
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out += '_' |
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else: |
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out += c |
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return out |
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# index html |
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index_html = """ |
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<html> |
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<head> |
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<title>Microbenchmark Results</title> |
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</head> |
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<body> |
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""" |
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def heading(name): |
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global index_html |
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index_html += "<h1>%s</h1>\n" % name |
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def link(txt, tgt): |
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global index_html |
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index_html += "<p><a href=\"%s\">%s</a></p>\n" % ( |
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cgi.escape(tgt, quote=True), cgi.escape(txt)) |
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def text(txt): |
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global index_html |
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index_html += "<p><pre>%s</pre></p>\n" % cgi.escape(txt) |
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def collect_latency(bm_name, args): |
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"""generate latency profiles""" |
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benchmarks = [] |
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profile_analysis = [] |
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cleanup = [] |
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heading('Latency Profiles: %s' % bm_name) |
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subprocess.check_call( |
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['make', bm_name, |
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'CONFIG=basicprof', '-j', '%d' % multiprocessing.cpu_count()]) |
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for line in subprocess.check_output(['bins/basicprof/%s' % bm_name, |
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'--benchmark_list_tests']).splitlines(): |
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link(line, '%s.txt' % fnize(line)) |
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benchmarks.append( |
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jobset.JobSpec(['bins/basicprof/%s' % bm_name, |
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'--benchmark_filter=^%s$' % line, |
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'--benchmark_min_time=0.05'], |
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environ={'LATENCY_TRACE': '%s.trace' % fnize(line)})) |
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profile_analysis.append( |
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jobset.JobSpec([sys.executable, |
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'tools/profiling/latency_profile/profile_analyzer.py', |
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'--source', '%s.trace' % fnize(line), '--fmt', 'simple', |
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'--out', 'reports/%s.txt' % fnize(line)], timeout_seconds=None)) |
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cleanup.append(jobset.JobSpec(['rm', '%s.trace' % fnize(line)])) |
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# periodically flush out the list of jobs: profile_analysis jobs at least |
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# consume upwards of five gigabytes of ram in some cases, and so analysing |
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# hundreds of them at once is impractical -- but we want at least some |
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# concurrency or the work takes too long |
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if len(benchmarks) >= min(16, multiprocessing.cpu_count()): |
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# run up to half the cpu count: each benchmark can use up to two cores |
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# (one for the microbenchmark, one for the data flush) |
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jobset.run(benchmarks, maxjobs=max(1, multiprocessing.cpu_count()/2), |
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add_env={'GRPC_TEST_PORT_SERVER': 'localhost:%d' % port_server_port}) |
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jobset.run(profile_analysis, maxjobs=multiprocessing.cpu_count()) |
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jobset.run(cleanup, maxjobs=multiprocessing.cpu_count()) |
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benchmarks = [] |
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profile_analysis = [] |
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cleanup = [] |
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# run the remaining benchmarks that weren't flushed |
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if len(benchmarks): |
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jobset.run(benchmarks, maxjobs=max(1, multiprocessing.cpu_count()/2), |
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add_env={'GRPC_TEST_PORT_SERVER': 'localhost:%d' % port_server_port}) |
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jobset.run(profile_analysis, maxjobs=multiprocessing.cpu_count()) |
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jobset.run(cleanup, maxjobs=multiprocessing.cpu_count()) |
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def collect_perf(bm_name, args): |
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"""generate flamegraphs""" |
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heading('Flamegraphs: %s' % bm_name) |
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subprocess.check_call( |
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['make', bm_name, |
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'CONFIG=mutrace', '-j', '%d' % multiprocessing.cpu_count()]) |
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benchmarks = [] |
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profile_analysis = [] |
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cleanup = [] |
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for line in subprocess.check_output(['bins/mutrace/%s' % bm_name, |
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'--benchmark_list_tests']).splitlines(): |
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link(line, '%s.svg' % fnize(line)) |
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benchmarks.append( |
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jobset.JobSpec(['perf', 'record', '-o', '%s-perf.data' % fnize(line), |
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'-g', '-F', '997', |
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'bins/mutrace/%s' % bm_name, |
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'--benchmark_filter=^%s$' % line, |
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'--benchmark_min_time=10'])) |
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profile_analysis.append( |
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jobset.JobSpec(['tools/run_tests/performance/process_local_perf_flamegraphs.sh'], |
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environ = { |
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'PERF_BASE_NAME': fnize(line), |
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'OUTPUT_DIR': 'reports', |
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'OUTPUT_FILENAME': fnize(line), |
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})) |
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cleanup.append(jobset.JobSpec(['rm', '%s-perf.data' % fnize(line)])) |
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cleanup.append(jobset.JobSpec(['rm', '%s-out.perf' % fnize(line)])) |
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# periodically flush out the list of jobs: temporary space required for this |
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# processing is large |
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if len(benchmarks) >= 20: |
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# run up to half the cpu count: each benchmark can use up to two cores |
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# (one for the microbenchmark, one for the data flush) |
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jobset.run(benchmarks, maxjobs=1, |
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add_env={'GRPC_TEST_PORT_SERVER': 'localhost:%d' % port_server_port}) |
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jobset.run(profile_analysis, maxjobs=multiprocessing.cpu_count()) |
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jobset.run(cleanup, maxjobs=multiprocessing.cpu_count()) |
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benchmarks = [] |
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profile_analysis = [] |
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cleanup = [] |
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# run the remaining benchmarks that weren't flushed |
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if len(benchmarks): |
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jobset.run(benchmarks, maxjobs=1, |
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add_env={'GRPC_TEST_PORT_SERVER': 'localhost:%d' % port_server_port}) |
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jobset.run(profile_analysis, maxjobs=multiprocessing.cpu_count()) |
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jobset.run(cleanup, maxjobs=multiprocessing.cpu_count()) |
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def run_summary(bm_name, cfg, base_json_name): |
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subprocess.check_call( |
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['make', bm_name, |
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'CONFIG=%s' % cfg, '-j', '%d' % multiprocessing.cpu_count()]) |
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cmd = ['bins/%s/%s' % (cfg, bm_name), |
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'--benchmark_out=%s.%s.json' % (base_json_name, cfg), |
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'--benchmark_out_format=json'] |
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if args.summary_time is not None: |
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cmd += ['--benchmark_min_time=%d' % args.summary_time] |
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return subprocess.check_output(cmd) |
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def collect_summary(bm_name, args): |
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heading('Summary: %s [no counters]' % bm_name) |
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text(run_summary(bm_name, 'opt', 'out')) |
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heading('Summary: %s [with counters]' % bm_name) |
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text(run_summary(bm_name, 'counters', 'out')) |
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if args.bigquery_upload: |
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with open('out.csv', 'w') as f: |
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f.write(subprocess.check_output(['tools/profiling/microbenchmarks/bm2bq.py', 'out.counters.json', 'out.opt.json'])) |
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subprocess.check_call(['bq', 'load', 'microbenchmarks.microbenchmarks', 'out.csv']) |
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collectors = { |
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'latency': collect_latency, |
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'perf': collect_perf, |
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'summary': collect_summary, |
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} |
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argp = argparse.ArgumentParser(description='Collect data from microbenchmarks') |
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argp.add_argument('-c', '--collect', |
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choices=sorted(collectors.keys()), |
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nargs='+', |
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default=sorted(collectors.keys()), |
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help='Which collectors should be run against each benchmark') |
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argp.add_argument('-b', '--benchmarks', |
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default=['bm_fullstack', |
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'bm_closure', |
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'bm_cq', |
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'bm_call_create', |
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'bm_error', |
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'bm_chttp2_hpack', |
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'bm_metadata'], |
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nargs='+', |
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type=str, |
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help='Which microbenchmarks should be run') |
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argp.add_argument('--diff_perf', |
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default=None, |
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type=str, |
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help='Diff microbenchmarks against this git revision') |
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argp.add_argument('--bigquery_upload', |
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default=False, |
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action='store_const', |
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const=True, |
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help='Upload results from summary collection to bigquery') |
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argp.add_argument('--summary_time', |
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default=None, |
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type=int, |
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help='Minimum time to run benchmarks for the summary collection') |
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args = argp.parse_args() |
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for bm_name in args.benchmarks: |
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for collect in args.collect: |
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collectors[collect](bm_name, args) |
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if args.diff_perf: |
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for bm_name in args.benchmarks: |
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run_summary(bm_name, 'opt', '%s.new' % bm_name) |
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where_am_i = submodule.check_call(['git', 'rev-parse', '--abbrev-ref', 'HEAD']) |
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submodule.check_call(['git', 'checkout', args.diff_perf]) |
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comparables = [] |
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try: |
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for bm_name in args.benchmarks: |
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try: |
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run_summary(bm_name, 'opt', '%s.old' % bm_name) |
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comparables.append(bm_name) |
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except subprocess.CalledProcessError, e: |
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pass |
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finally: |
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submodule.check_call(['git', 'checkout', where_am_i]) |
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for bm_name in comparables: |
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submodule.check_call(['third_party/benchmark/tools/compare_bench.py', |
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'%s.new.opt.json' % bm_name, |
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'%s.old.opt.json' % bm_name]) |
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index_html += "</body>\n</html>\n" |
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with open('reports/index.html', 'w') as f: |
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f.write(index_html)
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