diff options
Diffstat (limited to 'tools/run_tests/performance/bq_upload_result.py')
| -rwxr-xr-x | tools/run_tests/performance/bq_upload_result.py | 219 |
1 files changed, 117 insertions, 102 deletions
diff --git a/tools/run_tests/performance/bq_upload_result.py b/tools/run_tests/performance/bq_upload_result.py index 31819d6159..6702587557 100755 --- a/tools/run_tests/performance/bq_upload_result.py +++ b/tools/run_tests/performance/bq_upload_result.py @@ -26,146 +26,161 @@ import time import uuid import massage_qps_stats - -gcp_utils_dir = os.path.abspath(os.path.join( - os.path.dirname(__file__), '../../gcp/utils')) +gcp_utils_dir = os.path.abspath( + os.path.join(os.path.dirname(__file__), '../../gcp/utils')) sys.path.append(gcp_utils_dir) import big_query_utils - -_PROJECT_ID='grpc-testing' +_PROJECT_ID = 'grpc-testing' def _upload_netperf_latency_csv_to_bigquery(dataset_id, table_id, result_file): - with open(result_file, 'r') as f: - (col1, col2, col3) = f.read().split(',') - latency50 = float(col1.strip()) * 1000 - latency90 = float(col2.strip()) * 1000 - latency99 = float(col3.strip()) * 1000 - - scenario_result = { - 'scenario': { - 'name': 'netperf_tcp_rr' - }, - 'summary': { - 'latency50': latency50, - 'latency90': latency90, - 'latency99': latency99 + with open(result_file, 'r') as f: + (col1, col2, col3) = f.read().split(',') + latency50 = float(col1.strip()) * 1000 + latency90 = float(col2.strip()) * 1000 + latency99 = float(col3.strip()) * 1000 + + scenario_result = { + 'scenario': { + 'name': 'netperf_tcp_rr' + }, + 'summary': { + 'latency50': latency50, + 'latency90': latency90, + 'latency99': latency99 + } } - } - bq = big_query_utils.create_big_query() - _create_results_table(bq, dataset_id, table_id) + bq = big_query_utils.create_big_query() + _create_results_table(bq, dataset_id, table_id) - if not _insert_result(bq, dataset_id, table_id, scenario_result, flatten=False): - print('Error uploading result to bigquery.') - sys.exit(1) + if not _insert_result( + bq, dataset_id, table_id, scenario_result, flatten=False): + print('Error uploading result to bigquery.') + sys.exit(1) def _upload_scenario_result_to_bigquery(dataset_id, table_id, result_file): - with open(result_file, 'r') as f: - scenario_result = json.loads(f.read()) + with open(result_file, 'r') as f: + scenario_result = json.loads(f.read()) - bq = big_query_utils.create_big_query() - _create_results_table(bq, dataset_id, table_id) + bq = big_query_utils.create_big_query() + _create_results_table(bq, dataset_id, table_id) - if not _insert_result(bq, dataset_id, table_id, scenario_result): - print('Error uploading result to bigquery.') - sys.exit(1) + if not _insert_result(bq, dataset_id, table_id, scenario_result): + print('Error uploading result to bigquery.') + sys.exit(1) def _insert_result(bq, dataset_id, table_id, scenario_result, flatten=True): - if flatten: - _flatten_result_inplace(scenario_result) - _populate_metadata_inplace(scenario_result) - row = big_query_utils.make_row(str(uuid.uuid4()), scenario_result) - return big_query_utils.insert_rows(bq, - _PROJECT_ID, - dataset_id, - table_id, - [row]) + if flatten: + _flatten_result_inplace(scenario_result) + _populate_metadata_inplace(scenario_result) + row = big_query_utils.make_row(str(uuid.uuid4()), scenario_result) + return big_query_utils.insert_rows(bq, _PROJECT_ID, dataset_id, table_id, + [row]) def _create_results_table(bq, dataset_id, table_id): - with open(os.path.dirname(__file__) + '/scenario_result_schema.json', 'r') as f: - table_schema = json.loads(f.read()) - desc = 'Results of performance benchmarks.' - return big_query_utils.create_table2(bq, _PROJECT_ID, dataset_id, - table_id, table_schema, desc) + with open(os.path.dirname(__file__) + '/scenario_result_schema.json', + 'r') as f: + table_schema = json.loads(f.read()) + desc = 'Results of performance benchmarks.' + return big_query_utils.create_table2(bq, _PROJECT_ID, dataset_id, table_id, + table_schema, desc) def _flatten_result_inplace(scenario_result): - """Bigquery is not really great for handling deeply nested data + """Bigquery is not really great for handling deeply nested data and repeated fields. To maintain values of some fields while keeping the schema relatively simple, we artificially leave some of the fields as JSON strings. """ - scenario_result['scenario']['clientConfig'] = json.dumps(scenario_result['scenario']['clientConfig']) - scenario_result['scenario']['serverConfig'] = json.dumps(scenario_result['scenario']['serverConfig']) - scenario_result['latencies'] = json.dumps(scenario_result['latencies']) - scenario_result['serverCpuStats'] = [] - for stats in scenario_result['serverStats']: - scenario_result['serverCpuStats'].append(dict()) - scenario_result['serverCpuStats'][-1]['totalCpuTime'] = stats.pop('totalCpuTime', None) - scenario_result['serverCpuStats'][-1]['idleCpuTime'] = stats.pop('idleCpuTime', None) - for stats in scenario_result['clientStats']: - stats['latencies'] = json.dumps(stats['latencies']) - stats.pop('requestResults', None) - scenario_result['serverCores'] = json.dumps(scenario_result['serverCores']) - scenario_result['clientSuccess'] = json.dumps(scenario_result['clientSuccess']) - scenario_result['serverSuccess'] = json.dumps(scenario_result['serverSuccess']) - scenario_result['requestResults'] = json.dumps(scenario_result.get('requestResults', [])) - scenario_result['serverCpuUsage'] = scenario_result['summary'].pop('serverCpuUsage', None) - scenario_result['summary'].pop('successfulRequestsPerSecond', None) - scenario_result['summary'].pop('failedRequestsPerSecond', None) - massage_qps_stats.massage_qps_stats(scenario_result) + scenario_result['scenario']['clientConfig'] = json.dumps( + scenario_result['scenario']['clientConfig']) + scenario_result['scenario']['serverConfig'] = json.dumps( + scenario_result['scenario']['serverConfig']) + scenario_result['latencies'] = json.dumps(scenario_result['latencies']) + scenario_result['serverCpuStats'] = [] + for stats in scenario_result['serverStats']: + scenario_result['serverCpuStats'].append(dict()) + scenario_result['serverCpuStats'][-1]['totalCpuTime'] = stats.pop( + 'totalCpuTime', None) + scenario_result['serverCpuStats'][-1]['idleCpuTime'] = stats.pop( + 'idleCpuTime', None) + for stats in scenario_result['clientStats']: + stats['latencies'] = json.dumps(stats['latencies']) + stats.pop('requestResults', None) + scenario_result['serverCores'] = json.dumps(scenario_result['serverCores']) + scenario_result['clientSuccess'] = json.dumps( + scenario_result['clientSuccess']) + scenario_result['serverSuccess'] = json.dumps( + scenario_result['serverSuccess']) + scenario_result['requestResults'] = json.dumps( + scenario_result.get('requestResults', [])) + scenario_result['serverCpuUsage'] = scenario_result['summary'].pop( + 'serverCpuUsage', None) + scenario_result['summary'].pop('successfulRequestsPerSecond', None) + scenario_result['summary'].pop('failedRequestsPerSecond', None) + massage_qps_stats.massage_qps_stats(scenario_result) def _populate_metadata_inplace(scenario_result): - """Populates metadata based on environment variables set by Jenkins.""" - # NOTE: Grabbing the Jenkins environment variables will only work if the - # driver is running locally on the same machine where Jenkins has started - # the job. For our setup, this is currently the case, so just assume that. - build_number = os.getenv('BUILD_NUMBER') - build_url = os.getenv('BUILD_URL') - job_name = os.getenv('JOB_NAME') - git_commit = os.getenv('GIT_COMMIT') - # actual commit is the actual head of PR that is getting tested - git_actual_commit = os.getenv('ghprbActualCommit') - - utc_timestamp = str(calendar.timegm(time.gmtime())) - metadata = {'created': utc_timestamp} - - if build_number: - metadata['buildNumber'] = build_number - if build_url: - metadata['buildUrl'] = build_url - if job_name: - metadata['jobName'] = job_name - if git_commit: - metadata['gitCommit'] = git_commit - if git_actual_commit: - metadata['gitActualCommit'] = git_actual_commit - - scenario_result['metadata'] = metadata + """Populates metadata based on environment variables set by Jenkins.""" + # NOTE: Grabbing the Jenkins environment variables will only work if the + # driver is running locally on the same machine where Jenkins has started + # the job. For our setup, this is currently the case, so just assume that. + build_number = os.getenv('BUILD_NUMBER') + build_url = os.getenv('BUILD_URL') + job_name = os.getenv('JOB_NAME') + git_commit = os.getenv('GIT_COMMIT') + # actual commit is the actual head of PR that is getting tested + git_actual_commit = os.getenv('ghprbActualCommit') + + utc_timestamp = str(calendar.timegm(time.gmtime())) + metadata = {'created': utc_timestamp} + + if build_number: + metadata['buildNumber'] = build_number + if build_url: + metadata['buildUrl'] = build_url + if job_name: + metadata['jobName'] = job_name + if git_commit: + metadata['gitCommit'] = git_commit + if git_actual_commit: + metadata['gitActualCommit'] = git_actual_commit + + scenario_result['metadata'] = metadata argp = argparse.ArgumentParser(description='Upload result to big query.') -argp.add_argument('--bq_result_table', required=True, default=None, type=str, - help='Bigquery "dataset.table" to upload results to.') -argp.add_argument('--file_to_upload', default='scenario_result.json', type=str, - help='Report file to upload.') -argp.add_argument('--file_format', - choices=['scenario_result','netperf_latency_csv'], - default='scenario_result', - help='Format of the file to upload.') +argp.add_argument( + '--bq_result_table', + required=True, + default=None, + type=str, + help='Bigquery "dataset.table" to upload results to.') +argp.add_argument( + '--file_to_upload', + default='scenario_result.json', + type=str, + help='Report file to upload.') +argp.add_argument( + '--file_format', + choices=['scenario_result', 'netperf_latency_csv'], + default='scenario_result', + help='Format of the file to upload.') args = argp.parse_args() dataset_id, table_id = args.bq_result_table.split('.', 2) if args.file_format == 'netperf_latency_csv': - _upload_netperf_latency_csv_to_bigquery(dataset_id, table_id, args.file_to_upload) + _upload_netperf_latency_csv_to_bigquery(dataset_id, table_id, + args.file_to_upload) else: - _upload_scenario_result_to_bigquery(dataset_id, table_id, args.file_to_upload) + _upload_scenario_result_to_bigquery(dataset_id, table_id, + args.file_to_upload) print('Successfully uploaded %s to BigQuery.\n' % args.file_to_upload) |