""" Copyright (c) Contributors to the Open 3D Engine Project. For complete copyright and license terms please see the LICENSE at the root of this distribution. SPDX-License-Identifier: Apache-2.0 OR MIT """ from argparse import ArgumentParser import json from pathlib import Path import time import subprocess from ly_test_tools.mars.filebeat_client import FilebeatClient class BenchmarkPathException(Exception): """Custom Exception class for invalid benchmark file paths.""" pass class BenchmarkDataAggregator(object): def __init__(self, workspace, logger, test_suite): self.build_dir = workspace.paths.build_directory() self.results_dir = Path(workspace.paths.project(), 'user/Scripts/PerformanceBenchmarks') self.test_suite = test_suite self.filebeat_client = FilebeatClient(logger) def _update_pass(self, pass_stats, entry): ''' Modifies pass_stats dict keyed by pass name with the time recorded in a pass timestamp entry. :param pass_stats: dict aggregating statistics from each pass (key: pass name, value: dict with stats) :param entry: dict representing the timestamp entry of a pass :return: Time (in nanoseconds) recorded by this pass ''' name = entry['passName'] time_ns = entry['timestampResultInNanoseconds'] pass_entry = pass_stats.get(name, { 'totalTime': 0, 'maxTime': 0 }) pass_entry['maxTime'] = max(time_ns, pass_entry['maxTime']) pass_entry['totalTime'] += time_ns pass_stats[name] = pass_entry return time_ns def _process_benchmark(self, benchmark_dir, benchmark_metadata): ''' Aggregates data from results from a single benchmark contained in a subdirectory of self.results_dir. :param benchmark_dir: Path of directory containing the benchmark results :param benchmark_metadata: Dict with benchmark metadata mutated with additional info from metadata file :return: Tuple with two indexes: [0]: Dict aggregating statistics from frame times (key: stat name) [1]: Dict aggregating statistics from pass times (key: pass name, value: dict with stats) ''' # Parse benchmark metadata metadata_file = benchmark_dir / 'benchmark_metadata.json' if metadata_file.exists(): data = json.loads(metadata_file.read_text()) benchmark_metadata.update(data['ClassData']) else: raise BenchmarkPathException(f'Metadata file could not be found at {metadata_file}') # data structures aggregating statistics from timestamp logs frame_stats = { 'count': 0, 'totalTime': 0, 'maxTime': 0, 'minTime': float('inf') } pass_stats = {} # key: pass name, value: dict with totalTime and maxTime keys # this allows us to add additional data if necessary, e.g. frame_test_timestamps.json is_timestamp_file = lambda file: file.name.startswith('frame') and file.name.endswith('_timestamps.json') # parse benchmark files for file in benchmark_dir.iterdir(): if file.is_dir() or not is_timestamp_file(file): continue data = json.loads(file.read_text()) entries = data['ClassData']['timestampEntries'] frame_time = sum(self._update_pass(pass_stats, entry) for entry in entries) frame_stats['totalTime'] += frame_time frame_stats['maxTime'] = max(frame_time, frame_stats['maxTime']) frame_stats['minTime'] = min(frame_time, frame_stats['minTime']) frame_stats['count'] += 1 if frame_stats['count'] < 1: raise BenchmarkPathException(f'No frame timestamp logs were found in {benchmark_dir}') return frame_stats, pass_stats def _generate_payloads(self, benchmark_metadata, frame_stats, pass_stats): ''' Generates payloads to send to Filebeat based on aggregated stats and metadata. :param benchmark_metadata: Dict of benchmark metadata :param frame_stats: Dict of aggregated frame statistics :param pass_stats: Dict of aggregated pass statistics :return payloads: List of tuples, each with two indexes: [0]: Elasticsearch index suffix associated with the payload [1]: Payload dict to deliver to Filebeat ''' ns_to_ms = lambda ns: ns / 1e6 payloads = [] # calculate statistics based on aggregated frame data frame_time_avg = frame_stats['totalTime'] / frame_stats['count'] frame_payload = { 'frameTime': { 'avg': ns_to_ms(frame_time_avg), 'max': ns_to_ms(frame_stats['maxTime']), 'min': ns_to_ms(frame_stats['minTime']) } } # add benchmark metadata to payload frame_payload.update(benchmark_metadata) payloads.append(('frame_data', frame_payload)) # calculate statistics for each pass for name, stat in pass_stats.items(): avg_ms = ns_to_ms(stat['totalTime'] / frame_stats['count']) max_ms = ns_to_ms(stat['maxTime']) pass_payload = { 'passName': name, 'passTime': { 'avg': avg_ms, 'max': max_ms } } # add benchmark metadata to payload pass_payload.update(benchmark_metadata) payloads.append(('pass_data', pass_payload)) return payloads def upload_metrics(self, rhi): ''' Uploads metrics aggregated from all the benchmarks run in a test suite to filebeat. :param rhi: The RHI the benchmarks were run on ''' start_timestamp = time.time() git_commit_data = subprocess.check_output(['git', 'rev-parse', '--short', 'HEAD'], cwd=self.build_dir) git_commit_hash = git_commit_data.decode('ascii').strip() build_date = time.strftime('%m/%d/%y', time.localtime(start_timestamp)) # use gmtime if GMT is preferred for benchmark_dir in self.results_dir.iterdir(): if not benchmark_dir.is_dir(): continue benchmark_metadata = { 'gitCommitAndBuildDate': f'{git_commit_hash} {build_date}', 'RHI': rhi } frame_stats, pass_stats = self._process_benchmark(benchmark_dir, benchmark_metadata) payloads = self._generate_payloads(benchmark_metadata, frame_stats, pass_stats) for index_suffix, payload in payloads: self.filebeat_client.send_event( payload, f'ly_atom.performance_metrics.{self.test_suite}.{index_suffix}', start_timestamp )