# Copyright (c) 2011-present, Facebook, Inc. All rights reserved. # This source code is licensed under both the GPLv2 (found in the # COPYING file in the root directory) and Apache 2.0 License # (found in the LICENSE.Apache file in the root directory). from advisor.db_stats_fetcher import LogStatsParser, DatabasePerfContext from advisor.db_timeseries_parser import NO_ENTITY from advisor.rule_parser import Condition, TimeSeriesCondition import os import time import unittest from unittest.mock import MagicMock class TestLogStatsParser(unittest.TestCase): def setUp(self): this_path = os.path.abspath(os.path.dirname(__file__)) stats_file = os.path.join( this_path, 'input_files/log_stats_parser_keys_ts' ) # populate the keys_ts dictionary of LogStatsParser self.stats_dict = {NO_ENTITY: {}} with open(stats_file, 'r') as fp: for line in fp: stat_name = line.split(':')[0].strip() self.stats_dict[NO_ENTITY][stat_name] = {} token_list = line.split(':')[1].strip().split(',') for token in token_list: timestamp = int(token.split()[0]) value = float(token.split()[1]) self.stats_dict[NO_ENTITY][stat_name][timestamp] = value self.log_stats_parser = LogStatsParser('dummy_log_file', 20) self.log_stats_parser.keys_ts = self.stats_dict def test_check_and_trigger_conditions_bursty(self): # mock fetch_timeseries() because 'keys_ts' has been pre-populated self.log_stats_parser.fetch_timeseries = MagicMock() # condition: bursty cond1 = Condition('cond-1') cond1 = TimeSeriesCondition.create(cond1) cond1.set_parameter('keys', 'rocksdb.db.get.micros.p50') cond1.set_parameter('behavior', 'bursty') cond1.set_parameter('window_sec', 40) cond1.set_parameter('rate_threshold', 0) self.log_stats_parser.check_and_trigger_conditions([cond1]) expected_cond_trigger = { NO_ENTITY: {1530896440: 0.9767546362322214} } self.assertDictEqual(expected_cond_trigger, cond1.get_trigger()) # ensure that fetch_timeseries() was called once self.log_stats_parser.fetch_timeseries.assert_called_once() def test_check_and_trigger_conditions_eval_agg(self): # mock fetch_timeseries() because 'keys_ts' has been pre-populated self.log_stats_parser.fetch_timeseries = MagicMock() # condition: evaluate_expression cond1 = Condition('cond-1') cond1 = TimeSeriesCondition.create(cond1) cond1.set_parameter('keys', 'rocksdb.db.get.micros.p50') cond1.set_parameter('behavior', 'evaluate_expression') keys = [ 'rocksdb.manifest.file.sync.micros.p99', 'rocksdb.db.get.micros.p50' ] cond1.set_parameter('keys', keys) cond1.set_parameter('aggregation_op', 'latest') # condition evaluates to FALSE cond1.set_parameter('evaluate', 'keys[0]-(keys[1]*100)>200') self.log_stats_parser.check_and_trigger_conditions([cond1]) expected_cond_trigger = {NO_ENTITY: [1792.0, 15.9638]} self.assertIsNone(cond1.get_trigger()) # condition evaluates to TRUE cond1.set_parameter('evaluate', 'keys[0]-(keys[1]*100)<200') self.log_stats_parser.check_and_trigger_conditions([cond1]) expected_cond_trigger = {NO_ENTITY: [1792.0, 15.9638]} self.assertDictEqual(expected_cond_trigger, cond1.get_trigger()) # ensure that fetch_timeseries() was called self.log_stats_parser.fetch_timeseries.assert_called() def test_check_and_trigger_conditions_eval(self): # mock fetch_timeseries() because 'keys_ts' has been pre-populated self.log_stats_parser.fetch_timeseries = MagicMock() # condition: evaluate_expression cond1 = Condition('cond-1') cond1 = TimeSeriesCondition.create(cond1) cond1.set_parameter('keys', 'rocksdb.db.get.micros.p50') cond1.set_parameter('behavior', 'evaluate_expression') keys = [ 'rocksdb.manifest.file.sync.micros.p99', 'rocksdb.db.get.micros.p50' ] cond1.set_parameter('keys', keys) cond1.set_parameter('evaluate', 'keys[0]-(keys[1]*100)>500') self.log_stats_parser.check_and_trigger_conditions([cond1]) expected_trigger = {NO_ENTITY: { 1530896414: [9938.0, 16.31508], 1530896440: [9938.0, 16.346602], 1530896466: [9938.0, 16.284669], 1530896492: [9938.0, 16.16005] }} self.assertDictEqual(expected_trigger, cond1.get_trigger()) self.log_stats_parser.fetch_timeseries.assert_called_once() class TestDatabasePerfContext(unittest.TestCase): def test_unaccumulate_metrics(self): perf_dict = { "user_key_comparison_count": 675903942, "block_cache_hit_count": 830086, } timestamp = int(time.time()) perf_ts = {} for key in perf_dict: perf_ts[key] = {} start_val = perf_dict[key] for ix in range(5): perf_ts[key][timestamp+(ix*10)] = start_val + (2 * ix * ix) db_perf_context = DatabasePerfContext(perf_ts, 10, True) timestamps = [timestamp+(ix*10) for ix in range(1, 5, 1)] values = [val for val in range(2, 15, 4)] inner_dict = {timestamps[ix]: values[ix] for ix in range(4)} expected_keys_ts = {NO_ENTITY: { 'user_key_comparison_count': inner_dict, 'block_cache_hit_count': inner_dict }} self.assertDictEqual(expected_keys_ts, db_perf_context.keys_ts)