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