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# 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).
import os
import time
import unittest
from unittest.mock import MagicMock
from advisor.db_stats_fetcher import DatabasePerfContext, LogStatsParser
from advisor.db_timeseries_parser import NO_ENTITY
from advisor.rule_parser import Condition, TimeSeriesCondition
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)
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