update ceph source to reef 18.1.2

[ceph.git] / ceph / src / rocksdb / tools / advisor / advisor / db_timeseries_parser.py

diff --git a/ceph/src/rocksdb/tools/advisor/advisor/db_timeseries_parser.py b/ceph/src/rocksdb/tools/advisor/advisor/db_timeseries_parser.py
index 308eb139ae4da642022886a7dc6b2c829944b44d..5840d7b909af508b25d12f62977e3c1c809e5096 100644 (file)
--- a/ceph/src/rocksdb/tools/advisor/advisor/db_timeseries_parser.py
+++ b/ceph/src/rocksdb/tools/advisor/advisor/db_timeseries_parser.py
@@ -3,13 +3,15 @@
 #  COPYING file in the root directory) and Apache 2.0 License
 #  (found in the LICENSE.Apache file in the root directory).
 
+import math
 from abc import abstractmethod
-from advisor.db_log_parser import DataSource
 from enum import Enum
-import math
+from typing import Dict
+
+from advisor.db_log_parser import DataSource
 
 
-NO_ENTITY = 'ENTITY_PLACEHOLDER'
+NO_ENTITY = "ENTITY_PLACEHOLDER"
 
 
 class TimeSeriesData(DataSource):
@@ -43,9 +45,13 @@ class TimeSeriesData(DataSource):
         pass
 
     def fetch_burst_epochs(
-        self, entities, statistic, window_sec, threshold, percent
-    ):
-        # type: (str, int, float, bool) -> Dict[str, Dict[int, float]]
+        self,
+        entities: str,
+        statistic: int,
+        window_sec: float,
+        threshold: bool,
+        percent: bool,
+    ) -> Dict[str, Dict[int, float]]:
         # this method calculates the (percent) rate change in the 'statistic'
         # for each entity (over 'window_sec' seconds) and returns the epochs
         # where this rate change is greater than or equal to the 'threshold'
@@ -90,7 +96,6 @@ class TimeSeriesData(DataSource):
         return burst_epochs
 
     def fetch_aggregated_values(self, entity, statistics, aggregation_op):
-        # type: (str, AggregationOperator) -> Dict[str, float]
         # this method performs the aggregation specified by 'aggregation_op'
         # on the timeseries of 'statistics' for 'entity' and returns:
         # Dict[statistic, aggregated_value]
@@ -145,7 +150,7 @@ class TimeSeriesData(DataSource):
                     complete_keys[0],  # there should be only one key
                     cond.window_sec,
                     cond.rate_threshold,
-                    True
+                    True,
                 )
                 # Trigger in this case is:
                 # Dict[entity_name, Dict[timestamp, rate_change]]
@@ -156,32 +161,28 @@ class TimeSeriesData(DataSource):
                     cond.set_trigger(result)
             elif cond.behavior is self.Behavior.evaluate_expression:
                 self.handle_evaluate_expression(
-                    cond,
-                    complete_keys,
-                    entities_with_stats
+                    cond, complete_keys, entities_with_stats
                 )
 
     def handle_evaluate_expression(self, condition, statistics, entities):
         trigger = {}
         # check 'condition' for each of these entities
         for entity in entities:
-            if hasattr(condition, 'aggregation_op'):
+            if hasattr(condition, "aggregation_op"):
                 # in this case, the aggregation operation is performed on each
                 # of the condition's 'keys' and then with aggregated values
                 # condition's 'expression' is evaluated; if it evaluates to
                 # True, then list of the keys values is added to the
                 # condition's trigger: Dict[entity_name, List[stats]]
                 result = self.fetch_aggregated_values(
-                        entity, statistics, condition.aggregation_op
+                    entity, statistics, condition.aggregation_op
                 )
                 keys = [result[key] for key in statistics]
                 try:
                     if eval(condition.expression):
                         trigger[entity] = keys
                 except Exception as e:
-                    print(
-                        'WARNING(TimeSeriesData) check_and_trigger: ' + str(e)
-                    )
+                    print("WARNING(TimeSeriesData) check_and_trigger: " + str(e))
             else:
                 # assumption: all stats have same series of timestamps
                 # this is similar to the above but 'expression' is evaluated at
@@ -190,19 +191,13 @@ class TimeSeriesData(DataSource):
                 # 'expression' evaluated to true; so trigger is:
                 # Dict[entity, Dict[timestamp, List[stats]]]
                 for epoch in self.keys_ts[entity][statistics[0]].keys():
-                    keys = [
-                        self.keys_ts[entity][key][epoch]
-                        for key in statistics
-                    ]
+                    keys = [self.keys_ts[entity][key][epoch] for key in statistics]
                     try:
                         if eval(condition.expression):
                             if entity not in trigger:
                                 trigger[entity] = {}
                             trigger[entity][epoch] = keys
                     except Exception as e:
-                        print(
-                            'WARNING(TimeSeriesData) check_and_trigger: ' +
-                            str(e)
-                        )
+                        print("WARNING(TimeSeriesData) check_and_trigger: " + str(e))
         if trigger:
             condition.set_trigger(trigger)