request_metric: fix wrong key

backend/src/appenlight/models/services/request_metric.py

@@ -1,623 +1,623 b''
 # -*- coding: utf-8 -*-
 
 # Copyright 2010 - 2017 RhodeCode GmbH and the AppEnlight project authors
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
 #
 #   http://www.apache.org/licenses/LICENSE-2.0
 #
 # Unless required by applicable law or agreed to in writing, software
 # distributed under the License is distributed on an "AS IS" BASIS,
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
 from datetime import datetime
 
 import appenlight.lib.helpers as h
 from appenlight.models import get_db_session, Datastores
 from appenlight.models.services.base import BaseService
 from appenlight.lib.enums import ReportType
 from appenlight.lib.utils import es_index_name_limiter
 
 try:
     from ae_uptime_ce.models.services.uptime_metric import UptimeMetricService
 except ImportError:
     UptimeMetricService = None
 
 
 def check_key(key, stats, uptime, total_seconds):
     if key not in stats:
         stats[key] = {
             "name": key,
             "requests": 0,
             "errors": 0,
             "tolerated_requests": 0,
             "frustrating_requests": 0,
             "satisfying_requests": 0,
             "total_minutes": total_seconds / 60.0,
             "uptime": uptime,
             "apdex": 0,
             "rpm": 0,
             "response_time": 0,
             "avg_response_time": 0,
         }
 
 
 class RequestMetricService(BaseService):
     @classmethod
     def get_metrics_stats(cls, request, filter_settings, db_session=None):
         delta = filter_settings["end_date"] - filter_settings["start_date"]
         if delta < h.time_deltas.get("12h")["delta"]:
             interval = "1m"
         elif delta <= h.time_deltas.get("3d")["delta"]:
             interval = "5m"
         elif delta >= h.time_deltas.get("2w")["delta"]:
             interval = "24h"
         else:
             interval = "1h"
 
         filter_settings["namespace"] = ["appenlight.request_metric"]
 
         es_query = {
             "aggs": {
                 "parent_agg": {
                     "aggs": {
                         "custom": {
                             "aggs": {
                                 "sub_agg": {
                                     "sum": {"field": "tags.custom.numeric_values"}
                                 }
                             },
                             "filter": {
                                 "exists": {"field": "tags.custom.numeric_values"}
                             },
                         },
                         "main": {
                             "aggs": {
                                 "sub_agg": {
                                     "sum": {"field": "tags.main.numeric_values"}
                                 }
                             },
                             "filter": {"exists": {"field": "tags.main.numeric_values"}},
                         },
                         "nosql": {
                             "aggs": {
                                 "sub_agg": {
                                     "sum": {"field": "tags.nosql.numeric_values"}
                                 }
                             },
                             "filter": {
                                 "exists": {"field": "tags.nosql.numeric_values"}
                             },
                         },
                         "remote": {
                             "aggs": {
                                 "sub_agg": {
                                     "sum": {"field": "tags.remote.numeric_values"}
                                 }
                             },
                             "filter": {
                                 "exists": {"field": "tags.remote.numeric_values"}
                             },
                         },
                         "requests": {
                             "aggs": {
                                 "sub_agg": {
                                     "sum": {"field": "tags.requests.numeric_values"}
                                 }
                             },
                             "filter": {
                                 "exists": {"field": "tags.requests.numeric_values"}
                             },
                         },
                         "sql": {
                             "aggs": {
                                 "sub_agg": {"sum": {"field": "tags.sql.numeric_values"}}
                             },
                             "filter": {"exists": {"field": "tags.sql.numeric_values"}},
                         },
                         "tmpl": {
                             "aggs": {
                                 "sub_agg": {
                                     "sum": {"field": "tags.tmpl.numeric_values"}
                                 }
                             },
                             "filter": {"exists": {"field": "tags.tmpl.numeric_values"}},
                         },
                     },
                     "date_histogram": {
                         "extended_bounds": {
                             "max": filter_settings["end_date"],
                             "min": filter_settings["start_date"],
                         },
                         "field": "timestamp",
                         "interval": interval,
                         "min_doc_count": 0,
                     },
                 }
             },
             "query": {
                 "bool": {
                     "filter": [
                         {"terms": {"resource_id": [filter_settings["resource"][0]]}},
                         {
                             "range": {
                                 "timestamp": {
                                     "gte": filter_settings["start_date"],
                                     "lte": filter_settings["end_date"],
                                 }
                             }
                         },
                         {"terms": {"namespace": ["appenlight.request_metric"]}},
                     ]
                 }
             },
         }
 
         index_names = es_index_name_limiter(
             start_date=filter_settings["start_date"],
             end_date=filter_settings["end_date"],
             ixtypes=["metrics"],
         )
         if not index_names:
             return []
 
         result = Datastores.es.search(
             body=es_query, index=index_names, doc_type="log", size=0
         )
 
         plot_data = []
         for item in result["aggregations"]["parent_agg"]["buckets"]:
             x_time = datetime.utcfromtimestamp(int(item["key"]) / 1000)
             point = {"x": x_time}
             for key in ["custom", "main", "nosql", "remote", "requests", "sql", "tmpl"]:
                 value = item[key]["sub_agg"]["value"]
                 point[key] = round(value, 3) if value else 0
             plot_data.append(point)
 
         return plot_data
 
     @classmethod
     def get_requests_breakdown(cls, request, filter_settings, db_session=None):
         db_session = get_db_session(db_session)
 
         # fetch total time of all requests in this time range
         index_names = es_index_name_limiter(
             start_date=filter_settings["start_date"],
             end_date=filter_settings["end_date"],
             ixtypes=["metrics"],
         )
 
         if index_names and filter_settings["resource"]:
             es_query = {
                 "aggs": {
                     "main": {
                         "aggs": {
                             "sub_agg": {"sum": {"field": "tags.main.numeric_values"}}
                         },
                         "filter": {"exists": {"field": "tags.main.numeric_values"}},
                     }
                 },
                 "query": {
                     "bool": {
                         "filter": [
                             {
                                 "terms": {
                                     "resource_id": [filter_settings["resource"][0]]
                                 }
                             },
                             {
                                 "range": {
                                     "timestamp": {
                                         "gte": filter_settings["start_date"],
                                         "lte": filter_settings["end_date"],
                                     }
                                 }
                             },
                             {"terms": {"namespace": ["appenlight.request_metric"]}},
                         ]
                     }
                 },
             }
             result = Datastores.es.search(
                 body=es_query, index=index_names, doc_type="log", size=0
             )
             total_time_spent = result["aggregations"]["main"]["sub_agg"]["value"]
         else:
             total_time_spent = 0
         script_text = "doc['tags.main.numeric_values'].value / {}".format(
             total_time_spent
         )
         if total_time_spent == 0:
             script_text = "0"
 
         if index_names and filter_settings["resource"]:
             es_query = {
                 "aggs": {
                     "parent_agg": {
                         "aggs": {
                             "main": {
                                 "aggs": {
                                     "sub_agg": {
                                         "sum": {"field": "tags.main.numeric_values"}
                                     }
                                 },
                                 "filter": {
                                     "exists": {"field": "tags.main.numeric_values"}
                                 },
                             },
                             "percentage": {
                                 "aggs": {"sub_agg": {"sum": {"script": script_text}}},
                                 "filter": {
                                     "exists": {"field": "tags.main.numeric_values"}
                                 },
                             },
                             "requests": {
                                 "aggs": {
                                     "sub_agg": {
                                         "sum": {"field": "tags.requests.numeric_values"}
                                     }
                                 },
                                 "filter": {
                                     "exists": {"field": "tags.requests.numeric_values"}
                                 },
                             },
                         },
                         "terms": {
                             "field": "tags.view_name.values.keyword",
                             "order": {"percentage>sub_agg": "desc"},
                             "size": 15,
                         },
                     }
                 },
                 "query": {
                     "bool": {
                         "filter": [
                             {
                                 "terms": {
                                     "resource_id": [filter_settings["resource"][0]]
                                 }
                             },
                             {
                                 "range": {
                                     "timestamp": {
                                         "gte": filter_settings["start_date"],
                                         "lte": filter_settings["end_date"],
                                     }
                                 }
                             },
                         ]
                     }
                 },
             }
             result = Datastores.es.search(
                 body=es_query, index=index_names, doc_type="log", size=0
             )
             series = result["aggregations"]["parent_agg"]["buckets"]
         else:
             series = []
 
         and_part = [
             {"term": {"resource_id": filter_settings["resource"][0]}},
             {"terms": {"tags.view_name.values": [row["key"] for row in series]}},
             {"term": {"report_type": str(ReportType.slow)}},
         ]
         query = {
             "aggs": {
                 "top_reports": {
                     "terms": {
                         "field": "tags.view_name.values.keyword",
                         "size": len(series),
                     },
                     "aggs": {
                         "top_calls_hits": {
                             "top_hits": {"sort": {"start_time": "desc"}, "size": 5}
                         }
                     },
                 }
             },
             "query": {"bool": {"filter": and_part}},
         }
         details = {}
         index_names = es_index_name_limiter(ixtypes=["reports"])
         if index_names and series:
             result = Datastores.es.search(
                 body=query, doc_type="report", size=0, index=index_names
             )
             for bucket in result["aggregations"]["top_reports"]["buckets"]:
                 details[bucket["key"]] = []
 
                 for hit in bucket["top_calls_hits"]["hits"]["hits"]:
                     details[bucket["key"]].append(
                         {
-                            "report_id": hit["_source"]["request_metric_id"],
+                            "report_id": hit["_source"]["report_id"],
                             "group_id": hit["_source"]["group_id"],
                         }
                     )
 
         results = []
         for row in series:
             result = {
                 "key": row["key"],
                 "main": row["main"]["sub_agg"]["value"],
                 "requests": row["requests"]["sub_agg"]["value"],
             }
             # es can return 'infinity'
             try:
                 result["percentage"] = float(row["percentage"]["sub_agg"]["value"])
             except ValueError:
                 result["percentage"] = 0
 
             result["latest_details"] = details.get(row["key"]) or []
             results.append(result)
 
         return results
 
     @classmethod
     def get_apdex_stats(cls, request, filter_settings, threshold=1, db_session=None):
         """
         Returns information and calculates APDEX score per server for dashboard
         server information (upper right stats boxes)
         """
         # Apdex t = (Satisfied Count + Tolerated Count / 2) / Total Samples
         db_session = get_db_session(db_session)
         index_names = es_index_name_limiter(
             start_date=filter_settings["start_date"],
             end_date=filter_settings["end_date"],
             ixtypes=["metrics"],
         )
 
         requests_series = []
 
         if index_names and filter_settings["resource"]:
             es_query = {
                 "aggs": {
                     "parent_agg": {
                         "aggs": {
                             "frustrating": {
                                 "aggs": {
                                     "sub_agg": {
                                         "sum": {"field": "tags.requests.numeric_values"}
                                     }
                                 },
                                 "filter": {
                                     "bool": {
                                         "filter": [
                                             {
                                                 "range": {
                                                     "tags.main.numeric_values": {
                                                         "gte": "4"
                                                     }
                                                 }
                                             },
                                             {
                                                 "exists": {
                                                     "field": "tags.requests.numeric_values"
                                                 }
                                             },
                                         ]
                                     }
                                 },
                             },
                             "main": {
                                 "aggs": {
                                     "sub_agg": {
                                         "sum": {"field": "tags.main.numeric_values"}
                                     }
                                 },
                                 "filter": {
                                     "exists": {"field": "tags.main.numeric_values"}
                                 },
                             },
                             "requests": {
                                 "aggs": {
                                     "sub_agg": {
                                         "sum": {"field": "tags.requests.numeric_values"}
                                     }
                                 },
                                 "filter": {
                                     "exists": {"field": "tags.requests.numeric_values"}
                                 },
                             },
                             "tolerated": {
                                 "aggs": {
                                     "sub_agg": {
                                         "sum": {"field": "tags.requests.numeric_values"}
                                     }
                                 },
                                 "filter": {
                                     "bool": {
                                         "filter": [
                                             {
                                                 "range": {
                                                     "tags.main.numeric_values": {
                                                         "gte": "1"
                                                     }
                                                 }
                                             },
                                             {
                                                 "range": {
                                                     "tags.main.numeric_values": {
                                                         "lt": "4"
                                                     }
                                                 }
                                             },
                                             {
                                                 "exists": {
                                                     "field": "tags.requests.numeric_values"
                                                 }
                                             },
                                         ]
                                     }
                                 },
                             },
                         },
                         "terms": {
                             "field": "tags.server_name.values.keyword",
                             "size": 999999,
                         },
                     }
                 },
                 "query": {
                     "bool": {
                         "filter": [
                             {
                                 "terms": {
                                     "resource_id": [filter_settings["resource"][0]]
                                 }
                             },
                             {
                                 "range": {
                                     "timestamp": {
                                         "gte": filter_settings["start_date"],
                                         "lte": filter_settings["end_date"],
                                     }
                                 }
                             },
                             {"terms": {"namespace": ["appenlight.request_metric"]}},
                         ]
                     }
                 },
             }
 
             result = Datastores.es.search(
                 body=es_query, index=index_names, doc_type="log", size=0
             )
             for bucket in result["aggregations"]["parent_agg"]["buckets"]:
                 requests_series.append(
                     {
                         "frustrating": bucket["frustrating"]["sub_agg"]["value"],
                         "main": bucket["main"]["sub_agg"]["value"],
                         "requests": bucket["requests"]["sub_agg"]["value"],
                         "tolerated": bucket["tolerated"]["sub_agg"]["value"],
                         "key": bucket["key"],
                     }
                 )
 
         since_when = filter_settings["start_date"]
         until = filter_settings["end_date"]
 
         # total errors
 
         index_names = es_index_name_limiter(
             start_date=filter_settings["start_date"],
             end_date=filter_settings["end_date"],
             ixtypes=["reports"],
         )
 
         report_series = []
         if index_names and filter_settings["resource"]:
             report_type = ReportType.key_from_value(ReportType.error)
             es_query = {
                 "aggs": {
                     "parent_agg": {
                         "aggs": {
                             "errors": {
                                 "aggs": {
                                     "sub_agg": {
                                         "sum": {
                                             "field": "tags.occurences.numeric_values"
                                         }
                                     }
                                 },
                                 "filter": {
                                     "bool": {
                                         "filter": [
                                             {
                                                 "terms": {
                                                     "tags.type.values": [report_type]
                                                 }
                                             },
                                             {
                                                 "exists": {
                                                     "field": "tags.occurences.numeric_values"
                                                 }
                                             },
                                         ]
                                     }
                                 },
                             }
                         },
                         "terms": {
                             "field": "tags.server_name.values.keyword",
                             "size": 999999,
                         },
                     }
                 },
                 "query": {
                     "bool": {
                         "filter": [
                             {
                                 "terms": {
                                     "resource_id": [filter_settings["resource"][0]]
                                 }
                             },
                             {
                                 "range": {
                                     "timestamp": {
                                         "gte": filter_settings["start_date"],
                                         "lte": filter_settings["end_date"],
                                     }
                                 }
                             },
                             {"terms": {"namespace": ["appenlight.error"]}},
                         ]
                     }
                 },
             }
             result = Datastores.es.search(
                 body=es_query, index=index_names, doc_type="log", size=0
             )
             for bucket in result["aggregations"]["parent_agg"]["buckets"]:
                 report_series.append(
                     {
                         "key": bucket["key"],
                         "errors": bucket["errors"]["sub_agg"]["value"],
                     }
                 )
 
         stats = {}
         if UptimeMetricService is not None:
             uptime = UptimeMetricService.get_uptime_by_app(
                 filter_settings["resource"][0], since_when=since_when, until=until
             )
         else:
             uptime = 0
 
         total_seconds = (until - since_when).total_seconds()
 
         for stat in requests_series:
             check_key(stat["key"], stats, uptime, total_seconds)
             stats[stat["key"]]["requests"] = int(stat["requests"])
             stats[stat["key"]]["response_time"] = stat["main"]
             stats[stat["key"]]["tolerated_requests"] = stat["tolerated"]
             stats[stat["key"]]["frustrating_requests"] = stat["frustrating"]
         for server in report_series:
             check_key(server["key"], stats, uptime, total_seconds)
             stats[server["key"]]["errors"] = server["errors"]
 
         server_stats = list(stats.values())
         for stat in server_stats:
             stat["satisfying_requests"] = (
                 stat["requests"]
                 - stat["errors"]
                 - stat["frustrating_requests"]
                 - stat["tolerated_requests"]
             )
             if stat["satisfying_requests"] < 0:
                 stat["satisfying_requests"] = 0
 
             if stat["requests"]:
                 stat["avg_response_time"] = round(
                     stat["response_time"] / stat["requests"], 3
                 )
                 qual_requests = (
                     stat["satisfying_requests"] + stat["tolerated_requests"] / 2.0
                 )
                 stat["apdex"] = round((qual_requests / stat["requests"]) * 100, 2)
                 stat["rpm"] = round(stat["requests"] / stat["total_minutes"], 2)
 
         return sorted(server_stats, key=lambda x: x["name"])