import hashlib from collections import defaultdict from contextlib import closing from datetime import datetime from operator import attrgetter from typing import Sequence, Set, Tuple import six from elasticsearch import helpers from mongoengine import Q from nested_dict import nested_dict import database.utils as dbutils import es_factory from apierrors import errors from bll.event.debug_images_iterator import DebugImagesIterator from bll.event.event_metrics import EventMetrics, EventType from bll.event.log_events_iterator import LogEventsIterator, TaskEventsResult from bll.task import TaskBLL from config import config from database.errors import translate_errors_context from database.model.task.task import Task, TaskStatus from redis_manager import redman from timing_context import TimingContext from utilities.dicts import flatten_nested_items # noinspection PyTypeChecker EVENT_TYPES = set(map(attrgetter("value"), EventType)) LOCKED_TASK_STATUSES = (TaskStatus.publishing, TaskStatus.published) class EventBLL(object): id_fields = ("task", "iter", "metric", "variant", "key") def __init__(self, events_es=None, redis=None): self.es = events_es or es_factory.connect("events") self._metrics = EventMetrics(self.es) self._skip_iteration_for_metric = set( config.get("services.events.ignore_iteration.metrics", []) ) self.redis = redis or redman.connection("apiserver") self.debug_images_iterator = DebugImagesIterator(es=self.es, redis=self.redis) self.log_events_iterator = LogEventsIterator(es=self.es, redis=self.redis) @property def metrics(self) -> EventMetrics: return self._metrics @staticmethod def _get_valid_tasks(company_id, task_ids: Set, allow_locked_tasks=False) -> Set: """Verify that task exists and can be updated""" if not task_ids: return set() with translate_errors_context(), TimingContext("mongo", "task_by_ids"): query = Q(id__in=task_ids, company=company_id) if not allow_locked_tasks: query &= Q(status__nin=LOCKED_TASK_STATUSES) res = Task.objects(query).only("id") return {r.id for r in res} def add_events( self, company_id, events, worker, allow_locked_tasks=False ) -> Tuple[int, int, dict]: actions = [] task_ids = set() task_iteration = defaultdict(lambda: 0) task_last_scalar_events = nested_dict( 3, dict ) # task_id -> metric_hash -> variant_hash -> MetricEvent task_last_events = nested_dict( 3, dict ) # task_id -> metric_hash -> event_type -> MetricEvent errors_per_type = defaultdict(int) valid_tasks = self._get_valid_tasks( company_id, task_ids={event["task"] for event in events if event.get("task")}, allow_locked_tasks=allow_locked_tasks, ) for event in events: # remove spaces from event type event_type = event.get("type") if event_type is None: errors_per_type["Event must have a 'type' field"] += 1 continue event_type = event_type.replace(" ", "_") if event_type not in EVENT_TYPES: errors_per_type[f"Invalid event type {event_type}"] += 1 continue task_id = event.get("task") if task_id is None: errors_per_type["Event must have a 'task' field"] += 1 continue if task_id not in valid_tasks: errors_per_type["Invalid task id"] += 1 continue event["type"] = event_type # @timestamp indicates the time the event is written, not when it happened event["@timestamp"] = es_factory.get_es_timestamp_str() # for backward bomba-tavili-tea if "ts" in event: event["timestamp"] = event.pop("ts") # set timestamp and worker if not sent if "timestamp" not in event: event["timestamp"] = es_factory.get_timestamp_millis() if "worker" not in event: event["worker"] = worker # force iter to be a long int iter = event.get("iter") if iter is not None: iter = int(iter) event["iter"] = iter # used to have "values" to indicate array. no need anymore if "values" in event: event["value"] = event["values"] del event["values"] event["metric"] = event.get("metric") or "" event["variant"] = event.get("variant") or "" index_name = EventMetrics.get_index_name(company_id, event_type) es_action = { "_op_type": "index", # overwrite if exists with same ID "_index": index_name, "_type": "event", "_source": event, } # for "log" events, don't assing custom _id - whatever is sent, is written (not overwritten) if event_type != "log": es_action["_id"] = self._get_event_id(event) else: es_action["_id"] = dbutils.id() es_action["_routing"] = task_id task_ids.add(task_id) if ( iter is not None and event.get("metric") not in self._skip_iteration_for_metric ): task_iteration[task_id] = max(iter, task_iteration[task_id]) self._update_last_metric_events_for_task( last_events=task_last_events[task_id], event=event, ) if event_type == EventType.metrics_scalar.value: self._update_last_scalar_events_for_task( last_events=task_last_scalar_events[task_id], event=event ) actions.append(es_action) added = 0 if actions: chunk_size = 500 with translate_errors_context(), TimingContext("es", "events_add_batch"): # TODO: replace it with helpers.parallel_bulk in the future once the parallel pool leak is fixed with closing( helpers.streaming_bulk( self.es, actions, chunk_size=chunk_size, # thread_count=8, refresh=True, ) ) as it: for success, info in it: if success: added += chunk_size else: errors_per_type["Error when indexing events batch"] += 1 remaining_tasks = set() now = datetime.utcnow() for task_id in task_ids: # Update related tasks. For reasons of performance, we prefer to update # all of them and not only those who's events were successful updated = self._update_task( company_id=company_id, task_id=task_id, now=now, iter_max=task_iteration.get(task_id), last_scalar_events=task_last_scalar_events.get(task_id), last_events=task_last_events.get(task_id), ) if not updated: remaining_tasks.add(task_id) continue if remaining_tasks: TaskBLL.set_last_update( remaining_tasks, company_id, last_update=now ) # Compensate for always adding chunk_size on success (last chunk is probably smaller) added = min(added, len(actions)) if not added: raise errors.bad_request.EventsNotAdded(**errors_per_type) errors_count = sum(errors_per_type.values()) return added, errors_count, errors_per_type def _update_last_scalar_events_for_task(self, last_events, event): """ Update last_events structure with the provided event details if this event is more recent than the currently stored event for its metric/variant combination. last_events contains [hashed_metric_name -> hashed_variant_name -> event]. Keys are hashed to avoid mongodb key conflicts due to invalid characters and/or long field names. """ metric = event.get("metric") variant = event.get("variant") if not (metric and variant): return metric_hash = dbutils.hash_field_name(metric) variant_hash = dbutils.hash_field_name(variant) timestamp = last_events[metric_hash][variant_hash].get("timestamp", None) if timestamp is None or timestamp < event["timestamp"]: last_events[metric_hash][variant_hash] = event def _update_last_metric_events_for_task(self, last_events, event): """ Update last_events structure with the provided event details if this event is more recent than the currently stored event for its metric/event_type combination. last_events contains [metric_name -> event_type -> event] """ metric = event.get("metric") event_type = event.get("type") if not (metric and event_type): return timestamp = last_events[metric][event_type].get("timestamp", None) if timestamp is None or timestamp < event["timestamp"]: last_events[metric][event_type] = event def _update_task( self, company_id, task_id, now, iter_max=None, last_scalar_events=None, last_events=None, ): """ Update task information in DB with aggregated results after handling event(s) related to this task. This updates the task with the highest iteration value encountered during the last events update, as well as the latest metric/variant scalar values reported (according to the report timestamp) and the task's last update time. """ fields = {} if iter_max is not None: fields["last_iteration_max"] = iter_max if last_scalar_events: fields["last_scalar_values"] = list( flatten_nested_items( last_scalar_events, nesting=2, include_leaves=["value", "metric", "variant"], ) ) if last_events: fields["last_events"] = last_events if not fields: return False return TaskBLL.update_statistics(task_id, company_id, last_update=now, **fields) def _get_event_id(self, event): id_values = (str(event[field]) for field in self.id_fields if field in event) return hashlib.md5("-".join(id_values).encode()).hexdigest() def scroll_task_events( self, company_id, task_id, order, event_type=None, batch_size=10000, scroll_id=None, ): if scroll_id: with translate_errors_context(), TimingContext("es", "task_log_events"): es_res = self.es.scroll(scroll_id=scroll_id, scroll="1h") else: size = min(batch_size, 10000) if event_type is None: event_type = "*" es_index = EventMetrics.get_index_name(company_id, event_type) if not self.es.indices.exists(es_index): return [], None, 0 es_req = { "size": size, "sort": {"timestamp": {"order": order}}, "query": {"bool": {"must": [{"term": {"task": task_id}}]}}, } with translate_errors_context(), TimingContext("es", "scroll_task_events"): es_res = self.es.search( index=es_index, body=es_req, scroll="1h", routing=task_id ) events = [hit["_source"] for hit in es_res["hits"]["hits"]] next_scroll_id = es_res["_scroll_id"] total_events = es_res["hits"]["total"] return events, next_scroll_id, total_events def get_last_iterations_per_event_metric_variant( self, es_index: str, task_id: str, num_last_iterations: int, event_type: str ): if not self.es.indices.exists(es_index): return [] es_req: dict = { "size": 0, "aggs": { "metrics": { "terms": { "field": "metric", "size": EventMetrics.MAX_METRICS_COUNT, }, "aggs": { "variants": { "terms": { "field": "variant", "size": EventMetrics.MAX_VARIANTS_COUNT, }, "aggs": { "iters": { "terms": { "field": "iter", "size": num_last_iterations, "order": {"_term": "desc"}, } } }, } }, } }, "query": {"bool": {"must": [{"term": {"task": task_id}}]}}, } if event_type: es_req["query"]["bool"]["must"].append({"term": {"type": event_type}}) with translate_errors_context(), TimingContext( "es", "task_last_iter_metric_variant" ): es_res = self.es.search(index=es_index, body=es_req, routing=task_id) if "aggregations" not in es_res: return [] return [ (metric["key"], variant["key"], iter["key"]) for metric in es_res["aggregations"]["metrics"]["buckets"] for variant in metric["variants"]["buckets"] for iter in variant["iters"]["buckets"] ] def get_task_plots( self, company_id: str, tasks: Sequence[str], last_iterations_per_plot: int = None, sort=None, size: int = 500, scroll_id: str = None, ): if scroll_id: with translate_errors_context(), TimingContext("es", "get_task_events"): es_res = self.es.scroll(scroll_id=scroll_id, scroll="1h") else: event_type = "plot" es_index = EventMetrics.get_index_name(company_id, event_type) if not self.es.indices.exists(es_index): return TaskEventsResult() query = {"bool": defaultdict(list)} if last_iterations_per_plot is None: must = query["bool"]["must"] must.append({"terms": {"task": tasks}}) else: should = query["bool"]["should"] for i, task_id in enumerate(tasks): last_iters = self.get_last_iterations_per_event_metric_variant( es_index, task_id, last_iterations_per_plot, event_type ) if not last_iters: continue for metric, variant, iter in last_iters: should.append( { "bool": { "must": [ {"term": {"task": task_id}}, {"term": {"metric": metric}}, {"term": {"variant": variant}}, {"term": {"iter": iter}}, ] } } ) if not should: return TaskEventsResult() if sort is None: sort = [{"timestamp": {"order": "asc"}}] es_req = {"sort": sort, "size": min(size, 10000), "query": query} routing = ",".join(tasks) with translate_errors_context(), TimingContext("es", "get_task_plots"): es_res = self.es.search( index=es_index, body=es_req, ignore=404, routing=routing, scroll="1h", ) events = [doc["_source"] for doc in es_res.get("hits", {}).get("hits", [])] # scroll id may be missing when queering a totally empty DB next_scroll_id = es_res.get("_scroll_id") total_events = es_res["hits"]["total"] return TaskEventsResult( events=events, next_scroll_id=next_scroll_id, total_events=total_events ) def get_task_events( self, company_id, task_id, event_type=None, metric=None, variant=None, last_iter_count=None, sort=None, size=500, scroll_id=None, ): if scroll_id: with translate_errors_context(), TimingContext("es", "get_task_events"): es_res = self.es.scroll(scroll_id=scroll_id, scroll="1h") else: task_ids = [task_id] if isinstance(task_id, six.string_types) else task_id if event_type is None: event_type = "*" es_index = EventMetrics.get_index_name(company_id, event_type) if not self.es.indices.exists(es_index): return TaskEventsResult() query = {"bool": defaultdict(list)} if metric or variant: must = query["bool"]["must"] if metric: must.append({"term": {"metric": metric}}) if variant: must.append({"term": {"variant": variant}}) if last_iter_count is None: must = query["bool"]["must"] must.append({"terms": {"task": task_ids}}) else: should = query["bool"]["should"] for i, task_id in enumerate(task_ids): last_iters = self.get_last_iters( es_index, task_id, event_type, last_iter_count ) if not last_iters: continue should.append( { "bool": { "must": [ {"term": {"task": task_id}}, {"terms": {"iter": last_iters}}, ] } } ) if not should: return TaskEventsResult() if sort is None: sort = [{"timestamp": {"order": "asc"}}] es_req = {"sort": sort, "size": min(size, 10000), "query": query} routing = ",".join(task_ids) with translate_errors_context(), TimingContext("es", "get_task_events"): es_res = self.es.search( index=es_index, body=es_req, ignore=404, routing=routing, scroll="1h", ) events = [doc["_source"] for doc in es_res.get("hits", {}).get("hits", [])] next_scroll_id = es_res["_scroll_id"] total_events = es_res["hits"]["total"] return TaskEventsResult( events=events, next_scroll_id=next_scroll_id, total_events=total_events ) def get_metrics_and_variants(self, company_id, task_id, event_type): es_index = EventMetrics.get_index_name(company_id, event_type) if not self.es.indices.exists(es_index): return {} es_req = { "size": 0, "aggs": { "metrics": { "terms": { "field": "metric", "size": EventMetrics.MAX_METRICS_COUNT, }, "aggs": { "variants": { "terms": { "field": "variant", "size": EventMetrics.MAX_VARIANTS_COUNT, } } }, } }, "query": {"bool": {"must": [{"term": {"task": task_id}}]}}, } with translate_errors_context(), TimingContext( "es", "events_get_metrics_and_variants" ): es_res = self.es.search(index=es_index, body=es_req, routing=task_id) metrics = {} for metric_bucket in es_res["aggregations"]["metrics"].get("buckets"): metric = metric_bucket["key"] metrics[metric] = [ b["key"] for b in metric_bucket["variants"].get("buckets") ] return metrics def get_task_latest_scalar_values(self, company_id, task_id): es_index = EventMetrics.get_index_name(company_id, "training_stats_scalar") if not self.es.indices.exists(es_index): return {} es_req = { "size": 0, "query": { "bool": { "must": [ {"query_string": {"query": "value:>0"}}, {"term": {"task": task_id}}, ] } }, "aggs": { "metrics": { "terms": { "field": "metric", "size": EventMetrics.MAX_METRICS_COUNT, "order": {"_term": "asc"}, }, "aggs": { "variants": { "terms": { "field": "variant", "size": EventMetrics.MAX_VARIANTS_COUNT, "order": {"_term": "asc"}, }, "aggs": { "last_value": { "top_hits": { "docvalue_fields": ["value"], "_source": "value", "size": 1, "sort": [{"iter": {"order": "desc"}}], } }, "last_timestamp": {"max": {"field": "@timestamp"}}, "last_10_value": { "top_hits": { "docvalue_fields": ["value"], "_source": "value", "size": 10, "sort": [{"iter": {"order": "desc"}}], } }, }, } }, } }, "_source": {"excludes": []}, } with translate_errors_context(), TimingContext( "es", "events_get_metrics_and_variants" ): es_res = self.es.search(index=es_index, body=es_req, routing=task_id) metrics = [] max_timestamp = 0 for metric_bucket in es_res["aggregations"]["metrics"].get("buckets"): metric_summary = dict(name=metric_bucket["key"], variants=[]) for variant_bucket in metric_bucket["variants"].get("buckets"): variant_name = variant_bucket["key"] last_value = variant_bucket["last_value"]["hits"]["hits"][0]["fields"][ "value" ][0] last_10_value = variant_bucket["last_10_value"]["hits"]["hits"][0][ "fields" ]["value"][0] timestamp = variant_bucket["last_timestamp"]["value"] max_timestamp = max(timestamp, max_timestamp) metric_summary["variants"].append( dict( name=variant_name, last_value=last_value, last_10_value=last_10_value, ) ) metrics.append(metric_summary) return metrics, max_timestamp def get_vector_metrics_per_iter(self, company_id, task_id, metric, variant): es_index = EventMetrics.get_index_name(company_id, "training_stats_vector") if not self.es.indices.exists(es_index): return [], [] es_req = { "size": 10000, "query": { "bool": { "must": [ {"term": {"task": task_id}}, {"term": {"metric": metric}}, {"term": {"variant": variant}}, ] } }, "_source": ["iter", "value"], "sort": ["iter"], } with translate_errors_context(), TimingContext("es", "task_stats_vector"): es_res = self.es.search(index=es_index, body=es_req, routing=task_id) vectors = [] iterations = [] for hit in es_res["hits"]["hits"]: vectors.append(hit["_source"]["value"]) iterations.append(hit["_source"]["iter"]) return iterations, vectors def get_last_iters(self, es_index, task_id, event_type, iters): if not self.es.indices.exists(es_index): return [] es_req: dict = { "size": 0, "aggs": { "iters": { "terms": { "field": "iter", "size": iters, "order": {"_term": "desc"}, } } }, "query": {"bool": {"must": [{"term": {"task": task_id}}]}}, } if event_type: es_req["query"]["bool"]["must"].append({"term": {"type": event_type}}) with translate_errors_context(), TimingContext("es", "task_last_iter"): es_res = self.es.search(index=es_index, body=es_req, routing=task_id) if "aggregations" not in es_res: return [] return [b["key"] for b in es_res["aggregations"]["iters"]["buckets"]] def delete_task_events(self, company_id, task_id, allow_locked=False): with translate_errors_context(): extra_msg = None query = Q(id=task_id, company=company_id) if not allow_locked: query &= Q(status__nin=LOCKED_TASK_STATUSES) extra_msg = "or task published" res = Task.objects(query).only("id").first() if not res: raise errors.bad_request.InvalidTaskId( extra_msg, company=company_id, id=task_id ) es_index = EventMetrics.get_index_name(company_id, "*") es_req = {"query": {"term": {"task": task_id}}} with translate_errors_context(), TimingContext("es", "delete_task_events"): es_res = self.es.delete_by_query( index=es_index, body=es_req, routing=task_id, refresh=True ) return es_res.get("deleted", 0)