mirror of
https://github.com/clearml/clearml-server
synced 2025-06-26 23:15:47 +00:00
Rename server to apiserver
This commit is contained in:
allegroai
243
apiserver/bll/workers/stats.py
Normal file
243
apiserver/bll/workers/stats.py
Normal file
@@ -0,0 +1,243 @@
|
||||
from operator import attrgetter
|
||||
from typing import Optional, Sequence
|
||||
|
||||
from boltons.iterutils import bucketize
|
||||
|
||||
from apierrors.errors import bad_request
|
||||
from apimodels.workers import AggregationType, GetStatsRequest, StatItem
|
||||
from bll.query import Builder as QueryBuilder
|
||||
from config import config
|
||||
from database.errors import translate_errors_context
|
||||
from timing_context import TimingContext
|
||||
|
||||
log = config.logger(__file__)
|
||||
|
||||
|
||||
class WorkerStats:
|
||||
def __init__(self, es):
|
||||
self.es = es
|
||||
|
||||
@staticmethod
|
||||
def worker_stats_prefix_for_company(company_id: str) -> str:
|
||||
"""Returns the es index prefix for the company"""
|
||||
return f"worker_stats_{company_id}_"
|
||||
|
||||
def _search_company_stats(self, company_id: str, es_req: dict) -> dict:
|
||||
return self.es.search(
|
||||
index=f"{self.worker_stats_prefix_for_company(company_id)}*",
|
||||
body=es_req,
|
||||
)
|
||||
|
||||
def get_worker_stats_keys(
|
||||
self, company_id: str, worker_ids: Optional[Sequence[str]]
|
||||
) -> dict:
|
||||
"""
|
||||
Get dictionary of metric types grouped by categories
|
||||
:param company_id: company id
|
||||
:param worker_ids: optional list of workers to get metric types from.
|
||||
If not specified them metrics for all the company workers returned
|
||||
:return:
|
||||
"""
|
||||
es_req = {
|
||||
"size": 0,
|
||||
"aggs": {
|
||||
"categories": {
|
||||
"terms": {"field": "category"},
|
||||
"aggs": {"metrics": {"terms": {"field": "metric"}}},
|
||||
}
|
||||
},
|
||||
}
|
||||
if worker_ids:
|
||||
es_req["query"] = QueryBuilder.terms("worker", worker_ids)
|
||||
|
||||
res = self._search_company_stats(company_id, es_req)
|
||||
|
||||
if not res["hits"]["total"]["value"]:
|
||||
raise bad_request.WorkerStatsNotFound(
|
||||
f"No statistic metrics found for the company {company_id} and workers {worker_ids}"
|
||||
)
|
||||
|
||||
return {
|
||||
category["key"]: [
|
||||
metric["key"] for metric in category["metrics"]["buckets"]
|
||||
]
|
||||
for category in res["aggregations"]["categories"]["buckets"]
|
||||
}
|
||||
|
||||
def get_worker_stats(self, company_id: str, request: GetStatsRequest) -> dict:
|
||||
"""
|
||||
Get statistics for company workers metrics in the specified time range
|
||||
Returned as date histograms for different aggregation types
|
||||
grouped by worker, metric type (and optionally metric variant)
|
||||
Buckets with no metrics are not returned
|
||||
Note: all the statistics are retrieved as one ES query
|
||||
"""
|
||||
if request.from_date >= request.to_date:
|
||||
raise bad_request.FieldsValueError("from_date must be less than to_date")
|
||||
|
||||
def get_dates_agg() -> dict:
|
||||
es_to_agg_types = (
|
||||
("avg", AggregationType.avg.value),
|
||||
("min", AggregationType.min.value),
|
||||
("max", AggregationType.max.value),
|
||||
)
|
||||
|
||||
return {
|
||||
"dates": {
|
||||
"date_histogram": {
|
||||
"field": "timestamp",
|
||||
"fixed_interval": f"{request.interval}s",
|
||||
"min_doc_count": 1,
|
||||
},
|
||||
"aggs": {
|
||||
agg_type: {es_agg: {"field": "value"}}
|
||||
for es_agg, agg_type in es_to_agg_types
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
def get_variants_agg() -> dict:
|
||||
return {
|
||||
"variants": {"terms": {"field": "variant"}, "aggs": get_dates_agg()}
|
||||
}
|
||||
|
||||
es_req = {
|
||||
"size": 0,
|
||||
"aggs": {
|
||||
"workers": {
|
||||
"terms": {"field": "worker"},
|
||||
"aggs": {
|
||||
"metrics": {
|
||||
"terms": {"field": "metric"},
|
||||
"aggs": get_variants_agg()
|
||||
if request.split_by_variant
|
||||
else get_dates_agg(),
|
||||
}
|
||||
},
|
||||
}
|
||||
},
|
||||
}
|
||||
|
||||
query_terms = [
|
||||
QueryBuilder.dates_range(request.from_date, request.to_date),
|
||||
QueryBuilder.terms("metric", {item.key for item in request.items}),
|
||||
]
|
||||
if request.worker_ids:
|
||||
query_terms.append(QueryBuilder.terms("worker", request.worker_ids))
|
||||
es_req["query"] = {"bool": {"must": query_terms}}
|
||||
|
||||
with translate_errors_context(), TimingContext("es", "get_worker_stats"):
|
||||
data = self._search_company_stats(company_id, es_req)
|
||||
|
||||
return self._extract_results(data, request.items, request.split_by_variant)
|
||||
|
||||
@staticmethod
|
||||
def _extract_results(
|
||||
data: dict, request_items: Sequence[StatItem], split_by_variant: bool
|
||||
) -> dict:
|
||||
"""
|
||||
Clean results returned from elastic search (remove "aggregations", "buckets" etc.),
|
||||
leave only aggregation types requested by the user and return a clean dictionary
|
||||
and return a "clean" dictionary of
|
||||
:param data: aggregation data retrieved from ES
|
||||
:param request_items: aggs types requested by the user
|
||||
:param split_by_variant: if False then aggregate by metric type, otherwise metric type + variant
|
||||
"""
|
||||
if "aggregations" not in data:
|
||||
return {}
|
||||
|
||||
items_by_key = bucketize(request_items, key=attrgetter("key"))
|
||||
aggs_per_metric = {
|
||||
key: [item.aggregation for item in items]
|
||||
for key, items in items_by_key.items()
|
||||
}
|
||||
|
||||
def extract_date_stats(date: dict, metric_key) -> dict:
|
||||
return {
|
||||
"date": date["key"],
|
||||
"count": date["doc_count"],
|
||||
**{agg: date[agg]["value"] for agg in aggs_per_metric[metric_key]},
|
||||
}
|
||||
|
||||
def extract_metric_results(
|
||||
metric_or_variant: dict, metric_key: str
|
||||
) -> Sequence[dict]:
|
||||
return [
|
||||
extract_date_stats(date, metric_key)
|
||||
for date in metric_or_variant["dates"]["buckets"]
|
||||
if date["doc_count"]
|
||||
]
|
||||
|
||||
def extract_variant_results(metric: dict) -> dict:
|
||||
metric_key = metric["key"]
|
||||
return {
|
||||
variant["key"]: extract_metric_results(variant, metric_key)
|
||||
for variant in metric["variants"]["buckets"]
|
||||
}
|
||||
|
||||
def extract_worker_results(worker: dict) -> dict:
|
||||
return {
|
||||
metric["key"]: extract_variant_results(metric)
|
||||
if split_by_variant
|
||||
else extract_metric_results(metric, metric["key"])
|
||||
for metric in worker["metrics"]["buckets"]
|
||||
}
|
||||
|
||||
return {
|
||||
worker["key"]: extract_worker_results(worker)
|
||||
for worker in data["aggregations"]["workers"]["buckets"]
|
||||
}
|
||||
|
||||
def get_activity_report(
|
||||
self,
|
||||
company_id: str,
|
||||
from_date: float,
|
||||
to_date: float,
|
||||
interval: int,
|
||||
active_only: bool,
|
||||
) -> Sequence[dict]:
|
||||
"""
|
||||
Get statistics for company workers metrics in the specified time range
|
||||
Returned as date histograms for different aggregation types
|
||||
grouped by worker, metric type (and optionally metric variant)
|
||||
Note: all the statistics are retrieved using one ES query
|
||||
"""
|
||||
if from_date >= to_date:
|
||||
raise bad_request.FieldsValueError("from_date must be less than to_date")
|
||||
|
||||
must = [QueryBuilder.dates_range(from_date, to_date)]
|
||||
if active_only:
|
||||
must.append({"exists": {"field": "task"}})
|
||||
|
||||
es_req = {
|
||||
"size": 0,
|
||||
"aggs": {
|
||||
"dates": {
|
||||
"date_histogram": {
|
||||
"field": "timestamp",
|
||||
"fixed_interval": f"{interval}s",
|
||||
},
|
||||
"aggs": {"workers_count": {"cardinality": {"field": "worker"}}},
|
||||
}
|
||||
},
|
||||
"query": {"bool": {"must": must}},
|
||||
}
|
||||
|
||||
with translate_errors_context(), TimingContext(
|
||||
"es", "get_worker_activity_report"
|
||||
):
|
||||
data = self._search_company_stats(company_id, es_req)
|
||||
|
||||
if "aggregations" not in data:
|
||||
return {}
|
||||
|
||||
ret = [
|
||||
dict(date=date["key"], count=date["workers_count"]["value"])
|
||||
for date in data["aggregations"]["dates"]["buckets"]
|
||||
]
|
||||
|
||||
if ret and ret[-1]["date"] > (to_date - 0.9 * interval):
|
||||
# remove last interval if it's incomplete. Allow 10% tolerance
|
||||
ret.pop()
|
||||
|
||||
return ret
|
||||
Reference in New Issue
Block a user