8000 Use `collections.defaultdict` to speed up metrics aggregation by umax · Pull Request #257 · prometheus/client_python · GitHub
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Use collections.defaultdict to speed up metrics aggregation #257

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merged 1 commit into from
Mar 21, 2018
Merged

Use collections.defaultdict to speed up metrics aggregation #257

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23 changes: 12 additions & 11 deletions prometheus_client/multiprocess.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,8 @@

from __future__ import unicode_literals

from collections import defaultdict

import glob
import json
import os
Expand Down Expand Up @@ -44,39 +46,38 @@ def collect(self):
d.close()

for metric in metrics.values():
samples = {}
samples = defaultdict(float)
buckets = {}
for name, labels, value in metric.samples:
if metric.type == 'gauge':
without_pid = tuple([l for l in labels if l[0] != 'pid'])
without_pid = tuple(l for l in labels if l[0] != 'pid')
if metric._multiprocess_mode == 'min':
samples.setdefault((name, without_pid), value)
if samples[(name, without_pid)] > value:
current = samples.setdefault((name, without_pid), value)
if value < current:
samples[(name, without_pid)] = value
elif metric._multiprocess_mode == 'max':
samples.setdefault((name, without_pid), value)
if samples[(name, without_pid)] < value:
current = samples.setdefault((name, without_pid), value)
if value > current:
samples[(name, without_pid)] = value
elif metric._multiprocess_mode == 'livesum':
samples.setdefault((name, without_pid), 0.0)
samples[(name, without_pid)] += value
else: # all/liveall
samples[(name, labels)] = value

elif metric.type == 'histogram':
bucket = [float(l[1]) for l in labels if l[0] == 'le']
bucket = tuple(float(l[1]) for l in labels if l[0] == 'le')
if bucket:
# _bucket
without_le = tuple([l for l in labels if l[0] != 'le'])
without_le = tuple(l for l in labels if l[0] != 'le')
buckets.setdefault(without_le, {})
buckets[without_le].setdefault(bucket[0], 0.0)
buckets[without_le][bucket[0]] += value
else:
# _sum/_count
samples.setdefault((name, labels), 0.0)
samples[(name, labels)] += value

else:
# Counter and Summary.
samples.setdefault((name, labels), 0.0)
samples[(name, labels)] += value

# Accumulate bucket values.
Expand Down
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