Viewing file:  multiprocess.py (6.32 KB) -rw-r--r--
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from __future__ import unicode_literals
from collections import defaultdict
import glob
import json
import os
from .metrics_core import Metric
from .mmap_dict import MmapedDict
from .samples import Sample
from .utils import floatToGoString
try: # Python3
FileNotFoundError
except NameError: # Python >= 2.5
FileNotFoundError = IOError
MP_METRIC_HELP = 'Multiprocess metric'
class MultiProcessCollector(object):
"""Collector for files for multi-process mode."""
def __init__(self, registry, path=None):
if path is None:
path = os.environ.get('prometheus_multiproc_dir')
if not path or not os.path.isdir(path):
raise ValueError('env prometheus_multiproc_dir is not set or not a directory')
self._path = path
if registry:
registry.register(self)
@staticmethod
def merge(files, accumulate=True):
"""Merge metrics from given mmap files.
By default, histograms are accumulated, as per prometheus wire format.
But if writing the merged data back to mmap files, use
accumulate=False to avoid compound accumulation.
"""
metrics = MultiProcessCollector._read_metrics(files)
return MultiProcessCollector._accumulate_metrics(metrics, accumulate)
@staticmethod
def _read_metrics(files):
metrics = {}
key_cache = {}
def _parse_key(key):
val = key_cache.get(key)
if not val:
metric_name, name, labels = json.loads(key)
labels_key = tuple(sorted(labels.items()))
val = key_cache[key] = (metric_name, name, labels, labels_key)
return val
for f in files:
parts = os.path.basename(f).split('_')
typ = parts[0]
try:
file_values = MmapedDict.read_all_values_from_file(f)
except FileNotFoundError:
if typ == 'gauge' and parts[1] in ('liveall', 'livesum'):
# Those files can disappear between the glob of collect
# and now (via a mark_process_dead call) so don't fail if
# the file is missing
continue
raise
for key, value, pos in file_values:
metric_name, name, labels, labels_key = _parse_key(key)
metric = metrics.get(metric_name)
if metric is None:
metric = Metric(metric_name, MP_METRIC_HELP, typ)
metrics[metric_name] = metric
if typ == 'gauge':
pid = parts[2][:-3]
metric._multiprocess_mode = parts[1]
metric.add_sample(name, labels_key + (('pid', pid),), value)
else:
# The duplicates and labels are fixed in the next for.
metric.add_sample(name, labels_key, value)
return metrics
@staticmethod
def _accumulate_metrics(metrics, accumulate):
for metric in metrics.values():
samples = defaultdict(float)
buckets = defaultdict(lambda: defaultdict(float))
samples_setdefault = samples.setdefault
for s in metric.samples:
name, labels, value, timestamp, exemplar = s
if metric.type == 'gauge':
without_pid_key = (name, tuple([l for l in labels if l[0] != 'pid']))
if metric._multiprocess_mode == 'min':
current = samples_setdefault(without_pid_key, value)
if value < current:
samples[without_pid_key] = value
elif metric._multiprocess_mode == 'max':
current = samples_setdefault(without_pid_key, value)
if value > current:
samples[without_pid_key] = value
elif metric._multiprocess_mode == 'livesum':
samples[without_pid_key] += value
else: # all/liveall
samples[(name, labels)] = value
elif metric.type == 'histogram':
# A for loop with early exit is faster than a genexpr
# or a listcomp that ends up building unnecessary things
for l in labels:
if l[0] == 'le':
bucket_value = float(l[1])
# _bucket
without_le = tuple(l for l in labels if l[0] != 'le')
buckets[without_le][bucket_value] += value
break
else: # did not find the `le` key
# _sum/_count
samples[(name, labels)] += value
else:
# Counter and Summary.
samples[(name, labels)] += value
# Accumulate bucket values.
if metric.type == 'histogram':
for labels, values in buckets.items():
acc = 0.0
for bucket, value in sorted(values.items()):
sample_key = (
metric.name + '_bucket',
labels + (('le', floatToGoString(bucket)),),
)
if accumulate:
acc += value
samples[sample_key] = acc
else:
samples[sample_key] = value
if accumulate:
samples[(metric.name + '_count', labels)] = acc
# Convert to correct sample format.
metric.samples = [Sample(name_, dict(labels), value) for (name_, labels), value in samples.items()]
return metrics.values()
def collect(self):
files = glob.glob(os.path.join(self._path, '*.db'))
return self.merge(files, accumulate=True)
def mark_process_dead(pid, path=None):
"""Do bookkeeping for when one process dies in a multi-process setup."""
if path is None:
path = os.environ.get('prometheus_multiproc_dir')
for f in glob.glob(os.path.join(path, 'gauge_livesum_{0}.db'.format(pid))):
os.remove(f)
for f in glob.glob(os.path.join(path, 'gauge_liveall_{0}.db'.format(pid))):
os.remove(f)
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