anonymousland-synapse/synapse/metrics/__init__.py
Vincent Breitmoser 6d7f0f8dd3 Don't disable GC when running on PyPy
PyPy's incminimark GC can't be triggered manually. From what I observed
there are no obvious issues with just letting it run normally. And
unlike CPython, it actually returns unused RAM to the system.

Signed-off-by: Vincent Breitmoser <look@my.amazin.horse>
2018-04-10 11:35:34 +02:00

218 lines
6.2 KiB
Python

# -*- coding: utf-8 -*-
# Copyright 2015, 2016 OpenMarket Ltd
#
# 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.
import logging
import functools
import time
import gc
import platform
from twisted.internet import reactor
from .metric import (
CounterMetric, CallbackMetric, DistributionMetric, CacheMetric,
MemoryUsageMetric,
)
from .process_collector import register_process_collector
logger = logging.getLogger(__name__)
running_on_pypy = platform.python_implementation() == 'PyPy'
all_metrics = []
all_collectors = []
class Metrics(object):
""" A single Metrics object gives a (mutable) slice view of the all_metrics
dict, allowing callers to easily register new metrics that are namespaced
nicely."""
def __init__(self, name):
self.name_prefix = name
def make_subspace(self, name):
return Metrics("%s_%s" % (self.name_prefix, name))
def register_collector(self, func):
all_collectors.append(func)
def _register(self, metric_class, name, *args, **kwargs):
full_name = "%s_%s" % (self.name_prefix, name)
metric = metric_class(full_name, *args, **kwargs)
all_metrics.append(metric)
return metric
def register_counter(self, *args, **kwargs):
"""
Returns:
CounterMetric
"""
return self._register(CounterMetric, *args, **kwargs)
def register_callback(self, *args, **kwargs):
"""
Returns:
CallbackMetric
"""
return self._register(CallbackMetric, *args, **kwargs)
def register_distribution(self, *args, **kwargs):
"""
Returns:
DistributionMetric
"""
return self._register(DistributionMetric, *args, **kwargs)
def register_cache(self, *args, **kwargs):
"""
Returns:
CacheMetric
"""
return self._register(CacheMetric, *args, **kwargs)
def register_memory_metrics(hs):
try:
import psutil
process = psutil.Process()
process.memory_info().rss
except (ImportError, AttributeError):
logger.warn(
"psutil is not installed or incorrect version."
" Disabling memory metrics."
)
return
metric = MemoryUsageMetric(hs, psutil)
all_metrics.append(metric)
def get_metrics_for(pkg_name):
""" Returns a Metrics instance for conveniently creating metrics
namespaced with the given name prefix. """
# Convert a "package.name" to "package_name" because Prometheus doesn't
# let us use . in metric names
return Metrics(pkg_name.replace(".", "_"))
def render_all():
strs = []
for collector in all_collectors:
collector()
for metric in all_metrics:
try:
strs += metric.render()
except Exception:
strs += ["# FAILED to render"]
logger.exception("Failed to render metric")
strs.append("") # to generate a final CRLF
return "\n".join(strs)
register_process_collector(get_metrics_for("process"))
python_metrics = get_metrics_for("python")
gc_time = python_metrics.register_distribution("gc_time", labels=["gen"])
gc_unreachable = python_metrics.register_counter("gc_unreachable_total", labels=["gen"])
python_metrics.register_callback(
"gc_counts", lambda: {(i,): v for i, v in enumerate(gc.get_count())}, labels=["gen"]
)
reactor_metrics = get_metrics_for("python.twisted.reactor")
tick_time = reactor_metrics.register_distribution("tick_time")
pending_calls_metric = reactor_metrics.register_distribution("pending_calls")
def runUntilCurrentTimer(func):
@functools.wraps(func)
def f(*args, **kwargs):
now = reactor.seconds()
num_pending = 0
# _newTimedCalls is one long list of *all* pending calls. Below loop
# is based off of impl of reactor.runUntilCurrent
for delayed_call in reactor._newTimedCalls:
if delayed_call.time > now:
break
if delayed_call.delayed_time > 0:
continue
num_pending += 1
num_pending += len(reactor.threadCallQueue)
start = time.time() * 1000
ret = func(*args, **kwargs)
end = time.time() * 1000
# record the amount of wallclock time spent running pending calls.
# This is a proxy for the actual amount of time between reactor polls,
# since about 25% of time is actually spent running things triggered by
# I/O events, but that is harder to capture without rewriting half the
# reactor.
tick_time.inc_by(end - start)
pending_calls_metric.inc_by(num_pending)
if running_on_pypy:
return ret
# Check if we need to do a manual GC (since its been disabled), and do
# one if necessary.
threshold = gc.get_threshold()
counts = gc.get_count()
for i in (2, 1, 0):
if threshold[i] < counts[i]:
logger.info("Collecting gc %d", i)
start = time.time() * 1000
unreachable = gc.collect(i)
end = time.time() * 1000
gc_time.inc_by(end - start, i)
gc_unreachable.inc_by(unreachable, i)
return ret
return f
try:
# Ensure the reactor has all the attributes we expect
reactor.runUntilCurrent
reactor._newTimedCalls
reactor.threadCallQueue
# runUntilCurrent is called when we have pending calls. It is called once
# per iteratation after fd polling.
reactor.runUntilCurrent = runUntilCurrentTimer(reactor.runUntilCurrent)
# We manually run the GC each reactor tick so that we can get some metrics
# about time spent doing GC,
if not running_on_pypy:
gc.disable()
except AttributeError:
pass