def __init__(self, max_workers=None, name='', trace=None,metrics_registry=None):
if trace is None:
self._trace = 'BGX_TRACE_LOGGING' in os.environ
else:
self._trace = trace
self._name = name
if name == '':
self._name = 'Instrumented'
LOGGER.debug('Creating thread pool executor %s', self._name)
self._old_workers_in_use = atomic.Counter()
self._max_workers = max_workers
if self._max_workers is None:
# This is the same default as ThreadPoolExecutor, but we want to
# know how many workers there are for logging
self._max_workers = multiprocessing.cpu_count() * 5
super().__init__(max_workers)
if metrics_registry:
self._task_time_in_queue_timer = TimerWrapper(metrics_registry.timer('threadpool.InstrumentedThreadPoolExecutor.task_time_in_queue', tags=['name={}'.format(self._name)]))
self._task_run_timer = TimerWrapper(metrics_registry.timer('threadpool.InstrumentedThreadPoolExecutor.task_run_time', tags=['name={}'.format(self._name)]))
self._workers_in_use = TimerWrapper(metrics_registry.timer('threadpool.InstrumentedThreadPoolExecutor.workers_in_use', tags=['name={}'.format(self._name)]))
else:
self._task_time_in_queue_timer = TimerWrapper()
self._task_run_timer = TimerWrapper()
self._workers_in_use = TimerWrapper()
def __init__(self,
max_workers=None,
name='',
trace=None,
metrics_registry=None):
if trace is None:
self._trace = 'SAWTOOTH_TRACE_LOGGING' in os.environ
else:
self._trace = trace
self._name = name
if name == '':
self._name = 'Instrumented'
LOGGER.debug('Creating thread pool executor %s', self._name)
self._workers_in_use = atomic.Counter()
self._max_workers = max_workers
if self._max_workers is None:
# This is the same default as ThreadPoolExecutor, but we want to
# know how many workers there are for logging
self._max_workers = multiprocessing.cpu_count() * 5
super().__init__(max_workers)
if metrics_registry:
# Tracks how many workers are already in use
self._workers_already_in_use_gauge = GaugeWrapper(
metrics_registry.gauge(
'{}-threadpool.workers_already_in_use'.format(self._name)))
# Tracks how long tasks take to run
self._task_run_timer = TimerWrapper(
metrics_registry.timer('{}-threadpool.task_run_time'.format(
self._name)))
# Tracks how long tasks wait in the queue
self._task_time_in_queue_timer = TimerWrapper(
metrics_registry.timer(
'{}-threadpool.task_time_in_queue'.format(self._name)))
else:
self._workers_already_in_use_gauge = GaugeWrapper()
self._task_run_timer = TimerWrapper()
self._task_time_in_queue_timer = TimerWrapper()
def __init__(self, max_workers=None, name='', trace=None):
if trace is None:
self._trace = 'SAWTOOTH_TRACE_LOGGING' in os.environ
else:
self._trace = trace
self._name = name
if name == '':
self._name = 'Instrumented'
LOGGER.debug('Creating thread pool executor %s', self._name)
self._workers_in_use = atomic.Counter()
self._max_workers = max_workers
if self._max_workers is None:
# This is the same default as ThreadPoolExecutor, but we want to
# know how many workers there are for logging
self._max_workers = multiprocessing.cpu_count() * 5
super().__init__(max_workers)