# Copyright The OpenTelemetry Authors
#
# 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 collections
import logging
import os
import sys
import threading
import typing
from enum import Enum
from opentelemetry.configuration import Configuration
from opentelemetry.context import Context, attach, detach, set_value
from opentelemetry.sdk.trace import Span, SpanProcessor
from opentelemetry.util import time_ns
logger = logging.getLogger(__name__)
class SpanExportResult(Enum):
SUCCESS = 0
FAILURE = 1
class SpanExporter:
"""Interface for exporting spans.
Interface to be implemented by services that want to export recorded in
its own format.
To export data this MUST be registered to the :class`opentelemetry.sdk.trace.Tracer` using a
`SimpleExportSpanProcessor` or a `BatchExportSpanProcessor`.
"""
def export(self, spans: typing.Sequence[Span]) -> "SpanExportResult":
"""Exports a batch of telemetry data.
Args:
spans: The list of `opentelemetry.trace.Span` objects to be exported
Returns:
The result of the export
"""
def shutdown(self) -> None:
"""Shuts down the exporter.
Called when the SDK is shut down.
"""
class SimpleExportSpanProcessor(SpanProcessor):
"""Simple SpanProcessor implementation.
SimpleExportSpanProcessor is an implementation of `SpanProcessor` that
passes ended spans directly to the configured `SpanExporter`.
"""
def __init__(self, span_exporter: SpanExporter):
self.span_exporter = span_exporter
def on_start(
self, span: Span, parent_context: typing.Optional[Context] = None
) -> None:
pass
def on_end(self, span: Span) -> None:
if not span.context.trace_flags.sampled:
return
token = attach(set_value("suppress_instrumentation", True))
try:
self.span_exporter.export((span,))
# pylint: disable=broad-except
except Exception:
logger.exception("Exception while exporting Span.")
detach(token)
def shutdown(self) -> None:
self.span_exporter.shutdown()
def force_flush(self, timeout_millis: int = 30000) -> bool:
# pylint: disable=unused-argument
return True
class _FlushRequest:
"""Represents a request for the BatchExportSpanProcessor to flush spans."""
__slots__ = ["event", "num_spans"]
def __init__(self):
self.event = threading.Event()
self.num_spans = 0
class BatchExportSpanProcessor(SpanProcessor):
"""Batch span processor implementation.
BatchExportSpanProcessor is an implementation of `SpanProcessor` that
batches ended spans and pushes them to the configured `SpanExporter`.
"""
def __init__(
self,
span_exporter: SpanExporter,
max_queue_size: int = None,
schedule_delay_millis: float = None,
max_export_batch_size: int = None,
export_timeout_millis: float = None,
):
if max_queue_size is None:
max_queue_size = Configuration().get("BSP_MAX_QUEUE_SIZE", 2048)
if schedule_delay_millis is None:
schedule_delay_millis = Configuration().get(
"BSP_SCHEDULE_DELAY_MILLIS", 5000
)
if max_export_batch_size is None:
max_export_batch_size = Configuration().get(
"BSP_MAX_EXPORT_BATCH_SIZE", 512
)
if export_timeout_millis is None:
export_timeout_millis = Configuration().get(
"BSP_EXPORT_TIMEOUT_MILLIS", 30000
)
if max_queue_size <= 0:
raise ValueError("max_queue_size must be a positive integer.")
if schedule_delay_millis <= 0:
raise ValueError("schedule_delay_millis must be positive.")
if max_export_batch_size <= 0:
raise ValueError(
"max_export_batch_size must be a positive integer."
)
if max_export_batch_size > max_queue_size:
raise ValueError(
"max_export_batch_size must be less than or equal to max_queue_size."
)
self.span_exporter = span_exporter
self.queue = collections.deque(
[], max_queue_size
) # type: typing.Deque[Span]
self.worker_thread = threading.Thread(target=self.worker, daemon=True)
self.condition = threading.Condition(threading.Lock())
self._flush_request = None # type: typing.Optional[_FlushRequest]
self.schedule_delay_millis = schedule_delay_millis
self.max_export_batch_size = max_export_batch_size
self.max_queue_size = max_queue_size
self.export_timeout_millis = export_timeout_millis
self.done = False
# flag that indicates that spans are being dropped
self._spans_dropped = False
# precallocated list to send spans to exporter
self.spans_list = [
None
] * self.max_export_batch_size # type: typing.List[typing.Optional[Span]]
self.worker_thread.start()
def on_start(
self, span: Span, parent_context: typing.Optional[Context] = None
) -> None:
pass
def on_end(self, span: Span) -> None:
if self.done:
logger.warning("Already shutdown, dropping span.")
return
if not span.context.trace_flags.sampled:
return
if len(self.queue) == self.max_queue_size:
if not self._spans_dropped:
logger.warning("Queue is full, likely spans will be dropped.")
self._spans_dropped = True
self.queue.appendleft(span)
if len(self.queue) >= self.max_queue_size // 2:
with self.condition:
self.condition.notify()
def worker(self):
timeout = self.schedule_delay_millis / 1e3
flush_request = None # type: typing.Optional[_FlushRequest]
while not self.done:
with self.condition:
if self.done:
# done flag may have changed, avoid waiting
break
flush_request = self._get_and_unset_flush_request()
if (
len(self.queue) < self.max_export_batch_size
and flush_request is None
):
self.condition.wait(timeout)
flush_request = self._get_and_unset_flush_request()
if not self.queue:
# spurious notification, let's wait again, reset timeout
timeout = self.schedule_delay_millis / 1e3
self._notify_flush_request_finished(flush_request)
flush_request = None
continue
if self.done:
# missing spans will be sent when calling flush
break
# subtract the duration of this export call to the next timeout
start = time_ns()
self._export(flush_request)
end = time_ns()
duration = (end - start) / 1e9
timeout = self.schedule_delay_millis / 1e3 - duration
self._notify_flush_request_finished(flush_request)
flush_request = None
# there might have been a new flush request while export was running
# and before the done flag switched to true
with self.condition:
shutdown_flush_request = self._get_and_unset_flush_request()
# be sure that all spans are sent
self._drain_queue()
self._notify_flush_request_finished(flush_request)
self._notify_flush_request_finished(shutdown_flush_request)
def _get_and_unset_flush_request(self,) -> typing.Optional[_FlushRequest]:
"""Returns the current flush request and makes it invisible to the
worker thread for subsequent calls.
"""
flush_request = self._flush_request
self._flush_request = None
if flush_request is not None:
flush_request.num_spans = len(self.queue)
return flush_request
@staticmethod
def _notify_flush_request_finished(
flush_request: typing.Optional[_FlushRequest],
):
"""Notifies the flush initiator(s) waiting on the given request/event
that the flush operation was finished.
"""
if flush_request is not None:
flush_request.event.set()
def _get_or_create_flush_request(self) -> _FlushRequest:
"""Either returns the current active flush event or creates a new one.
The flush event will be visible and read by the worker thread before an
export operation starts. Callers of a flush operation may wait on the
returned event to be notified when the flush/export operation was
finished.
This method is not thread-safe, i.e. callers need to take care about
synchronization/locking.
"""
if self._flush_request is None:
self._flush_request = _FlushRequest()
return self._flush_request
def _export(self, flush_request: typing.Optional[_FlushRequest]):
"""Exports spans considering the given flush_request.
In case of a given flush_requests spans are exported in batches until
the number of exported spans reached or exceeded the number of spans in
the flush request.
In no flush_request was given at most max_export_batch_size spans are
exported.
"""
if not flush_request:
self._export_batch()
return
num_spans = flush_request.num_spans
while self.queue:
num_exported = self._export_batch()
num_spans -= num_exported
if num_spans <= 0:
break
def _export_batch(self) -> int:
"""Exports at most max_export_batch_size spans and returns the number of
exported spans.
"""
idx = 0
# currently only a single thread acts as consumer, so queue.pop() will
# not raise an exception
while idx < self.max_export_batch_size and self.queue:
self.spans_list[idx] = self.queue.pop()
idx += 1
token = attach(set_value("suppress_instrumentation", True))
try:
# Ignore type b/c the Optional[None]+slicing is too "clever"
# for mypy
self.span_exporter.export(self.spans_list[:idx]) # type: ignore
except Exception: # pylint: disable=broad-except
logger.exception("Exception while exporting Span batch.")
detach(token)
# clean up list
for index in range(idx):
self.spans_list[index] = None
return idx
def _drain_queue(self):
""""Export all elements until queue is empty.
Can only be called from the worker thread context because it invokes
`export` that is not thread safe.
"""
while self.queue:
self._export_batch()
def force_flush(self, timeout_millis: int = None) -> bool:
if timeout_millis is None:
timeout_millis = self.export_timeout_millis
if self.done:
logger.warning("Already shutdown, ignoring call to force_flush().")
return True
with self.condition:
flush_request = self._get_or_create_flush_request()
# signal the worker thread to flush and wait for it to finish
self.condition.notify_all()
# wait for token to be processed
ret = flush_request.event.wait(timeout_millis / 1e3)
if not ret:
logger.warning("Timeout was exceeded in force_flush().")
return ret
def shutdown(self) -> None:
# signal the worker thread to finish and then wait for it
self.done = True
with self.condition:
self.condition.notify_all()
self.worker_thread.join()
self.span_exporter.shutdown()
class ConsoleSpanExporter(SpanExporter):
"""Implementation of :class:`SpanExporter` that prints spans to the
console.
This class can be used for diagnostic purposes. It prints the exported
spans to the console STDOUT.
"""
def __init__(
self,
out: typing.IO = sys.stdout,
formatter: typing.Callable[[Span], str] = lambda span: span.to_json()
+ os.linesep,
):
self.out = out
self.formatter = formatter
def export(self, spans: typing.Sequence[Span]) -> SpanExportResult:
for span in spans:
self.out.write(self.formatter(span))
self.out.flush()
return SpanExportResult.SUCCESS