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Editing: _span_batcher.py
import os import random import threading import time import weakref from collections import defaultdict from datetime import datetime, timezone from typing import TYPE_CHECKING from sentry_sdk._batcher import Batcher from sentry_sdk.envelope import Envelope, Item, PayloadRef from sentry_sdk.utils import format_timestamp, serialize_attribute if TYPE_CHECKING: from typing import Any, Callable, Optional from sentry_sdk._types import SpanJSON class SpanBatcher(Batcher["SpanJSON"]): # MAX_BEFORE_FLUSH should be lower than MAX_BEFORE_DROP, so that there is # a bit of a buffer for spans that appear between the trigger to flush # and actually flushing the buffer. # # The max limits are all per trace (per bucket). MAX_ENVELOPE_SIZE = 1000 # spans MAX_BEFORE_FLUSH = 1000 MAX_BEFORE_DROP = 2000 MAX_BYTES_BEFORE_FLUSH = 5 * 1024 * 1024 # 5 MB FLUSH_WAIT_TIME = 5.0 TYPE = "span" CONTENT_TYPE = "application/vnd.sentry.items.span.v2+json" def __init__( self, capture_func: "Callable[[Envelope], None]", record_lost_func: "Callable[..., None]", ) -> None: # Spans from different traces cannot be emitted in the same envelope # since the envelope contains a shared trace header. That's why we bucket # by trace_id, so that we can then send the buckets each in its own # envelope. # trace_id -> span buffer self._span_buffer: dict[str, list["SpanJSON"]] = defaultdict(list) self._running_size: dict[str, int] = defaultdict(lambda: 0) self._capture_func = capture_func self._record_lost_func = record_lost_func self._running = True self._lock = threading.Lock() self._active: "threading.local" = threading.local() self._last_full_flush: float = time.monotonic() # drives time-based flushes self._flush_event = threading.Event() self._pending_flush: set[str] = set() # buckets to be flushed self._flusher: "Optional[threading.Thread]" = None self._flusher_pid: "Optional[int]" = None # See https://github.com/getsentry/sentry-python/blob/051cc01640a29bfd64b1f1e2e3414c02f027dd1b/sentry_sdk/monitor.py#L41-L50 if hasattr(os, "register_at_fork"): weak_reset = weakref.WeakMethod(self._reset_thread_state) def _reset_in_child() -> None: method = weak_reset() if method is not None: method() os.register_at_fork(after_in_child=_reset_in_child) def _reset_thread_state(self) -> None: self._span_buffer = defaultdict(list) self._running_size = defaultdict(lambda: 0) self._running = True self._lock = threading.Lock() self._active = threading.local() self._last_full_flush = time.monotonic() self._flush_event = threading.Event() self._pending_flush = set() self._flusher = None self._flusher_pid = None def _flush_loop(self) -> None: self._active.flag = True while self._running: jitter = random.random() * self.FLUSH_WAIT_TIME * 0.1 self._flush_event.wait(timeout=self.FLUSH_WAIT_TIME + jitter) self._flush_event.clear() self._flush(only_pending=True) if ( time.monotonic() - self._last_full_flush >= self.FLUSH_WAIT_TIME + jitter ): self._flush() self._last_full_flush = time.monotonic() def add(self, span: "SpanJSON") -> None: # Bail out if the current thread is already executing batcher code. # This prevents deadlocks when code running inside the batcher (e.g. # _add_to_envelope during flush, or _flush_event.wait/set) triggers # a GC-emitted warning that routes back through the logging # integration into add(). if getattr(self._active, "flag", False): return None self._active.flag = True try: if not self._ensure_thread() or self._flusher is None: return None with self._lock: size = len(self._span_buffer[span["trace_id"]]) if size >= self.MAX_BEFORE_DROP: self._record_lost_func( reason="queue_overflow", data_category="span", quantity=1, ) return None self._span_buffer[span["trace_id"]].append(span) self._running_size[span["trace_id"]] += self._estimate_size(span) if ( size + 1 >= self.MAX_BEFORE_FLUSH or self._running_size[span["trace_id"]] >= self.MAX_BYTES_BEFORE_FLUSH ): self._pending_flush.add(span["trace_id"]) notify = True else: notify = False if notify: self._flush_event.set() finally: self._active.flag = False @staticmethod def _estimate_size(item: "SpanJSON") -> int: # Rough estimate of serialized span size that's quick to compute. # 210 is the rough size of the payload without attributes, and then we # estimate the attributes separately. estimate = 210 for value in (item.get("attributes") or {}).values(): estimate += 50 if isinstance(value, str): estimate += len(value) else: estimate += len(str(value)) return estimate @staticmethod def _to_transport_format(item: "SpanJSON") -> "Any": res = {k: v for k, v in item.items() if k not in ("_segment_span",)} if item.get("attributes"): res["attributes"] = { k: serialize_attribute(v) for (k, v) in item["attributes"].items() } else: del res["attributes"] return res def _flush(self, only_pending: bool = False) -> None: with self._lock: if only_pending: buckets = list(self._pending_flush) else: # flush whole buffer, e.g. if the SDK is shutting down buckets = list(self._span_buffer.keys()) self._pending_flush.clear() if not buckets: return envelopes = [] for bucket_id in buckets: spans = self._span_buffer.get(bucket_id) if not spans: continue dsc = spans[0]["_segment_span"]._dynamic_sampling_context() # Max per envelope is 1000, so if we happen to have more than # 1000 spans in one bucket, we'll need to separate them. for start in range(0, len(spans), self.MAX_ENVELOPE_SIZE): end = min(start + self.MAX_ENVELOPE_SIZE, len(spans)) envelope = Envelope( headers={ "sent_at": format_timestamp(datetime.now(timezone.utc)), "trace": dsc, } ) envelope.add_item( Item( type=self.TYPE, content_type=self.CONTENT_TYPE, headers={ "item_count": end - start, }, payload=PayloadRef( json={ "version": 2, "items": [ self._to_transport_format(spans[j]) for j in range(start, end) ], } ), ) ) envelopes.append(envelope) del self._span_buffer[bucket_id] del self._running_size[bucket_id] for envelope in envelopes: self._capture_func(envelope)
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