-
Notifications
You must be signed in to change notification settings - Fork 591
Expand file tree
/
Copy path_span_batcher.py
More file actions
154 lines (127 loc) · 5.57 KB
/
_span_batcher.py
File metadata and controls
154 lines (127 loc) · 5.57 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
import threading
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.traces import StreamedSpan
class SpanBatcher(Batcher["StreamedSpan"]):
# MAX_BEFORE_FLUSH should be lower than MAX_BEFORE_DROP, so that there is
# a bit of a buffer for spans that appear between setting the flush event
# and actually flushing the buffer.
#
# The max limits are all per trace.
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["StreamedSpan"]] = 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._flush_event: "threading.Event" = threading.Event()
self._flusher: "Optional[threading.Thread]" = None
self._flusher_pid: "Optional[int]" = None
def add(self, span: "StreamedSpan") -> None:
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:
self._flush_event.set()
return
if self._running_size[span.trace_id] >= self.MAX_BYTES_BEFORE_FLUSH:
self._flush_event.set()
return
@staticmethod
def _estimate_size(item: "StreamedSpan") -> int:
# Rough estimate of serialized span size that's quick to compute.
# 210 is the rough size of the payload without attributes, and we
# estimate additional 70 bytes on top of that per attribute.
return 210 + 70 * len(item._attributes)
@staticmethod
def _to_transport_format(item: "StreamedSpan") -> "Any":
res: "dict[str, Any]" = {
"trace_id": item.trace_id,
"span_id": item.span_id,
"name": item._name,
"status": item._status,
"is_segment": item._is_segment(),
"start_timestamp": item._start_timestamp.timestamp(),
}
if item._timestamp:
res["end_timestamp"] = item._timestamp.timestamp()
if item._parent_span_id:
res["parent_span_id"] = item._parent_span_id
if item._attributes:
res["attributes"] = {
k: serialize_attribute(v) for (k, v) in item._attributes.items()
}
return res
def _flush(self) -> None:
with self._lock:
if len(self._span_buffer) == 0:
return
envelopes = []
for spans in self._span_buffer.values():
if spans:
dsc = spans[0]._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={
"items": [
self._to_transport_format(spans[j])
for j in range(start, end)
]
}
),
)
)
envelopes.append(envelope)
self._span_buffer.clear()
self._running_size.clear()
for envelope in envelopes:
self._capture_func(envelope)