def replacer(replacements_topic, consumer_group, bootstrap_server,
clickhouse_server, distributed_table_name, max_batch_size,
max_batch_time_ms, auto_offset_reset, queued_max_messages_kbytes,
queued_min_messages, log_level, dogstatsd_host, dogstatsd_port):
import sentry_sdk
from snuba import util
from snuba.clickhouse import ClickhousePool
from batching_kafka_consumer import BatchingKafkaConsumer
from snuba.replacer import ReplacerWorker
sentry_sdk.init(dsn=settings.SENTRY_DSN)
logging.basicConfig(level=getattr(logging, log_level.upper()),
format='%(asctime)s %(message)s')
metrics = util.create_metrics(dogstatsd_host,
dogstatsd_port,
'snuba.replacer',
tags=["group:%s" % consumer_group])
client_settings = {
# Replacing existing rows requires reconstructing the entire tuple for each
# event (via a SELECT), which is a Hard Thing (TM) for columnstores to do. With
# the default settings it's common for ClickHouse to go over the default max_memory_usage
# of 10GB per query. Lowering the max_block_size reduces memory usage, and increasing the
# max_memory_usage gives the query more breathing room.
'max_block_size': settings.REPLACER_MAX_BLOCK_SIZE,
'max_memory_usage': settings.REPLACER_MAX_MEMORY_USAGE,
# Don't use up production cache for the count() queries.
'use_uncompressed_cache': 0,
}
clickhouse = ClickhousePool(
host=clickhouse_server.split(':')[0],
port=int(clickhouse_server.split(':')[1]),
client_settings=client_settings,
)
replacer = BatchingKafkaConsumer(
replacements_topic,
worker=ReplacerWorker(clickhouse,
distributed_table_name,
metrics=metrics),
max_batch_size=max_batch_size,
max_batch_time=max_batch_time_ms,
metrics=metrics,
bootstrap_servers=bootstrap_server,
group_id=consumer_group,
producer=None,
commit_log_topic=None,
auto_offset_reset=auto_offset_reset,
)
def handler(signum, frame):
replacer.signal_shutdown()
signal.signal(signal.SIGINT, handler)
replacer.run()
def consumer(raw_events_topic, replacements_topic, commit_log_topic, consumer_group,
bootstrap_server, clickhouse_server, distributed_table_name, max_batch_size, max_batch_time_ms,
auto_offset_reset, queued_max_messages_kbytes, queued_min_messages, log_level,
dogstatsd_host, dogstatsd_port):
import sentry_sdk
from snuba import util
from snuba.clickhouse import ClickhousePool
from batching_kafka_consumer import BatchingKafkaConsumer
from snuba.consumer import ConsumerWorker
sentry_sdk.init(dsn=settings.SENTRY_DSN)
logging.basicConfig(level=getattr(logging, log_level.upper()), format='%(asctime)s %(message)s')
metrics = util.create_metrics(
dogstatsd_host, dogstatsd_port, 'snuba.consumer', tags=["group:%s" % consumer_group]
)
clickhouse = ClickhousePool(
host=clickhouse_server.split(':')[0],
port=int(clickhouse_server.split(':')[1]),
client_settings={
'load_balancing': 'in_order',
'insert_distributed_sync': True,
},
metrics=metrics
)
producer = Producer({
'bootstrap.servers': ','.join(bootstrap_server),
'partitioner': 'consistent',
'message.max.bytes': 50000000, # 50MB, default is 1MB
})
consumer = BatchingKafkaConsumer(
raw_events_topic,
worker=ConsumerWorker(
clickhouse, distributed_table_name,
producer=producer, replacements_topic=replacements_topic, metrics=metrics
),
max_batch_size=max_batch_size,
max_batch_time=max_batch_time_ms,
metrics=metrics,
bootstrap_servers=bootstrap_server,
group_id=consumer_group,
producer=producer,
commit_log_topic=commit_log_topic,
auto_offset_reset=auto_offset_reset,
)
def handler(signum, frame):
consumer.signal_shutdown()
signal.signal(signal.SIGINT, handler)
consumer.run()
def __init__(self, dataset_name: str, raw_topic: str,
replacements_topic: str, max_batch_size: int,
max_batch_time_ms: int, bootstrap_servers: Sequence[str],
group_id: str, commit_log_topic: str, auto_offset_reset: str,
queued_max_messages_kbytes: int, queued_min_messages: int,
dogstatsd_host: str, dogstatsd_port: int) -> None:
self.dataset = get_dataset(dataset_name)
self.dataset_name = dataset_name
if not bootstrap_servers:
self.bootstrap_servers = settings.DEFAULT_DATASET_BROKERS.get(
dataset_name,
settings.DEFAULT_BROKERS,
)
else:
self.bootstrap_servers = bootstrap_servers
stream_loader = enforce_table_writer(self.dataset).get_stream_loader()
self.raw_topic = raw_topic or stream_loader.get_default_topic_spec(
).topic_name
default_replacement_topic_name = stream_loader.get_replacement_topic_spec().topic_name \
if stream_loader.get_replacement_topic_spec() \
else None
self.replacements_topic = replacements_topic or default_replacement_topic_name
default_commit_log_topic_name = stream_loader.get_commit_log_topic_spec().topic_name \
if stream_loader.get_commit_log_topic_spec() \
else None
self.commit_log_topic = commit_log_topic or default_commit_log_topic_name
# XXX: This can result in a producer being built in cases where it's
# not actually required.
self.producer = Producer({
'bootstrap.servers':
','.join(self.bootstrap_servers),
'partitioner':
'consistent',
'message.max.bytes':
50000000, # 50MB, default is 1MB
})
self.metrics = util.create_metrics(dogstatsd_host,
dogstatsd_port,
'snuba.consumer',
tags={
"group": group_id,
"dataset": self.dataset_name,
})
self.max_batch_size = max_batch_size
self.max_batch_time_ms = max_batch_time_ms
self.group_id = group_id
self.auto_offset_reset = auto_offset_reset
self.queued_max_messages_kbytes = queued_max_messages_kbytes
self.queued_min_messages = queued_min_messages
def __init__(self, dataset_name: str, raw_topic: str,
replacements_topic: str, max_batch_size: int,
max_batch_time_ms: int, bootstrap_servers: Sequence[str],
group_id: str, commit_log_topic: str, auto_offset_reset: str,
queued_max_messages_kbytes: int, queued_min_messages: int,
dogstatsd_host: str, dogstatsd_port: int) -> None:
self.dataset = get_dataset(dataset_name)
self.dataset_name = dataset_name
if not bootstrap_servers:
self.bootstrap_servers = settings.DEFAULT_DATASET_BROKERS.get(
dataset_name,
settings.DEFAULT_BROKERS,
)
else:
self.bootstrap_servers = bootstrap_servers
self.raw_topic = raw_topic or self.dataset.get_default_topic()
self.replacements_topic = replacements_topic or self.dataset.get_default_replacement_topic(
)
self.commit_log_topic = commit_log_topic or self.dataset.get_default_commit_log_topic(
)
self.producer = Producer({
'bootstrap.servers':
','.join(self.bootstrap_servers),
'partitioner':
'consistent',
'message.max.bytes':
50000000, # 50MB, default is 1MB
})
self.metrics = util.create_metrics(dogstatsd_host,
dogstatsd_port,
'snuba.consumer',
tags=[
"group:%s" % group_id,
"dataset:%s" %
self.dataset_name,
])
self.max_batch_size = max_batch_size
self.max_batch_time_ms = max_batch_time_ms
self.group_id = group_id
self.auto_offset_reset = auto_offset_reset
self.queued_max_messages_kbytes = queued_max_messages_kbytes
self.queued_min_messages = queued_min_messages
from snuba.redis import redis_client
from snuba.request import Request
from snuba.state.cache import Cache, RedisCache
from snuba.state.rate_limit import (
PROJECT_RATE_LIMIT_NAME,
RateLimitAggregator,
RateLimitExceeded,
)
from snuba.util import create_metrics, force_bytes
from snuba.utils.codecs import JSONCodec
from snuba.utils.metrics.timer import Timer
from snuba.web.split import split_query
logger = logging.getLogger("snuba.query")
metrics = create_metrics("snuba.api")
ClickhouseQueryResult = MutableMapping[str, MutableMapping[str, Any]]
class RawQueryException(Exception):
def __init__(
self, err_type: str, message: str, stats: Mapping[str, Any], sql: str, **meta
):
self.err_type = err_type
self.message = message
self.stats = stats
self.sql = sql
self.meta = meta
def subscriptions(
*,
dataset_name: str,
topic: Optional[str],
partitions: Optional[int],
commit_log_topic: Optional[str],
commit_log_groups: Sequence[str],
consumer_group: str,
auto_offset_reset: str,
bootstrap_servers: Sequence[str],
max_batch_size: int,
max_batch_time_ms: int,
schedule_ttl: int,
result_topic: Optional[str],
log_level: Optional[str],
) -> None:
"""Evaluates subscribed queries for a dataset."""
assert result_topic is not None
setup_logging(log_level)
setup_sentry()
dataset = get_dataset(dataset_name)
if not bootstrap_servers:
bootstrap_servers = settings.DEFAULT_DATASET_BROKERS.get(
dataset_name, settings.DEFAULT_BROKERS
)
loader = enforce_table_writer(dataset).get_stream_loader()
consumer = TickConsumer(
SynchronizedConsumer(
KafkaConsumer(
build_kafka_consumer_configuration(
bootstrap_servers,
consumer_group,
auto_offset_reset=auto_offset_reset,
),
PassthroughCodec(),
),
KafkaConsumer(
build_kafka_consumer_configuration(
bootstrap_servers,
f"subscriptions-commit-log-{uuid.uuid1().hex}",
auto_offset_reset="earliest",
),
CommitCodec(),
),
(
Topic(commit_log_topic)
if commit_log_topic is not None
else Topic(loader.get_commit_log_topic_spec().topic_name)
),
set(commit_log_groups),
)
)
producer = KafkaProducer(
{
"bootstrap.servers": ",".join(bootstrap_servers),
"partitioner": "consistent",
"message.max.bytes": 50000000, # 50MB, default is 1MB
},
SubscriptionResultCodec(),
)
with closing(consumer), closing(producer):
batching_consumer = BatchingConsumer(
consumer,
(
Topic(topic)
if topic is not None
else Topic(loader.get_default_topic_spec().topic_name)
),
SubscriptionWorker(
SubscriptionExecutor(
dataset,
ThreadPoolExecutor(
max_workers=settings.SUBSCRIPTIONS_MAX_CONCURRENT_QUERIES
),
),
{
index: SubscriptionScheduler(
RedisSubscriptionDataStore(
redis_client, dataset, PartitionId(index)
),
PartitionId(index),
cache_ttl=timedelta(seconds=schedule_ttl),
)
for index in range(
partitions
if partitions is not None
else loader.get_default_topic_spec().partitions_number
)
},
producer,
Topic(result_topic),
),
max_batch_size,
max_batch_time_ms,
create_metrics(
"snuba.subscriptions",
tags={"group": consumer_group, "dataset": dataset_name},
),
)
def handler(signum, frame) -> None:
batching_consumer.signal_shutdown()
signal.signal(signal.SIGINT, handler)
signal.signal(signal.SIGTERM, handler)
batching_consumer.run()
def replacer(
*,
replacements_topic: Optional[str],
consumer_group: str,
bootstrap_server: Sequence[str],
dataset_name: str,
max_batch_size: int,
max_batch_time_ms: int,
auto_offset_reset: str,
queued_max_messages_kbytes: int,
queued_min_messages: int,
log_level: Optional[str] = None,
) -> None:
from snuba import util
from snuba.clickhouse.native import ClickhousePool
from snuba.replacer import ReplacerWorker
from snuba.utils.codecs import PassthroughCodec
from snuba.utils.streams.batching import BatchingConsumer
from snuba.utils.streams.kafka import (
KafkaConsumer,
KafkaPayload,
TransportError,
build_kafka_consumer_configuration,
)
from snuba.utils.streams.types import Topic
setup_logging(log_level)
setup_sentry()
dataset = get_dataset(dataset_name)
stream_loader = enforce_table_writer(dataset).get_stream_loader()
default_replacement_topic_spec = stream_loader.get_replacement_topic_spec()
assert (
default_replacement_topic_spec
is not None), f"Dataset {dataset} does not have a replacement topic."
replacements_topic = replacements_topic or default_replacement_topic_spec.topic_name
metrics = util.create_metrics("snuba.replacer",
tags={"group": consumer_group})
client_settings = {
# Replacing existing rows requires reconstructing the entire tuple for each
# event (via a SELECT), which is a Hard Thing (TM) for columnstores to do. With
# the default settings it's common for ClickHouse to go over the default max_memory_usage
# of 10GB per query. Lowering the max_block_size reduces memory usage, and increasing the
# max_memory_usage gives the query more breathing room.
"max_block_size": settings.REPLACER_MAX_BLOCK_SIZE,
"max_memory_usage": settings.REPLACER_MAX_MEMORY_USAGE,
# Don't use up production cache for the count() queries.
"use_uncompressed_cache": 0,
}
clickhouse = ClickhousePool(
settings.CLICKHOUSE_HOST,
settings.CLICKHOUSE_PORT,
client_settings=client_settings,
)
codec: PassthroughCodec[KafkaPayload] = PassthroughCodec()
replacer = BatchingConsumer(
KafkaConsumer(
build_kafka_consumer_configuration(
bootstrap_servers=bootstrap_server,
group_id=consumer_group,
auto_offset_reset=auto_offset_reset,
queued_max_messages_kbytes=queued_max_messages_kbytes,
queued_min_messages=queued_min_messages,
),
codec=codec,
),
Topic(replacements_topic),
worker=ReplacerWorker(clickhouse, dataset, metrics=metrics),
max_batch_size=max_batch_size,
max_batch_time=max_batch_time_ms,
metrics=metrics,
recoverable_errors=[TransportError],
)
def handler(signum, frame) -> None:
replacer.signal_shutdown()
signal.signal(signal.SIGINT, handler)
signal.signal(signal.SIGTERM, handler)
replacer.run()
logging.basicConfig(
level=getattr(logging, level.upper()),
format=settings.LOG_FORMAT,
)
def traces_sampler(sampling_context: Mapping[str, Any]) -> Any:
return sampling_context["parent_sampled"] or False
def setup_sentry() -> None:
sentry_sdk.init(
dsn=settings.SENTRY_DSN,
integrations=[
FlaskIntegration(),
GnuBacktraceIntegration(),
LoggingIntegration(event_level=logging.WARNING),
RedisIntegration(),
],
release=os.getenv("SNUBA_RELEASE"),
traces_sampler=traces_sampler,
)
metrics = create_metrics(
"snuba",
tags=None,
sample_rates=settings.DOGSTATSD_SAMPLING_RATES,
)
extract_user,
flatten_nested_field,
)
from snuba.processor import (
_as_dict_safe,
MessageProcessor,
ProcessorAction,
ProcessedMessage,
_ensure_valid_date,
_ensure_valid_ip,
_unicodify,
)
from snuba.util import create_metrics
metrics = create_metrics("snuba.transactions.processor")
UNKNOWN_SPAN_STATUS = 2
class TransactionsMessageProcessor(MessageProcessor):
PROMOTED_TAGS = {
"environment",
"sentry:release",
"sentry:user",
"sentry:dist",
}
def __extract_timestamp(self, field):
timestamp = _ensure_valid_date(datetime.fromtimestamp(field))
if timestamp is None:
def setup_logging(level: Optional[str] = None) -> None:
if level is None:
level = settings.LOG_LEVEL
logging.basicConfig(
level=getattr(logging, level.upper()),
format=settings.LOG_FORMAT,
)
def setup_sentry() -> None:
sentry_sdk.init(
dsn=settings.SENTRY_DSN,
integrations=[FlaskIntegration(),
GnuBacktraceIntegration()],
release=os.getenv("SNUBA_RELEASE"),
)
clickhouse_rw = ClickhousePool(settings.CLICKHOUSE_HOST,
settings.CLICKHOUSE_PORT)
clickhouse_ro = ClickhousePool(
settings.CLICKHOUSE_HOST,
settings.CLICKHOUSE_PORT,
client_settings={"readonly": True},
)
metrics = create_metrics("snuba")
reader: Reader[ClickhouseQuery] = NativeDriverReader(clickhouse_ro)
from typing import Any, MutableMapping, NamedTuple
from snuba import settings, state
from snuba.clickhouse.native import ClickhousePool
from snuba.clickhouse.query import ClickhouseQuery
from snuba.query.columns import all_referenced_columns
from snuba.request import Request
from snuba.state.rate_limit import RateLimitAggregator, RateLimitExceeded, PROJECT_RATE_LIMIT_NAME
from snuba.util import (
create_metrics,
force_bytes,
Timer,
)
logger = logging.getLogger('snuba.query')
metrics = create_metrics(settings.DOGSTATSD_HOST, settings.DOGSTATSD_PORT,
'snuba.api')
class QueryResult(NamedTuple):
# TODO: Give a better abstraction to QueryResult
result: MutableMapping[str, MutableMapping[str, Any]]
status: int
def raw_query(
request: Request,
query: ClickhouseQuery,
client: ClickhousePool,
timer: Timer,
stats=None,
) -> QueryResult:
def __init__(
self,
dataset_name: str,
raw_topic: Optional[str],
replacements_topic: Optional[str],
max_batch_size: int,
max_batch_time_ms: int,
bootstrap_servers: Sequence[str],
group_id: str,
commit_log_topic: Optional[str],
auto_offset_reset: str,
queued_max_messages_kbytes: int,
queued_min_messages: int,
rapidjson_deserialize: bool,
rapidjson_serialize: bool,
commit_retry_policy: Optional[RetryPolicy] = None,
) -> None:
self.dataset = get_dataset(dataset_name)
self.dataset_name = dataset_name
if not bootstrap_servers:
self.bootstrap_servers = settings.DEFAULT_DATASET_BROKERS.get(
dataset_name, settings.DEFAULT_BROKERS,
)
else:
self.bootstrap_servers = bootstrap_servers
stream_loader = enforce_table_writer(self.dataset).get_stream_loader()
self.raw_topic: Topic
if raw_topic is not None:
self.raw_topic = Topic(raw_topic)
else:
self.raw_topic = Topic(stream_loader.get_default_topic_spec().topic_name)
self.replacements_topic: Optional[Topic]
if replacements_topic is not None:
self.replacements_topic = Topic(replacements_topic)
else:
replacement_topic_spec = stream_loader.get_replacement_topic_spec()
if replacement_topic_spec is not None:
self.replacements_topic = Topic(replacement_topic_spec.topic_name)
else:
self.replacements_topic = None
self.commit_log_topic: Optional[Topic]
if commit_log_topic is not None:
self.commit_log_topic = Topic(commit_log_topic)
else:
commit_log_topic_spec = stream_loader.get_commit_log_topic_spec()
if commit_log_topic_spec is not None:
self.commit_log_topic = Topic(commit_log_topic_spec.topic_name)
else:
self.commit_log_topic = None
# XXX: This can result in a producer being built in cases where it's
# not actually required.
self.producer = Producer(
{
"bootstrap.servers": ",".join(self.bootstrap_servers),
"partitioner": "consistent",
"message.max.bytes": 50000000, # 50MB, default is 1MB
}
)
self.metrics = util.create_metrics(
"snuba.consumer", tags={"group": group_id, "dataset": self.dataset_name},
)
self.max_batch_size = max_batch_size
self.max_batch_time_ms = max_batch_time_ms
self.group_id = group_id
self.auto_offset_reset = auto_offset_reset
self.queued_max_messages_kbytes = queued_max_messages_kbytes
self.queued_min_messages = queued_min_messages
if commit_retry_policy is None:
commit_retry_policy = BasicRetryPolicy(
3,
constant_delay(1),
lambda e: isinstance(e, KafkaException)
and e.args[0].code()
in (
KafkaError.REQUEST_TIMED_OUT,
KafkaError.NOT_COORDINATOR_FOR_GROUP,
KafkaError._WAIT_COORD,
),
)
self.__commit_retry_policy = commit_retry_policy
self.__rapidjson_deserialize = rapidjson_deserialize
self.__rapidjson_serialize = rapidjson_serialize
def replacer(*, replacements_topic, consumer_group, bootstrap_server,
clickhouse_host, clickhouse_port, dataset, max_batch_size,
max_batch_time_ms, auto_offset_reset, queued_max_messages_kbytes,
queued_min_messages, log_level, dogstatsd_host, dogstatsd_port):
import sentry_sdk
from snuba import util
from snuba.clickhouse.native import ClickhousePool
from snuba.replacer import ReplacerWorker
from snuba.utils.streams.batching import BatchingConsumer
from snuba.utils.streams.kafka import KafkaConsumer, TransportError, build_kafka_consumer_configuration
sentry_sdk.init(dsn=settings.SENTRY_DSN)
dataset = get_dataset(dataset)
logging.basicConfig(level=getattr(logging, log_level.upper()),
format='%(asctime)s %(message)s')
stream_loader = enforce_table_writer(dataset).get_stream_loader()
default_replacement_topic_spec = stream_loader.get_replacement_topic_spec()
assert default_replacement_topic_spec is not None, f"Dataset {dataset} does not have a replacement topic."
replacements_topic = replacements_topic or default_replacement_topic_spec.topic_name
metrics = util.create_metrics(dogstatsd_host,
dogstatsd_port,
'snuba.replacer',
tags={"group": consumer_group})
client_settings = {
# Replacing existing rows requires reconstructing the entire tuple for each
# event (via a SELECT), which is a Hard Thing (TM) for columnstores to do. With
# the default settings it's common for ClickHouse to go over the default max_memory_usage
# of 10GB per query. Lowering the max_block_size reduces memory usage, and increasing the
# max_memory_usage gives the query more breathing room.
'max_block_size': settings.REPLACER_MAX_BLOCK_SIZE,
'max_memory_usage': settings.REPLACER_MAX_MEMORY_USAGE,
# Don't use up production cache for the count() queries.
'use_uncompressed_cache': 0,
}
clickhouse = ClickhousePool(
host=clickhouse_host,
port=clickhouse_port,
client_settings=client_settings,
)
replacer = BatchingConsumer(
KafkaConsumer(
build_kafka_consumer_configuration(
bootstrap_servers=bootstrap_server,
group_id=consumer_group,
auto_offset_reset=auto_offset_reset,
queued_max_messages_kbytes=queued_max_messages_kbytes,
queued_min_messages=queued_min_messages,
), ),
replacements_topic,
worker=ReplacerWorker(clickhouse, dataset, metrics=metrics),
max_batch_size=max_batch_size,
max_batch_time=max_batch_time_ms,
metrics=metrics,
recoverable_errors=[TransportError],
)
def handler(signum, frame):
replacer.signal_shutdown()
signal.signal(signal.SIGINT, handler)
signal.signal(signal.SIGTERM, handler)
replacer.run()
import uuid
from snuba import settings
from snuba.processor import (_as_dict_safe, MessageProcessor, ProcessorAction,
ProcessedMessage, _ensure_valid_date,
_ensure_valid_ip, _unicodify)
from snuba.datasets.events_processor import (
enforce_retention,
extract_base,
extract_extra_contexts,
extract_extra_tags,
extract_user,
)
from snuba.util import create_metrics
metrics = create_metrics(settings.DOGSTATSD_HOST, settings.DOGSTATSD_PORT,
'snuba.transactions.processor')
class TransactionsMessageProcessor(MessageProcessor):
PROMOTED_TAGS = {
"environment",
"sentry:release",
"sentry:user",
"sentry:dist",
}
def __extract_timestamp(self, field):
timestamp = _ensure_valid_date(datetime.fromtimestamp(field))
if timestamp is None:
timestamp = datetime.utcnow()
milliseconds = int(timestamp.microsecond / 1000)
