def test_check_version(self):
client = AIOKafkaClient(loop=self.loop, bootstrap_servers=self.hosts)
yield from client.bootstrap()
ver = yield from client.check_version()
self.assertTrue('0.' in ver)
yield from self.wait_topic(client, 'some_test_topic')
ver2 = yield from client.check_version()
self.assertEqual(ver, ver2)
ver2 = yield from client.check_version(client.get_random_node())
self.assertEqual(ver, ver2)
with mock.patch.object(AIOKafkaConnection, 'send') as mocked:
mocked.side_effect = KafkaError('mocked exception')
with self.assertRaises(UnrecognizedBrokerVersion):
yield from client.check_version(client.get_random_node())
client._get_conn = asyncio.coroutine(lambda _: None)
with self.assertRaises(ConnectionError):
yield from client.check_version()
def test_check_version(self):
client = AIOKafkaClient(loop=self.loop, bootstrap_servers=self.hosts)
yield from client.bootstrap()
ver = yield from client.check_version()
self.assertTrue('0.' in ver)
yield from self.wait_topic(client, 'some_test_topic')
ver2 = yield from client.check_version()
self.assertEqual(ver, ver2)
ver2 = yield from client.check_version(client.get_random_node())
self.assertEqual(ver, ver2)
with mock.patch.object(
AIOKafkaConnection, 'send') as mocked:
mocked.side_effect = KafkaError('mocked exception')
with self.assertRaises(UnrecognizedBrokerVersion):
yield from client.check_version(client.get_random_node())
client._get_conn = asyncio.coroutine(lambda _: None)
with self.assertRaises(ConnectionError):
yield from client.check_version()
def test_check_version(self):
kafka_version = tuple(int(x) for x in self.kafka_version.split("."))
client = AIOKafkaClient(loop=self.loop, bootstrap_servers=self.hosts)
yield from client.bootstrap()
ver = yield from client.check_version()
self.assertEqual(kafka_version[:2], ver[:2])
yield from self.wait_topic(client, 'some_test_topic')
ver2 = yield from client.check_version()
self.assertEqual(ver, ver2)
ver2 = yield from client.check_version(client.get_random_node())
self.assertEqual(ver, ver2)
with mock.patch.object(AIOKafkaConnection, 'send') as mocked:
mocked.side_effect = KafkaError('mocked exception')
with self.assertRaises(UnrecognizedBrokerVersion):
yield from client.check_version(client.get_random_node())
client._get_conn = asyncio.coroutine(lambda _, **kw: None)
with self.assertRaises(ConnectionError):
yield from client.check_version()
yield from client.close()
def test_check_version(self):
kafka_version = tuple(int(x) for x in self.kafka_version.split("."))
client = AIOKafkaClient(loop=self.loop, bootstrap_servers=self.hosts)
yield from client.bootstrap()
ver = yield from client.check_version()
self.assertEqual(kafka_version[:2], ver[:2])
yield from self.wait_topic(client, 'some_test_topic')
ver2 = yield from client.check_version()
self.assertEqual(ver, ver2)
ver2 = yield from client.check_version(client.get_random_node())
self.assertEqual(ver, ver2)
with mock.patch.object(
AIOKafkaConnection, 'send') as mocked:
mocked.side_effect = KafkaError('mocked exception')
with self.assertRaises(UnrecognizedBrokerVersion):
yield from client.check_version(client.get_random_node())
client._get_conn = asyncio.coroutine(lambda _, **kw: None)
with self.assertRaises(ConnectionError):
yield from client.check_version()
yield from client.close()
class AIOKafkaProducer(object):
"""A Kafka client that publishes records to the Kafka cluster.
The producer consists of a pool of buffer space that holds records that
haven't yet been transmitted to the server as well as a background task
that is responsible for turning these records into requests and
transmitting them to the cluster.
The send() method is asynchronous. When called it adds the record to a
buffer of pending record sends and immediately returns. This allows the
producer to batch together individual records for efficiency.
The 'acks' config controls the criteria under which requests are considered
complete. The "all" setting will result in blocking on the full commit of
the record, the slowest but most durable setting.
The key_serializer and value_serializer instruct how to turn the key and
value objects the user provides into bytes.
Keyword Arguments:
bootstrap_servers: 'host[:port]' string (or list of 'host[:port]'
strings) that the producer should contact to bootstrap initial
cluster metadata. This does not have to be the full node list.
It just needs to have at least one broker that will respond to a
Metadata API Request. Default port is 9092. If no servers are
specified, will default to localhost:9092.
client_id (str): a name for this client. This string is passed in
each request to servers and can be used to identify specific
server-side log entries that correspond to this client.
Default: 'aiokafka-producer-#' (appended with a unique number
per instance)
key_serializer (callable): used to convert user-supplied keys to bytes
If not None, called as f(key), should return bytes. Default: None.
value_serializer (callable): used to convert user-supplied message
values to bytes. If not None, called as f(value), should return
bytes. Default: None.
acks (0, 1, 'all'): The number of acknowledgments the producer requires
the leader to have received before considering a request complete.
This controls the durability of records that are sent. The
following settings are common:
0: Producer will not wait for any acknowledgment from the server
at all. The message will immediately be added to the socket
buffer and considered sent. No guarantee can be made that the
server has received the record in this case, and the retries
configuration will not take effect (as the client won't
generally know of any failures). The offset given back for each
record will always be set to -1.
1: The broker leader will write the record to its local log but
will respond without awaiting full acknowledgement from all
followers. In this case should the leader fail immediately
after acknowledging the record but before the followers have
replicated it then the record will be lost.
all: The broker leader will wait for the full set of in-sync
replicas to acknowledge the record. This guarantees that the
record will not be lost as long as at least one in-sync replica
remains alive. This is the strongest available guarantee.
If unset, defaults to acks=1.
compression_type (str): The compression type for all data generated by
the producer. Valid values are 'gzip', 'snappy', 'lz4', or None.
Compression is of full batches of data, so the efficacy of batching
will also impact the compression ratio (more batching means better
compression). Default: None.
max_batch_size (int): Maximum size of buffered data per partition.
After this amount `send` coroutine will block until batch is
drained.
Default: 16384
linger_ms (int): The producer groups together any records that arrive
in between request transmissions into a single batched request.
Normally this occurs only under load when records arrive faster
than they can be sent out. However in some circumstances the client
may want to reduce the number of requests even under moderate load.
This setting accomplishes this by adding a small amount of
artificial delay; that is, rather than immediately sending out a
record the producer will wait for up to the given delay to allow
other records to be sent so that the sends can be batched together.
This setting defaults to 0 (i.e. no delay). Setting linger_ms=5
would have the effect of reducing the number of requests sent but
would add up to 5ms of latency to records sent in the absense of
load. Default: 0.
partitioner (callable): Callable used to determine which partition
each message is assigned to. Called (after key serialization):
partitioner(key_bytes, all_partitions, available_partitions).
The default partitioner implementation hashes each non-None key
using the same murmur2 algorithm as the java client so that
messages with the same key are assigned to the same partition.
When a key is None, the message is delivered to a random partition
(filtered to partitions with available leaders only, if possible).
max_request_size (int): The maximum size of a request. This is also
effectively a cap on the maximum record size. Note that the server
has its own cap on record size which may be different from this.
This setting will limit the number of record batches the producer
will send in a single request to avoid sending huge requests.
Default: 1048576.
metadata_max_age_ms (int): The period of time in milliseconds after
which we force a refresh of metadata even if we haven't seen any
partition leadership changes to proactively discover any new
brokers or partitions. Default: 300000
request_timeout_ms (int): Produce request timeout in milliseconds.
As it's sent as part of ProduceRequest, maximum waiting time can
be up to 2 * request_timeout_ms.
Default: 30000.
retry_backoff_ms (int): Milliseconds to backoff when retrying on
errors. Default: 100.
api_version (str): specify which kafka API version to use.
If set to 'auto', will attempt to infer the broker version by
probing various APIs. Default: auto
Note:
Many configuration parameters are taken from Java Client:
https://kafka.apache.org/documentation.html#producerconfigs
"""
_PRODUCER_CLIENT_ID_SEQUENCE = 0
def __init__(self,
*,
loop,
bootstrap_servers='localhost',
client_id=None,
metadata_max_age_ms=300000,
request_timeout_ms=40000,
api_version='auto',
acks=1,
key_serializer=None,
value_serializer=None,
compression_type=None,
max_batch_size=16384,
partitioner=DefaultPartitioner(),
max_request_size=1048576,
linger_ms=0,
send_backoff_ms=100,
retry_backoff_ms=100):
if acks not in (0, 1, -1, 'all'):
raise ValueError("Invalid ACKS parameter")
if compression_type not in ('gzip', 'snappy', 'lz4', None):
raise ValueError("Invalid compression type!")
if api_version not in ('auto', '0.9', '0.8.2', '0.8.1', '0.8.0'):
raise ValueError("Unsupported Kafka version")
self._PRODUCER_CLIENT_ID_SEQUENCE += 1
if client_id is None:
client_id = 'aiokafka-producer-%s' % \
self._PRODUCER_CLIENT_ID_SEQUENCE
if acks == 'all':
acks = -1
self._acks = acks
self._api_version = api_version
self._key_serializer = key_serializer
self._value_serializer = value_serializer
self._compression_type = compression_type
self._partitioner = partitioner
self._max_request_size = max_request_size
self._request_timeout_ms = request_timeout_ms
self.client = AIOKafkaClient(loop=loop,
bootstrap_servers=bootstrap_servers,
client_id=client_id,
metadata_max_age_ms=metadata_max_age_ms,
request_timeout_ms=request_timeout_ms)
self._metadata = self.client.cluster
self._message_accumulator = MessageAccumulator(
self._metadata, max_batch_size, self._compression_type,
self._request_timeout_ms / 1000, loop)
self._sender_task = None
self._in_flight = set()
self._closed = False
self._loop = loop
self._retry_backoff = retry_backoff_ms / 1000
self._linger_time = linger_ms / 1000
@asyncio.coroutine
def start(self):
"""Connect to Kafka cluster and check server version"""
log.debug("Starting the Kafka producer") # trace
yield from self.client.bootstrap()
# Check Broker Version if not set explicitly
if self._api_version == 'auto':
self._api_version = yield from self.client.check_version()
# Convert api_version config to tuple for easy comparisons
self._api_version = tuple(map(int, self._api_version.split('.')))
if self._compression_type == 'lz4':
assert self._api_version >= (0, 8, 2), \
'LZ4 Requires >= Kafka 0.8.2 Brokers'
self._sender_task = ensure_future(self._sender_routine(),
loop=self._loop)
log.debug("Kafka producer started")
@asyncio.coroutine
def stop(self):
"""Flush all pending data and close all connections to kafka cluser"""
if self._closed:
return
# Wait untill all batches are Delivered and futures resolved
yield from self._message_accumulator.close()
if self._sender_task:
self._sender_task.cancel()
yield from self._sender_task
yield from self.client.close()
self._closed = True
log.debug("The Kafka producer has closed.")
@asyncio.coroutine
def partitions_for(self, topic):
"""Returns set of all known partitions for the topic."""
return (yield from self._wait_on_metadata(topic))
@asyncio.coroutine
def _wait_on_metadata(self, topic):
"""
Wait for cluster metadata including partitions for the given topic to
be available.
Arguments:
topic (str): topic we want metadata for
Returns:
set: partition ids for the topic
Raises:
UnknownTopicOrPartitionError: if no topic or partitions found
in cluster metadata
"""
if topic in self.client.cluster.topics():
return self._metadata.partitions_for_topic(topic)
# add topic to metadata topic list if it is not there already.
self.client.add_topic(topic)
yield from self.client.force_metadata_update()
if topic not in self.client.cluster.topics():
raise UnknownTopicOrPartitionError()
return self._metadata.partitions_for_topic(topic)
@asyncio.coroutine
def send(self, topic, value=None, key=None, partition=None):
"""Publish a message to a topic.
Arguments:
topic (str): topic where the message will be published
value (optional): message value. Must be type bytes, or be
serializable to bytes via configured value_serializer. If value
is None, key is required and message acts as a 'delete'.
See kafka compaction documentation for more details:
http://kafka.apache.org/documentation.html#compaction
(compaction requires kafka >= 0.8.1)
partition (int, optional): optionally specify a partition. If not
set, the partition will be selected using the configured
'partitioner'.
key (optional): a key to associate with the message. Can be used to
determine which partition to send the message to. If partition
is None (and producer's partitioner config is left as default),
then messages with the same key will be delivered to the same
partition (but if key is None, partition is chosen randomly).
Must be type bytes, or be serializable to bytes via configured
key_serializer.
Returns:
asyncio.Future: future object that will be set when message is
processed
Note: The returned future will wait based on `request_timeout_ms`
setting. Cancelling this future will not stop event from being
sent.
"""
assert value is not None or self._api_version >= (0, 8, 1), (
'Null messages require kafka >= 0.8.1')
assert not (value is None and key is None), \
'Need at least one: key or value'
# first make sure the metadata for the topic is available
yield from self._wait_on_metadata(topic)
key_bytes, value_bytes = self._serialize(topic, key, value)
partition = self._partition(topic, partition, key, value, key_bytes,
value_bytes)
tp = TopicPartition(topic, partition)
log.debug("Sending (key=%s value=%s) to %s", key, value, tp)
fut = yield from self._message_accumulator.add_message(
tp, key_bytes, value_bytes, self._request_timeout_ms / 1000)
return fut
@asyncio.coroutine
def _sender_routine(self):
"""backgroud task that sends message batches to Kafka brokers"""
tasks = set()
try:
while True:
batches, unknown_leaders_exist = \
self._message_accumulator.drain_by_nodes(
ignore_nodes=self._in_flight)
# create produce task for every batch
for node_id, batches in batches.items():
task = ensure_future(self._send_produce_req(
node_id, batches),
loop=self._loop)
tasks.add(task)
if unknown_leaders_exist:
# we have at least one unknown partition's leader,
# try to update cluster metadata and wait backoff time
self.client.force_metadata_update()
# Just to have at least 1 future in wait() call
fut = asyncio.sleep(self._retry_backoff, loop=self._loop)
waiters = tasks.union([fut])
else:
fut = self._message_accumulator.data_waiter()
waiters = tasks.union([fut])
# wait when:
# * At least one of produce task is finished
# * Data for new partition arrived
done, _ = yield from asyncio.wait(
waiters,
return_when=asyncio.FIRST_COMPLETED,
loop=self._loop)
tasks -= done
except asyncio.CancelledError:
pass
except Exception: # noqa
log.error("Unexpected error in sender routine", exc_info=True)
@asyncio.coroutine
def _send_produce_req(self, node_id, batches):
"""Create produce request to node
If producer configured with `retries`>0 and produce response contain
"failed" partitions produce request for this partition will try
resend to broker `retries` times with `retry_timeout_ms` timeouts.
Arguments:
node_id (int): kafka broker identifier
batches (dict): dictionary of {TopicPartition: MessageBatch}
"""
self._in_flight.add(node_id)
t0 = self._loop.time()
while True:
topics = collections.defaultdict(list)
for tp, batch in batches.items():
topics[tp.topic].append((tp.partition, batch.data()))
request = ProduceRequest(required_acks=self._acks,
timeout=self._request_timeout_ms,
topics=list(topics.items()))
try:
response = yield from self.client.send(node_id, request)
except KafkaError as err:
for batch in batches.values():
if not err.retriable or batch.expired():
batch.done(exception=err)
log.warning("Got error produce response: %s", err)
if not err.retriable:
break
else:
if response is None:
# noacks, just "done" batches
for batch in batches.values():
batch.done()
break
for topic, partitions in response.topics:
for partition, error_code, offset in partitions:
tp = TopicPartition(topic, partition)
error = Errors.for_code(error_code)
batch = batches.pop(tp, None)
if batch is None:
continue
if error is Errors.NoError:
batch.done(offset)
elif not getattr(error, 'retriable', False) or \
batch.expired():
batch.done(exception=error())
else:
# Ok, we can retry this batch
batches[tp] = batch
log.warning(
"Got error produce response on topic-partition"
" %s, retrying. Error: %s", tp, error)
if batches:
yield from asyncio.sleep(self._retry_backoff, loop=self._loop)
else:
break
# if batches for node is processed in less than a linger seconds
# then waiting for the remaining time
sleep_time = self._linger_time - (self._loop.time() - t0)
if sleep_time > 0:
yield from asyncio.sleep(sleep_time, loop=self._loop)
self._in_flight.remove(node_id)
def _serialize(self, topic, key, value):
if self._key_serializer:
serialized_key = self._key_serializer(key)
else:
serialized_key = key
if self._value_serializer:
serialized_value = self._value_serializer(value)
else:
serialized_value = value
message_size = MessageSet.HEADER_SIZE + Message.HEADER_SIZE
if serialized_key is not None:
message_size += len(serialized_key)
if serialized_value is not None:
message_size += len(serialized_value)
if message_size > self._max_request_size:
raise MessageSizeTooLargeError(
"The message is %d bytes when serialized which is larger than"
" the maximum request size you have configured with the"
" max_request_size configuration" % message_size)
return serialized_key, serialized_value
def _partition(self, topic, partition, key, value, serialized_key,
serialized_value):
if partition is not None:
assert partition >= 0
assert partition in self._metadata.partitions_for_topic(topic), \
'Unrecognized partition'
return partition
all_partitions = list(self._metadata.partitions_for_topic(topic))
available = list(self._metadata.available_partitions_for_topic(topic))
return self._partitioner(serialized_key, all_partitions, available)
class AIOKafkaConsumer(object):
"""Consume records from a Kafka cluster.
The consumer will transparently handle the failure of servers in the Kafka
cluster, and adapt as topic-partitions are created or migrate between
brokers. It also interacts with the assigned kafka Group Coordinator node
to allow multiple consumers to load balance consumption of topics (requires
kafka >= 0.9.0.0).
Arguments:
*topics (str): optional list of topics to subscribe to. If not set,
call subscribe() or assign() before consuming records.
bootstrap_servers: 'host[:port]' string (or list of 'host[:port]'
strings) that the consumer should contact to bootstrap initial
cluster metadata. This does not have to be the full node list.
It just needs to have at least one broker that will respond to a
Metadata API Request. Default port is 9092. If no servers are
specified, will default to localhost:9092.
client_id (str): a name for this client. This string is passed in
each request to servers and can be used to identify specific
server-side log entries that correspond to this client. Also
submitted to GroupCoordinator for logging with respect to
consumer group administration. Default: 'aiokafka-{version}'
group_id (str or None): name of the consumer group to join for dynamic
partition assignment (if enabled), and to use for fetching and
committing offsets. If None, auto-partition assignment (via
group coordinator) and offset commits are disabled.
Default: None
key_deserializer (callable): Any callable that takes a
raw message key and returns a deserialized key.
value_deserializer (callable, optional): Any callable that takes a
raw message value and returns a deserialized value.
fetch_min_bytes (int): Minimum amount of data the server should
return for a fetch request, otherwise wait up to
fetch_max_wait_ms for more data to accumulate. Default: 1.
fetch_max_wait_ms (int): The maximum amount of time in milliseconds
the server will block before answering the fetch request if
there isn't sufficient data to immediately satisfy the
requirement given by fetch_min_bytes. Default: 500.
max_partition_fetch_bytes (int): The maximum amount of data
per-partition the server will return. The maximum total memory
used for a request = #partitions * max_partition_fetch_bytes.
This size must be at least as large as the maximum message size
the server allows or else it is possible for the producer to
send messages larger than the consumer can fetch. If that
happens, the consumer can get stuck trying to fetch a large
message on a certain partition. Default: 1048576.
request_timeout_ms (int): Client request timeout in milliseconds.
Default: 40000.
retry_backoff_ms (int): Milliseconds to backoff when retrying on
errors. Default: 100.
reconnect_backoff_ms (int): The amount of time in milliseconds to
wait before attempting to reconnect to a given host.
Default: 50.
auto_offset_reset (str): A policy for resetting offsets on
OffsetOutOfRange errors: 'earliest' will move to the oldest
available message, 'latest' will move to the most recent. Any
ofther value will raise the exception. Default: 'latest'.
enable_auto_commit (bool): If true the consumer's offset will be
periodically committed in the background. Default: True.
auto_commit_interval_ms (int): milliseconds between automatic
offset commits, if enable_auto_commit is True. Default: 5000.
check_crcs (bool): Automatically check the CRC32 of the records
consumed. This ensures no on-the-wire or on-disk corruption to
the messages occurred. This check adds some overhead, so it may
be disabled in cases seeking extreme performance. Default: True
metadata_max_age_ms (int): The period of time in milliseconds after
which we force a refresh of metadata even if we haven't seen any
partition leadership changes to proactively discover any new
brokers or partitions. Default: 300000
partition_assignment_strategy (list): List of objects to use to
distribute partition ownership amongst consumer instances when
group management is used. This preference is implicit in the order
of the strategies in the list. When assignment strategy changes:
to support a change to the assignment strategy, new versions must
enable support both for the old assignment strategy and the new
one. The coordinator will choose the old assignment strategy until
all members have been updated. Then it will choose the new
strategy. Default: [RoundRobinPartitionAssignor]
heartbeat_interval_ms (int): The expected time in milliseconds
between heartbeats to the consumer coordinator when using
Kafka's group management feature. Heartbeats are used to ensure
that the consumer's session stays active and to facilitate
rebalancing when new consumers join or leave the group. The
value must be set lower than session_timeout_ms, but typically
should be set no higher than 1/3 of that value. It can be
adjusted even lower to control the expected time for normal
rebalances. Default: 3000
session_timeout_ms (int): The timeout used to detect failures when
using Kafka's group managementment facilities. Default: 30000
consumer_timeout_ms (int): number of millisecond to poll available
fetched messages. Default: 100
api_version (str): specify which kafka API version to use.
AIOKafkaConsumer supports Kafka API versions >=0.9 only.
If set to 'auto', will attempt to infer the broker version by
probing various APIs. Default: auto
Note:
Many configuration parameters are taken from Java Client:
https://kafka.apache.org/documentation.html#newconsumerconfigs
"""
def __init__(self, *topics, loop,
bootstrap_servers='localhost',
client_id='aiokafka-'+__version__,
group_id=None,
key_deserializer=None, value_deserializer=None,
fetch_max_wait_ms=500,
fetch_min_bytes=1,
max_partition_fetch_bytes=1 * 1024 * 1024,
request_timeout_ms=40 * 1000,
retry_backoff_ms=100,
reconnect_backoff_ms=50,
auto_offset_reset='latest',
enable_auto_commit=True,
auto_commit_interval_ms=5000,
check_crcs=True,
metadata_max_age_ms=5 * 60 * 1000,
partition_assignment_strategy=(RoundRobinPartitionAssignor,),
heartbeat_interval_ms=3000,
session_timeout_ms=30000,
consumer_timeout_ms=100,
api_version='auto'):
if api_version not in ('auto', '0.9'):
raise ValueError("Unsupported Kafka API version")
self._client = AIOKafkaClient(
loop=loop, bootstrap_servers=bootstrap_servers,
client_id=client_id, metadata_max_age_ms=metadata_max_age_ms,
request_timeout_ms=request_timeout_ms)
self._api_version = api_version
self._group_id = group_id
self._heartbeat_interval_ms = heartbeat_interval_ms
self._retry_backoff_ms = retry_backoff_ms
self._enable_auto_commit = enable_auto_commit
self._auto_commit_interval_ms = auto_commit_interval_ms
self._partition_assignment_strategy = partition_assignment_strategy
self._key_deserializer = key_deserializer
self._value_deserializer = value_deserializer
self._fetch_min_bytes = fetch_min_bytes
self._fetch_max_wait_ms = fetch_max_wait_ms
self._max_partition_fetch_bytes = max_partition_fetch_bytes
self._consumer_timeout = consumer_timeout_ms / 1000
self._check_crcs = check_crcs
self._subscription = SubscriptionState(auto_offset_reset)
self._fetcher = None
self._coordinator = None
self._closed = False
self._loop = loop
self._topics = topics
if topics:
self._client.set_topics(topics)
self._subscription.subscribe(topics=topics)
@asyncio.coroutine
def start(self):
yield from self._client.bootstrap()
# Check Broker Version if not set explicitly
if self._api_version == 'auto':
self._api_version = yield from self._client.check_version()
# Convert api_version config to tuple for easy comparisons
self._api_version = tuple(
map(int, self._api_version.split('.')))
if self._api_version < (0, 9):
raise ValueError(
"Unsupported Kafka version: {}".format(self._api_version))
self._fetcher = Fetcher(
self._client, self._subscription, loop=self._loop,
key_deserializer=self._key_deserializer,
value_deserializer=self._value_deserializer,
fetch_min_bytes=self._fetch_min_bytes,
fetch_max_wait_ms=self._fetch_max_wait_ms,
max_partition_fetch_bytes=self._max_partition_fetch_bytes,
check_crcs=self._check_crcs,
fetcher_timeout=self._consumer_timeout)
if self._group_id is not None:
# using group coordinator for automatic partitions assignment
self._coordinator = GroupCoordinator(
self._client, self._subscription, loop=self._loop,
group_id=self._group_id,
heartbeat_interval_ms=self._heartbeat_interval_ms,
retry_backoff_ms=self._retry_backoff_ms,
enable_auto_commit=self._enable_auto_commit,
auto_commit_interval_ms=self._auto_commit_interval_ms,
assignors=self._partition_assignment_strategy)
self._coordinator.on_group_rebalanced(
self._on_change_subscription)
yield from self._coordinator.ensure_active_group()
elif self._subscription.needs_partition_assignment:
# using manual partitions assignment by topic(s)
yield from self._client.force_metadata_update()
partitions = []
for topic in self._topics:
p_ids = self.partitions_for_topic(topic)
for p_id in p_ids:
partitions.append(TopicPartition(topic, p_id))
self._subscription.unsubscribe()
self._subscription.assign_from_user(partitions)
yield from self._update_fetch_positions(
self._subscription.missing_fetch_positions())
def assign(self, partitions):
"""Manually assign a list of TopicPartitions to this consumer.
Arguments:
partitions (list of TopicPartition): assignment for this instance.
Raises:
IllegalStateError: if consumer has already called subscribe()
Warning:
It is not possible to use both manual partition assignment with
assign() and group assignment with subscribe().
Note:
This interface does not support incremental assignment and will
replace the previous assignment (if there was one).
Note:
Manual topic assignment through this method does not use the
consumer's group management functionality. As such, there will be
no rebalance operation triggered when group membership or cluster
and topic metadata change.
"""
self._subscription.assign_from_user(partitions)
self._on_change_subscription()
self._client.set_topics([tp.topic for tp in partitions])
def assignment(self):
"""Get the TopicPartitions currently assigned to this consumer.
If partitions were directly assigned using assign(), then this will
simply return the same partitions that were previously assigned.
If topics were subscribed using subscribe(), then this will give the
set of topic partitions currently assigned to the consumer (which may
be none if the assignment hasn't happened yet or if the partitions are
in the process of being reassigned).
Returns:
set: {TopicPartition, ...}
"""
return self._subscription.assigned_partitions()
@asyncio.coroutine
def stop(self):
"""Close the consumer, waiting indefinitely for any needed cleanup."""
if self._closed:
return
log.debug("Closing the KafkaConsumer.")
self._closed = True
if self._coordinator:
yield from self._coordinator.close()
if self._fetcher:
yield from self._fetcher.close()
yield from self._client.close()
log.debug("The KafkaConsumer has closed.")
@asyncio.coroutine
def commit(self, offsets=None):
"""Commit offsets to kafka, blocking until success or error
This commits offsets only to Kafka.
The offsets committed using this API will be used on the first fetch
after every rebalance and also on startup. As such, if you needto store
offsets in anything other than Kafka, this API should not be used.
Blocks until either the commit succeeds or an unrecoverable error is
encountered (in which case it is thrown to the caller).
Currently only supports kafka-topic offset storage (not zookeeper)
Arguments:
offsets (dict, optional): {TopicPartition: OffsetAndMetadata} dict
to commit with the configured group_id. Defaults to current
consumed offsets for all subscribed partitions.
"""
assert self._group_id is not None, 'Requires group_id'
if offsets is None:
offsets = self._subscription.all_consumed_offsets()
else:
# validate `offsets` structure
assert all(map(lambda k: isinstance(k, TopicPartition), offsets))
assert all(map(lambda v: isinstance(v, OffsetAndMetadata),
offsets.values()))
yield from self._coordinator.commit_offsets(offsets)
@asyncio.coroutine
def committed(self, partition):
"""Get the last committed offset for the given partition
This offset will be used as the position for the consumer
in the event of a failure.
This call may block to do a remote call if the partition in question
isn't assigned to this consumer or if the consumer hasn't yet
initialized its cache of committed offsets.
Arguments:
partition (TopicPartition): the partition to check
Returns:
The last committed offset, or None if there was no prior commit.
"""
assert self._group_id is not None, 'Requires group_id'
if self._subscription.is_assigned(partition):
committed = self._subscription.assignment[partition].committed
if committed is None:
yield from self._coordinator.refresh_committed_offsets()
committed = self._subscription.assignment[partition].committed
else:
commit_map = yield from self._coordinator.fetch_committed_offsets(
[partition])
if partition in commit_map:
committed = commit_map[partition].offset
else:
committed = None
return committed
@asyncio.coroutine
def topics(self):
"""Get all topics the user is authorized to view.
Returns:
set: topics
"""
cluster = yield from self._client.fetch_all_metadata()
return cluster.topics()
def partitions_for_topic(self, topic):
"""Get metadata about the partitions for a given topic.
Arguments:
topic (str): topic to check
Returns:
set: partition ids
"""
return self._client.cluster.partitions_for_topic(topic)
@asyncio.coroutine
def position(self, partition):
"""Get the offset of the next record that will be fetched
Arguments:
partition (TopicPartition): partition to check
Returns:
int: offset
"""
assert self._subscription.is_assigned(partition), \
'Partition is not assigned'
offset = self._subscription.assignment[partition].position
if offset is None:
yield from self._update_fetch_positions(partition)
offset = self._subscription.assignment[partition].position
return offset
def highwater(self, partition):
"""Last known highwater offset for a partition
A highwater offset is the offset that will be assigned to the next
message that is produced. It may be useful for calculating lag, by
comparing with the reported position. Note that both position and
highwater refer to the *next* offset -- i.e., highwater offset is
one greater than the newest availabel message.
Highwater offsets are returned in FetchResponse messages, so will
not be available if not FetchRequests have been sent for this partition
yet.
Arguments:
partition (TopicPartition): partition to check
Returns:
int or None: offset if available
"""
assert self._subscription.is_assigned(partition), \
'Partition is not assigned'
return self._subscription.assignment[partition].highwater
def seek(self, partition, offset):
"""Manually specify the fetch offset for a TopicPartition.
Overrides the fetch offsets that the consumer will use on the next
poll(). If this API is invoked for the same partition more than once,
the latest offset will be used on the next poll(). Note that you may
lose data if this API is arbitrarily used in the middle of consumption,
to reset the fetch offsets.
Arguments:
partition (TopicPartition): partition for seek operation
offset (int): message offset in partition
Raises:
AssertionError: if offset is not an int >= 0;
or if partition is not currently assigned.
"""
assert isinstance(offset, int) and offset >= 0, 'Offset must be >= 0'
assert partition in self._subscription.assigned_partitions(), \
'Unassigned partition'
log.debug("Seeking to offset %s for partition %s", offset, partition)
self._subscription.assignment[partition].seek(offset)
@asyncio.coroutine
def seek_to_committed(self, *partitions):
"""Seek to the committed offset for partitions
Arguments:
partitions: optionally provide specific TopicPartitions,
otherwise default to all assigned partitions
Raises:
AssertionError: if any partition is not currently assigned, or if
no partitions are assigned
"""
if not partitions:
partitions = self._subscription.assigned_partitions()
assert partitions, 'No partitions are currently assigned'
else:
for p in partitions:
assert p in self._subscription.assigned_partitions(), \
'Unassigned partition'
for tp in partitions:
log.debug("Seeking to committed of partition %s", tp)
offset = yield from self.committed(tp)
if offset and offset > 0:
self.seek(tp, offset)
def subscribe(self, topics=(), pattern=None, listener=None):
"""Subscribe to a list of topics, or a topic regex pattern
Partitions will be dynamically assigned via a group coordinator.
Topic subscriptions are not incremental: this list will replace the
current assignment (if there is one).
This method is incompatible with assign()
Arguments:
topics (list): List of topics for subscription.
pattern (str): Pattern to match available topics. You must provide
either topics or pattern, but not both.
listener (ConsumerRebalanceListener): Optionally include listener
callback, which will be called before and after each rebalance
operation.
As part of group management, the consumer will keep track of
the list of consumers that belong to a particular group and
will trigger a rebalance operation if one of the following
events trigger:
* Number of partitions change for any of the subscribed topics
* Topic is created or deleted
* An existing member of the consumer group dies
* A new member is added to the consumer group
When any of these events are triggered, the provided listener
will be invoked first to indicate that the consumer's
assignment has been revoked, and then again when the new
assignment has been received. Note that this listener will
immediately override any listener set in a previous call
to subscribe. It is guaranteed, however, that the partitions
revoked/assigned
through this interface are from topics subscribed in this call.
Raises:
IllegalStateError: if called after previously calling assign()
AssertionError: if neither topics or pattern is provided
TypeError: if listener is not a ConsumerRebalanceListener
"""
# SubscriptionState handles error checking
self._subscription.subscribe(topics=topics,
pattern=pattern,
listener=listener)
# regex will need all topic metadata
if pattern is not None:
self._client.set_topics([])
log.debug("Subscribed to topic pattern: %s", pattern)
else:
self._client.set_topics(self._subscription.group_subscription())
log.debug("Subscribed to topic(s): %s", topics)
def subscription(self):
"""Get the current topic subscription.
Returns:
set: {topic, ...}
"""
return self._subscription.subscription
def unsubscribe(self):
"""Unsubscribe from all topics and clear all assigned partitions."""
self._subscription.unsubscribe()
self._client.set_topics([])
log.debug(
"Unsubscribed all topics or patterns and assigned partitions")
@asyncio.coroutine
def _update_fetch_positions(self, partitions):
"""
Set the fetch position to the committed position (if there is one)
or reset it using the offset reset policy the user has configured.
Arguments:
partitions (List[TopicPartition]): The partitions that need
updating fetch positions
Raises:
NoOffsetForPartitionError: If no offset is stored for a given
partition and no offset reset policy is defined
"""
if self._group_id is not None:
# refresh commits for all assigned partitions
yield from self._coordinator.refresh_committed_offsets()
# then do any offset lookups in case some positions are not known
yield from self._fetcher.update_fetch_positions(partitions)
def _on_change_subscription(self):
"""This is `group rebalanced` signal handler for update fetch positions
of assigned partitions"""
# fetch positions if we have partitions we're subscribed
# to that we don't know the offset for
if not self._subscription.has_all_fetch_positions():
ensure_future(self._update_fetch_positions(
self._subscription.missing_fetch_positions()),
loop=self._loop)
@asyncio.coroutine
def getone(self, *partitions):
"""
Get one message from Kafka
If no new messages prefetched, this method will wait for it
Arguments:
partitions (List[TopicPartition]): Optional list of partitions to
return from. If no partitions specified then returned message
will be from any partition, which consumer is subscribed to.
Returns:
ConsumerRecord
Will return instance of
.. code:: python
collections.namedtuple(
"ConsumerRecord",
["topic", "partition", "offset", "key", "value"])
Example usage:
.. code:: python
while True:
message = yield from consumer.getone()
topic = message.topic
partition = message.partition
# Process message
print(message.offset, message.key, message.value)
"""
assert all(map(lambda k: isinstance(k, TopicPartition), partitions))
msg = yield from self._fetcher.next_record(partitions)
return msg
@asyncio.coroutine
def getmany(self, *partitions, timeout_ms=0):
"""Get messages from assigned topics / partitions.
Prefetched messages are returned in batches by topic-partition.
If messages is not available in the prefetched buffer this method waits
`timeout_ms` milliseconds.
Arguments:
partitions (List[TopicPartition]): The partitions that need
fetching message. If no one partition specified then all
subscribed partitions will be used
timeout_ms (int, optional): milliseconds spent waiting if
data is not available in the buffer. If 0, returns immediately
with any records that are available currently in the buffer,
else returns empty. Must not be negative. Default: 0
Returns:
dict: topic to list of records since the last fetch for the
subscribed list of topics and partitions
Example usage:
.. code:: python
data = yield from consumer.getmany()
for tp, messages in data.items():
topic = tp.topic
partition = tp.partition
for message in messages:
# Process message
print(message.offset, message.key, message.value)
"""
assert all(map(lambda k: isinstance(k, TopicPartition), partitions))
timeout = timeout_ms / 1000
records = yield from self._fetcher.fetched_records(partitions, timeout)
return records
if PY_35:
@asyncio.coroutine
def __aiter__(self):
return self
@asyncio.coroutine
def __anext__(self):
return (yield from self.getone())
class AIOKafkaProducer(object):
"""A Kafka client that publishes records to the Kafka cluster.
The producer consists of a pool of buffer space that holds records that
haven't yet been transmitted to the server as well as a background task
that is responsible for turning these records into requests and
transmitting them to the cluster.
The send() method is asynchronous. When called it adds the record to a
buffer of pending record sends and immediately returns. This allows the
producer to batch together individual records for efficiency.
The 'acks' config controls the criteria under which requests are considered
complete. The "all" setting will result in blocking on the full commit of
the record, the slowest but most durable setting.
The key_serializer and value_serializer instruct how to turn the key and
value objects the user provides into bytes.
Keyword Arguments:
bootstrap_servers: 'host[:port]' string (or list of 'host[:port]'
strings) that the producer should contact to bootstrap initial
cluster metadata. This does not have to be the full node list.
It just needs to have at least one broker that will respond to a
Metadata API Request. Default port is 9092. If no servers are
specified, will default to localhost:9092.
client_id (str): a name for this client. This string is passed in
each request to servers and can be used to identify specific
server-side log entries that correspond to this client.
Default: 'aiokafka-producer-#' (appended with a unique number
per instance)
key_serializer (callable): used to convert user-supplied keys to bytes
If not None, called as f(key), should return bytes. Default: None.
value_serializer (callable): used to convert user-supplied message
values to bytes. If not None, called as f(value), should return
bytes. Default: None.
acks (0, 1, 'all'): The number of acknowledgments the producer requires
the leader to have received before considering a request complete.
This controls the durability of records that are sent. The
following settings are common:
0: Producer will not wait for any acknowledgment from the server
at all. The message will immediately be added to the socket
buffer and considered sent. No guarantee can be made that the
server has received the record in this case, and the retries
configuration will not take effect (as the client won't
generally know of any failures). The offset given back for each
record will always be set to -1.
1: The broker leader will write the record to its local log but
will respond without awaiting full acknowledgement from all
followers. In this case should the leader fail immediately
after acknowledging the record but before the followers have
replicated it then the record will be lost.
all: The broker leader will wait for the full set of in-sync
replicas to acknowledge the record. This guarantees that the
record will not be lost as long as at least one in-sync replica
remains alive. This is the strongest available guarantee.
If unset, defaults to acks=1.
compression_type (str): The compression type for all data generated by
the producer. Valid values are 'gzip', 'snappy', 'lz4', or None.
Compression is of full batches of data, so the efficacy of batching
will also impact the compression ratio (more batching means better
compression). Default: None.
max_batch_size (int): Maximum size of buffered data per partition.
After this amount `send` coroutine will block until batch is
drained.
Default: 16384
linger_ms (int): The producer groups together any records that arrive
in between request transmissions into a single batched request.
Normally this occurs only under load when records arrive faster
than they can be sent out. However in some circumstances the client
may want to reduce the number of requests even under moderate load.
This setting accomplishes this by adding a small amount of
artificial delay; that is, rather than immediately sending out a
record the producer will wait for up to the given delay to allow
other records to be sent so that the sends can be batched together.
This setting defaults to 0 (i.e. no delay). Setting linger_ms=5
would have the effect of reducing the number of requests sent but
would add up to 5ms of latency to records sent in the absense of
load. Default: 0.
partitioner (callable): Callable used to determine which partition
each message is assigned to. Called (after key serialization):
partitioner(key_bytes, all_partitions, available_partitions).
The default partitioner implementation hashes each non-None key
using the same murmur2 algorithm as the java client so that
messages with the same key are assigned to the same partition.
When a key is None, the message is delivered to a random partition
(filtered to partitions with available leaders only, if possible).
max_request_size (int): The maximum size of a request. This is also
effectively a cap on the maximum record size. Note that the server
has its own cap on record size which may be different from this.
This setting will limit the number of record batches the producer
will send in a single request to avoid sending huge requests.
Default: 1048576.
metadata_max_age_ms (int): The period of time in milliseconds after
which we force a refresh of metadata even if we haven't seen any
partition leadership changes to proactively discover any new
brokers or partitions. Default: 300000
request_timeout_ms (int): Produce request timeout in milliseconds.
As it's sent as part of ProduceRequest, maximum waiting time can
be up to 2 * request_timeout_ms.
Default: 30000.
retry_backoff_ms (int): Milliseconds to backoff when retrying on
errors. Default: 100.
api_version (str): specify which kafka API version to use.
If set to 'auto', will attempt to infer the broker version by
probing various APIs. Default: auto
Note:
Many configuration parameters are taken from Java Client:
https://kafka.apache.org/documentation.html#producerconfigs
"""
_PRODUCER_CLIENT_ID_SEQUENCE = 0
def __init__(self, *, loop, bootstrap_servers='localhost',
client_id=None,
metadata_max_age_ms=300000, request_timeout_ms=40000,
api_version='auto', acks=1,
key_serializer=None, value_serializer=None,
compression_type=None, max_batch_size=16384,
partitioner=DefaultPartitioner(), max_request_size=1048576,
linger_ms=0, send_backoff_ms=100,
retry_backoff_ms=100):
if acks not in (0, 1, -1, 'all'):
raise ValueError("Invalid ACKS parameter")
if compression_type not in ('gzip', 'snappy', 'lz4', None):
raise ValueError("Invalid compression type!")
if api_version not in ('auto', '0.9', '0.8.2', '0.8.1', '0.8.0'):
raise ValueError("Unsupported Kafka version")
self._PRODUCER_CLIENT_ID_SEQUENCE += 1
if client_id is None:
client_id = 'aiokafka-producer-%s' % \
self._PRODUCER_CLIENT_ID_SEQUENCE
if acks == 'all':
acks = -1
self._acks = acks
self._api_version = api_version
self._key_serializer = key_serializer
self._value_serializer = value_serializer
self._compression_type = compression_type
self._partitioner = partitioner
self._max_request_size = max_request_size
self._request_timeout_ms = request_timeout_ms
self.client = AIOKafkaClient(
loop=loop, bootstrap_servers=bootstrap_servers,
client_id=client_id, metadata_max_age_ms=metadata_max_age_ms,
request_timeout_ms=request_timeout_ms)
self._metadata = self.client.cluster
self._message_accumulator = MessageAccumulator(
self._metadata, max_batch_size, self._compression_type,
self._request_timeout_ms/1000, loop)
self._sender_task = None
self._in_flight = set()
self._closed = False
self._loop = loop
self._retry_backoff = retry_backoff_ms / 1000
self._linger_time = linger_ms / 1000
@asyncio.coroutine
def start(self):
"""Connect to Kafka cluster and check server version"""
log.debug("Starting the Kafka producer") # trace
yield from self.client.bootstrap()
# Check Broker Version if not set explicitly
if self._api_version == 'auto':
self._api_version = yield from self.client.check_version()
# Convert api_version config to tuple for easy comparisons
self._api_version = tuple(
map(int, self._api_version.split('.')))
if self._compression_type == 'lz4':
assert self._api_version >= (0, 8, 2), \
'LZ4 Requires >= Kafka 0.8.2 Brokers'
self._sender_task = ensure_future(
self._sender_routine(), loop=self._loop)
log.debug("Kafka producer started")
@asyncio.coroutine
def stop(self):
"""Flush all pending data and close all connections to kafka cluser"""
if self._closed:
return
# Wait untill all batches are Delivered and futures resolved
yield from self._message_accumulator.close()
if self._sender_task:
self._sender_task.cancel()
yield from self._sender_task
yield from self.client.close()
self._closed = True
log.debug("The Kafka producer has closed.")
@asyncio.coroutine
def partitions_for(self, topic):
"""Returns set of all known partitions for the topic."""
return (yield from self._wait_on_metadata(topic))
@asyncio.coroutine
def _wait_on_metadata(self, topic):
"""
Wait for cluster metadata including partitions for the given topic to
be available.
Arguments:
topic (str): topic we want metadata for
Returns:
set: partition ids for the topic
Raises:
UnknownTopicOrPartitionError: if no topic or partitions found
in cluster metadata
"""
if topic in self.client.cluster.topics():
return self._metadata.partitions_for_topic(topic)
# add topic to metadata topic list if it is not there already.
self.client.add_topic(topic)
yield from self.client.force_metadata_update()
if topic not in self.client.cluster.topics():
raise UnknownTopicOrPartitionError()
return self._metadata.partitions_for_topic(topic)
@asyncio.coroutine
def send(self, topic, value=None, key=None, partition=None):
"""Publish a message to a topic.
Arguments:
topic (str): topic where the message will be published
value (optional): message value. Must be type bytes, or be
serializable to bytes via configured value_serializer. If value
is None, key is required and message acts as a 'delete'.
See kafka compaction documentation for more details:
http://kafka.apache.org/documentation.html#compaction
(compaction requires kafka >= 0.8.1)
partition (int, optional): optionally specify a partition. If not
set, the partition will be selected using the configured
'partitioner'.
key (optional): a key to associate with the message. Can be used to
determine which partition to send the message to. If partition
is None (and producer's partitioner config is left as default),
then messages with the same key will be delivered to the same
partition (but if key is None, partition is chosen randomly).
Must be type bytes, or be serializable to bytes via configured
key_serializer.
Returns:
asyncio.Future: future object that will be set when message is
processed
Note: The returned future will wait based on `request_timeout_ms`
setting. Cancelling this future will not stop event from being
sent.
"""
assert value is not None or self._api_version >= (0, 8, 1), (
'Null messages require kafka >= 0.8.1')
assert not (value is None and key is None), \
'Need at least one: key or value'
# first make sure the metadata for the topic is available
yield from self._wait_on_metadata(topic)
key_bytes, value_bytes = self._serialize(topic, key, value)
partition = self._partition(topic, partition, key, value,
key_bytes, value_bytes)
tp = TopicPartition(topic, partition)
log.debug("Sending (key=%s value=%s) to %s", key, value, tp)
fut = yield from self._message_accumulator.add_message(
tp, key_bytes, value_bytes, self._request_timeout_ms / 1000)
return fut
@asyncio.coroutine
def _sender_routine(self):
"""backgroud task that sends message batches to Kafka brokers"""
tasks = set()
try:
while True:
batches, unknown_leaders_exist = \
self._message_accumulator.drain_by_nodes(
ignore_nodes=self._in_flight)
# create produce task for every batch
for node_id, batches in batches.items():
task = ensure_future(
self._send_produce_req(node_id, batches),
loop=self._loop)
tasks.add(task)
if unknown_leaders_exist:
# we have at least one unknown partition's leader,
# try to update cluster metadata and wait backoff time
self.client.force_metadata_update()
# Just to have at least 1 future in wait() call
fut = asyncio.sleep(self._retry_backoff, loop=self._loop)
waiters = tasks.union([fut])
else:
fut = self._message_accumulator.data_waiter()
waiters = tasks.union([fut])
# wait when:
# * At least one of produce task is finished
# * Data for new partition arrived
done, _ = yield from asyncio.wait(
waiters,
return_when=asyncio.FIRST_COMPLETED,
loop=self._loop)
tasks -= done
except asyncio.CancelledError:
pass
except Exception: # noqa
log.error("Unexpected error in sender routine", exc_info=True)
@asyncio.coroutine
def _send_produce_req(self, node_id, batches):
"""Create produce request to node
If producer configured with `retries`>0 and produce response contain
"failed" partitions produce request for this partition will try
resend to broker `retries` times with `retry_timeout_ms` timeouts.
Arguments:
node_id (int): kafka broker identifier
batches (dict): dictionary of {TopicPartition: MessageBatch}
"""
self._in_flight.add(node_id)
t0 = self._loop.time()
while True:
topics = collections.defaultdict(list)
for tp, batch in batches.items():
topics[tp.topic].append((tp.partition, batch.data()))
request = ProduceRequest(
required_acks=self._acks,
timeout=self._request_timeout_ms,
topics=list(topics.items()))
try:
response = yield from self.client.send(node_id, request)
except KafkaError as err:
for batch in batches.values():
if not err.retriable or batch.expired():
batch.done(exception=err)
log.warning(
"Got error produce response: %s", err)
if not err.retriable:
break
else:
if response is None:
# noacks, just "done" batches
for batch in batches.values():
batch.done()
break
for topic, partitions in response.topics:
for partition, error_code, offset in partitions:
tp = TopicPartition(topic, partition)
error = Errors.for_code(error_code)
batch = batches.pop(tp, None)
if batch is None:
continue
if error is Errors.NoError:
batch.done(offset)
elif not getattr(error, 'retriable', False) or \
batch.expired():
batch.done(exception=error())
else:
# Ok, we can retry this batch
batches[tp] = batch
log.warning(
"Got error produce response on topic-partition"
" %s, retrying. Error: %s", tp, error)
if batches:
yield from asyncio.sleep(
self._retry_backoff, loop=self._loop)
else:
break
# if batches for node is processed in less than a linger seconds
# then waiting for the remaining time
sleep_time = self._linger_time - (self._loop.time() - t0)
if sleep_time > 0:
yield from asyncio.sleep(sleep_time, loop=self._loop)
self._in_flight.remove(node_id)
def _serialize(self, topic, key, value):
if self._key_serializer:
serialized_key = self._key_serializer(key)
else:
serialized_key = key
if self._value_serializer:
serialized_value = self._value_serializer(value)
else:
serialized_value = value
message_size = MessageSet.HEADER_SIZE + Message.HEADER_SIZE
if serialized_key is not None:
message_size += len(serialized_key)
if serialized_value is not None:
message_size += len(serialized_value)
if message_size > self._max_request_size:
raise MessageSizeTooLargeError(
"The message is %d bytes when serialized which is larger than"
" the maximum request size you have configured with the"
" max_request_size configuration" % message_size)
return serialized_key, serialized_value
def _partition(self, topic, partition, key, value,
serialized_key, serialized_value):
if partition is not None:
assert partition >= 0
assert partition in self._metadata.partitions_for_topic(topic), \
'Unrecognized partition'
return partition
all_partitions = list(self._metadata.partitions_for_topic(topic))
available = list(self._metadata.available_partitions_for_topic(topic))
return self._partitioner(
serialized_key, all_partitions, available)
class AIOKafkaConsumer(object):
"""Consume records from a Kafka cluster.
The consumer will transparently handle the failure of servers in the Kafka
cluster, and adapt as topic-partitions are created or migrate between
brokers. It also interacts with the assigned kafka Group Coordinator node
to allow multiple consumers to load balance consumption of topics (requires
kafka >= 0.9.0.0).
Arguments:
*topics (str): optional list of topics to subscribe to. If not set,
call subscribe() or assign() before consuming records.
bootstrap_servers: 'host[:port]' string (or list of 'host[:port]'
strings) that the consumer should contact to bootstrap initial
cluster metadata. This does not have to be the full node list.
It just needs to have at least one broker that will respond to a
Metadata API Request. Default port is 9092. If no servers are
specified, will default to localhost:9092.
client_id (str): a name for this client. This string is passed in
each request to servers and can be used to identify specific
server-side log entries that correspond to this client. Also
submitted to GroupCoordinator for logging with respect to
consumer group administration. Default: 'aiokafka-{version}'
group_id (str or None): name of the consumer group to join for dynamic
partition assignment (if enabled), and to use for fetching and
committing offsets. If None, auto-partition assignment (via
group coordinator) and offset commits are disabled.
Default: None
key_deserializer (callable): Any callable that takes a
raw message key and returns a deserialized key.
value_deserializer (callable, optional): Any callable that takes a
raw message value and returns a deserialized value.
fetch_min_bytes (int): Minimum amount of data the server should
return for a fetch request, otherwise wait up to
fetch_max_wait_ms for more data to accumulate. Default: 1.
fetch_max_wait_ms (int): The maximum amount of time in milliseconds
the server will block before answering the fetch request if
there isn't sufficient data to immediately satisfy the
requirement given by fetch_min_bytes. Default: 500.
max_partition_fetch_bytes (int): The maximum amount of data
per-partition the server will return. The maximum total memory
used for a request = #partitions * max_partition_fetch_bytes.
This size must be at least as large as the maximum message size
the server allows or else it is possible for the producer to
send messages larger than the consumer can fetch. If that
happens, the consumer can get stuck trying to fetch a large
message on a certain partition. Default: 1048576.
request_timeout_ms (int): Client request timeout in milliseconds.
Default: 40000.
retry_backoff_ms (int): Milliseconds to backoff when retrying on
errors. Default: 100.
reconnect_backoff_ms (int): The amount of time in milliseconds to
wait before attempting to reconnect to a given host.
Default: 50.
auto_offset_reset (str): A policy for resetting offsets on
OffsetOutOfRange errors: 'earliest' will move to the oldest
available message, 'latest' will move to the most recent. Any
ofther value will raise the exception. Default: 'latest'.
enable_auto_commit (bool): If true the consumer's offset will be
periodically committed in the background. Default: True.
auto_commit_interval_ms (int): milliseconds between automatic
offset commits, if enable_auto_commit is True. Default: 5000.
check_crcs (bool): Automatically check the CRC32 of the records
consumed. This ensures no on-the-wire or on-disk corruption to
the messages occurred. This check adds some overhead, so it may
be disabled in cases seeking extreme performance. Default: True
metadata_max_age_ms (int): The period of time in milliseconds after
which we force a refresh of metadata even if we haven't seen any
partition leadership changes to proactively discover any new
brokers or partitions. Default: 300000
partition_assignment_strategy (list): List of objects to use to
distribute partition ownership amongst consumer instances when
group management is used. This preference is implicit in the order
of the strategies in the list. When assignment strategy changes:
to support a change to the assignment strategy, new versions must
enable support both for the old assignment strategy and the new
one. The coordinator will choose the old assignment strategy until
all members have been updated. Then it will choose the new
strategy. Default: [RoundRobinPartitionAssignor]
heartbeat_interval_ms (int): The expected time in milliseconds
between heartbeats to the consumer coordinator when using
Kafka's group management feature. Heartbeats are used to ensure
that the consumer's session stays active and to facilitate
rebalancing when new consumers join or leave the group. The
value must be set lower than session_timeout_ms, but typically
should be set no higher than 1/3 of that value. It can be
adjusted even lower to control the expected time for normal
rebalances. Default: 3000
session_timeout_ms (int): The timeout used to detect failures when
using Kafka's group managementment facilities. Default: 30000
consumer_timeout_ms (int): number of millisecond to poll available
fetched messages. Default: 100
api_version (str): specify which kafka API version to use.
AIOKafkaConsumer supports Kafka API versions >=0.9 only.
If set to 'auto', will attempt to infer the broker version by
probing various APIs. Default: auto
Note:
Many configuration parameters are taken from Java Client:
https://kafka.apache.org/documentation.html#newconsumerconfigs
"""
def __init__(self,
*topics,
loop,
bootstrap_servers='localhost',
client_id='aiokafka-' + __version__,
group_id=None,
key_deserializer=None,
value_deserializer=None,
fetch_max_wait_ms=500,
fetch_min_bytes=1,
max_partition_fetch_bytes=1 * 1024 * 1024,
request_timeout_ms=40 * 1000,
retry_backoff_ms=100,
reconnect_backoff_ms=50,
auto_offset_reset='latest',
enable_auto_commit=True,
auto_commit_interval_ms=5000,
check_crcs=True,
metadata_max_age_ms=5 * 60 * 1000,
partition_assignment_strategy=(RoundRobinPartitionAssignor, ),
heartbeat_interval_ms=3000,
session_timeout_ms=30000,
consumer_timeout_ms=100,
api_version='auto'):
if api_version not in ('auto', '0.9'):
raise ValueError("Unsupported Kafka API version")
self._client = AIOKafkaClient(loop=loop,
bootstrap_servers=bootstrap_servers,
client_id=client_id,
metadata_max_age_ms=metadata_max_age_ms,
request_timeout_ms=request_timeout_ms)
self._api_version = api_version
self._group_id = group_id
self._heartbeat_interval_ms = heartbeat_interval_ms
self._retry_backoff_ms = retry_backoff_ms
self._enable_auto_commit = enable_auto_commit
self._auto_commit_interval_ms = auto_commit_interval_ms
self._partition_assignment_strategy = partition_assignment_strategy
self._key_deserializer = key_deserializer
self._value_deserializer = value_deserializer
self._fetch_min_bytes = fetch_min_bytes
self._fetch_max_wait_ms = fetch_max_wait_ms
self._max_partition_fetch_bytes = max_partition_fetch_bytes
self._consumer_timeout = consumer_timeout_ms / 1000
self._check_crcs = check_crcs
self._subscription = SubscriptionState(auto_offset_reset)
self._fetcher = None
self._coordinator = None
self._closed = False
self._loop = loop
self._topics = topics
if topics:
self._client.set_topics(topics)
self._subscription.subscribe(topics=topics)
@asyncio.coroutine
def start(self):
yield from self._client.bootstrap()
# Check Broker Version if not set explicitly
if self._api_version == 'auto':
self._api_version = yield from self._client.check_version()
# Convert api_version config to tuple for easy comparisons
self._api_version = tuple(map(int, self._api_version.split('.')))
if self._api_version < (0, 9):
raise ValueError("Unsupported Kafka version: {}".format(
self._api_version))
self._fetcher = Fetcher(
self._client,
self._subscription,
loop=self._loop,
key_deserializer=self._key_deserializer,
value_deserializer=self._value_deserializer,
fetch_min_bytes=self._fetch_min_bytes,
fetch_max_wait_ms=self._fetch_max_wait_ms,
max_partition_fetch_bytes=self._max_partition_fetch_bytes,
check_crcs=self._check_crcs,
fetcher_timeout=self._consumer_timeout)
if self._group_id is not None:
# using group coordinator for automatic partitions assignment
self._coordinator = GroupCoordinator(
self._client,
self._subscription,
loop=self._loop,
group_id=self._group_id,
heartbeat_interval_ms=self._heartbeat_interval_ms,
retry_backoff_ms=self._retry_backoff_ms,
enable_auto_commit=self._enable_auto_commit,
auto_commit_interval_ms=self._auto_commit_interval_ms,
assignors=self._partition_assignment_strategy)
self._coordinator.on_group_rebalanced(self._on_change_subscription)
yield from self._coordinator.ensure_active_group()
elif self._subscription.needs_partition_assignment:
# using manual partitions assignment by topic(s)
yield from self._client.force_metadata_update()
partitions = []
for topic in self._topics:
p_ids = self.partitions_for_topic(topic)
for p_id in p_ids:
partitions.append(TopicPartition(topic, p_id))
self._subscription.unsubscribe()
self._subscription.assign_from_user(partitions)
yield from self._update_fetch_positions(
self._subscription.missing_fetch_positions())
def assign(self, partitions):
"""Manually assign a list of TopicPartitions to this consumer.
Arguments:
partitions (list of TopicPartition): assignment for this instance.
Raises:
IllegalStateError: if consumer has already called subscribe()
Warning:
It is not possible to use both manual partition assignment with
assign() and group assignment with subscribe().
Note:
This interface does not support incremental assignment and will
replace the previous assignment (if there was one).
Note:
Manual topic assignment through this method does not use the
consumer's group management functionality. As such, there will be
no rebalance operation triggered when group membership or cluster
and topic metadata change.
"""
self._subscription.assign_from_user(partitions)
self._on_change_subscription()
self._client.set_topics([tp.topic for tp in partitions])
def assignment(self):
"""Get the TopicPartitions currently assigned to this consumer.
If partitions were directly assigned using assign(), then this will
simply return the same partitions that were previously assigned.
If topics were subscribed using subscribe(), then this will give the
set of topic partitions currently assigned to the consumer (which may
be none if the assignment hasn't happened yet or if the partitions are
in the process of being reassigned).
Returns:
set: {TopicPartition, ...}
"""
return self._subscription.assigned_partitions()
@asyncio.coroutine
def stop(self):
"""Close the consumer, waiting indefinitely for any needed cleanup."""
if self._closed:
return
log.debug("Closing the KafkaConsumer.")
self._closed = True
if self._coordinator:
yield from self._coordinator.close()
if self._fetcher:
yield from self._fetcher.close()
yield from self._client.close()
log.debug("The KafkaConsumer has closed.")
@asyncio.coroutine
def commit(self, offsets=None):
"""Commit offsets to kafka, blocking until success or error
This commits offsets only to Kafka.
The offsets committed using this API will be used on the first fetch
after every rebalance and also on startup. As such, if you needto store
offsets in anything other than Kafka, this API should not be used.
Blocks until either the commit succeeds or an unrecoverable error is
encountered (in which case it is thrown to the caller).
Currently only supports kafka-topic offset storage (not zookeeper)
Arguments:
offsets (dict, optional): {TopicPartition: OffsetAndMetadata} dict
to commit with the configured group_id. Defaults to current
consumed offsets for all subscribed partitions.
"""
assert self._group_id is not None, 'Requires group_id'
if offsets is None:
offsets = self._subscription.all_consumed_offsets()
else:
# validate `offsets` structure
assert all(map(lambda k: isinstance(k, TopicPartition), offsets))
assert all(
map(lambda v: isinstance(v, OffsetAndMetadata),
offsets.values()))
yield from self._coordinator.commit_offsets(offsets)
@asyncio.coroutine
def committed(self, partition):
"""Get the last committed offset for the given partition
This offset will be used as the position for the consumer
in the event of a failure.
This call may block to do a remote call if the partition in question
isn't assigned to this consumer or if the consumer hasn't yet
initialized its cache of committed offsets.
Arguments:
partition (TopicPartition): the partition to check
Returns:
The last committed offset, or None if there was no prior commit.
"""
assert self._group_id is not None, 'Requires group_id'
if self._subscription.is_assigned(partition):
committed = self._subscription.assignment[partition].committed
if committed is None:
yield from self._coordinator.refresh_committed_offsets()
committed = self._subscription.assignment[partition].committed
else:
commit_map = yield from self._coordinator.fetch_committed_offsets(
[partition])
if partition in commit_map:
committed = commit_map[partition].offset
else:
committed = None
return committed
@asyncio.coroutine
def topics(self):
"""Get all topics the user is authorized to view.
Returns:
set: topics
"""
cluster = yield from self._client.fetch_all_metadata()
return cluster.topics()
def partitions_for_topic(self, topic):
"""Get metadata about the partitions for a given topic.
Arguments:
topic (str): topic to check
Returns:
set: partition ids
"""
return self._client.cluster.partitions_for_topic(topic)
@asyncio.coroutine
def position(self, partition):
"""Get the offset of the next record that will be fetched
Arguments:
partition (TopicPartition): partition to check
Returns:
int: offset
"""
assert self._subscription.is_assigned(partition), \
'Partition is not assigned'
offset = self._subscription.assignment[partition].position
if offset is None:
yield from self._update_fetch_positions(partition)
offset = self._subscription.assignment[partition].position
return offset
def highwater(self, partition):
"""Last known highwater offset for a partition
A highwater offset is the offset that will be assigned to the next
message that is produced. It may be useful for calculating lag, by
comparing with the reported position. Note that both position and
highwater refer to the *next* offset -- i.e., highwater offset is
one greater than the newest availabel message.
Highwater offsets are returned in FetchResponse messages, so will
not be available if not FetchRequests have been sent for this partition
yet.
Arguments:
partition (TopicPartition): partition to check
Returns:
int or None: offset if available
"""
assert self._subscription.is_assigned(partition), \
'Partition is not assigned'
return self._subscription.assignment[partition].highwater
def seek(self, partition, offset):
"""Manually specify the fetch offset for a TopicPartition.
Overrides the fetch offsets that the consumer will use on the next
poll(). If this API is invoked for the same partition more than once,
the latest offset will be used on the next poll(). Note that you may
lose data if this API is arbitrarily used in the middle of consumption,
to reset the fetch offsets.
Arguments:
partition (TopicPartition): partition for seek operation
offset (int): message offset in partition
Raises:
AssertionError: if offset is not an int >= 0;
or if partition is not currently assigned.
"""
assert isinstance(offset, int) and offset >= 0, 'Offset must be >= 0'
assert partition in self._subscription.assigned_partitions(), \
'Unassigned partition'
log.debug("Seeking to offset %s for partition %s", offset, partition)
self._subscription.assignment[partition].seek(offset)
@asyncio.coroutine
def seek_to_committed(self, *partitions):
"""Seek to the committed offset for partitions
Arguments:
partitions: optionally provide specific TopicPartitions,
otherwise default to all assigned partitions
Raises:
AssertionError: if any partition is not currently assigned, or if
no partitions are assigned
"""
if not partitions:
partitions = self._subscription.assigned_partitions()
assert partitions, 'No partitions are currently assigned'
else:
for p in partitions:
assert p in self._subscription.assigned_partitions(), \
'Unassigned partition'
for tp in partitions:
log.debug("Seeking to committed of partition %s", tp)
offset = yield from self.committed(tp)
if offset and offset > 0:
self.seek(tp, offset)
def subscribe(self, topics=(), pattern=None, listener=None):
"""Subscribe to a list of topics, or a topic regex pattern
Partitions will be dynamically assigned via a group coordinator.
Topic subscriptions are not incremental: this list will replace the
current assignment (if there is one).
This method is incompatible with assign()
Arguments:
topics (list): List of topics for subscription.
pattern (str): Pattern to match available topics. You must provide
either topics or pattern, but not both.
listener (ConsumerRebalanceListener): Optionally include listener
callback, which will be called before and after each rebalance
operation.
As part of group management, the consumer will keep track of
the list of consumers that belong to a particular group and
will trigger a rebalance operation if one of the following
events trigger:
* Number of partitions change for any of the subscribed topics
* Topic is created or deleted
* An existing member of the consumer group dies
* A new member is added to the consumer group
When any of these events are triggered, the provided listener
will be invoked first to indicate that the consumer's
assignment has been revoked, and then again when the new
assignment has been received. Note that this listener will
immediately override any listener set in a previous call
to subscribe. It is guaranteed, however, that the partitions
revoked/assigned
through this interface are from topics subscribed in this call.
Raises:
IllegalStateError: if called after previously calling assign()
AssertionError: if neither topics or pattern is provided
TypeError: if listener is not a ConsumerRebalanceListener
"""
# SubscriptionState handles error checking
self._subscription.subscribe(topics=topics,
pattern=pattern,
listener=listener)
# regex will need all topic metadata
if pattern is not None:
self._client.set_topics([])
log.debug("Subscribed to topic pattern: %s", pattern)
else:
self._client.set_topics(self._subscription.group_subscription())
log.debug("Subscribed to topic(s): %s", topics)
def subscription(self):
"""Get the current topic subscription.
Returns:
set: {topic, ...}
"""
return self._subscription.subscription
def unsubscribe(self):
"""Unsubscribe from all topics and clear all assigned partitions."""
self._subscription.unsubscribe()
self._client.set_topics([])
log.debug(
"Unsubscribed all topics or patterns and assigned partitions")
@asyncio.coroutine
def _update_fetch_positions(self, partitions):
"""
Set the fetch position to the committed position (if there is one)
or reset it using the offset reset policy the user has configured.
Arguments:
partitions (List[TopicPartition]): The partitions that need
updating fetch positions
Raises:
NoOffsetForPartitionError: If no offset is stored for a given
partition and no offset reset policy is defined
"""
if self._group_id is not None:
# refresh commits for all assigned partitions
yield from self._coordinator.refresh_committed_offsets()
# then do any offset lookups in case some positions are not known
yield from self._fetcher.update_fetch_positions(partitions)
def _on_change_subscription(self):
"""This is `group rebalanced` signal handler for update fetch positions
of assigned partitions"""
# fetch positions if we have partitions we're subscribed
# to that we don't know the offset for
if not self._subscription.has_all_fetch_positions():
ensure_future(self._update_fetch_positions(
self._subscription.missing_fetch_positions()),
loop=self._loop)
@asyncio.coroutine
def getone(self, *partitions):
"""
Get one message from Kafka
If no new messages prefetched, this method will wait for it
Arguments:
partitions (List[TopicPartition]): Optional list of partitions to
return from. If no partitions specified then returned message
will be from any partition, which consumer is subscribed to.
Returns:
ConsumerRecord
Will return instance of
.. code:: python
collections.namedtuple(
"ConsumerRecord",
["topic", "partition", "offset", "key", "value"])
Example usage:
.. code:: python
while True:
message = yield from consumer.getone()
topic = message.topic
partition = message.partition
# Process message
print(message.offset, message.key, message.value)
"""
assert all(map(lambda k: isinstance(k, TopicPartition), partitions))
msg = yield from self._fetcher.next_record(partitions)
return msg
@asyncio.coroutine
def getmany(self, *partitions, timeout_ms=0):
"""Get messages from assigned topics / partitions.
Prefetched messages are returned in batches by topic-partition.
If messages is not available in the prefetched buffer this method waits
`timeout_ms` milliseconds.
Arguments:
partitions (List[TopicPartition]): The partitions that need
fetching message. If no one partition specified then all
subscribed partitions will be used
timeout_ms (int, optional): milliseconds spent waiting if
data is not available in the buffer. If 0, returns immediately
with any records that are available currently in the buffer,
else returns empty. Must not be negative. Default: 0
Returns:
dict: topic to list of records since the last fetch for the
subscribed list of topics and partitions
Example usage:
.. code:: python
data = yield from consumer.getmany()
for tp, messages in data.items():
topic = tp.topic
partition = tp.partition
for message in messages:
# Process message
print(message.offset, message.key, message.value)
"""
assert all(map(lambda k: isinstance(k, TopicPartition), partitions))
timeout = timeout_ms / 1000
records = yield from self._fetcher.fetched_records(partitions, timeout)
return records
if PY_35:
@asyncio.coroutine
def __aiter__(self):
return self
@asyncio.coroutine
def __anext__(self):
return (yield from self.getone())
