async def test_bootstrap(self): client = AIOKafkaClient(bootstrap_servers='0.42.42.42:444') with self.assertRaises(KafkaConnectionError): await client.bootstrap() client = AIOKafkaClient(bootstrap_servers=self.hosts) await client.bootstrap() await self.wait_topic(client, 'test_topic') metadata = await client.fetch_all_metadata() self.assertTrue('test_topic' in metadata.topics()) client.set_topics(['t2', 't3']) client.set_topics(['t2', 't3']) # should be ignored client.add_topic('t2') # should be ignored # bootstrap again -- no error expected await client.bootstrap() await client.close()
def test_bootstrap(self): client = AIOKafkaClient(loop=self.loop, bootstrap_servers='0.42.42.42:444') with self.assertRaises(ConnectionError): yield from client.bootstrap() client = AIOKafkaClient(loop=self.loop, bootstrap_servers=self.hosts) yield from client.bootstrap() yield from self.wait_topic(client, 'test_topic') metadata = yield from client.fetch_all_metadata() self.assertTrue('test_topic' in metadata.topics()) client.set_topics(['t2', 't3']) client.set_topics(['t2', 't3']) # should be ignored client.add_topic('t2') # shold be ignored # bootstrap again -- no error expected yield from client.bootstrap() 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 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)