import copy import logging from collections import defaultdict from functools import partial from itertools import count from kafka.common import (ErrorMapping, TopicAndPartition, ConnectionError, FailedPayloadsError, BrokerResponseError, PartitionUnavailableError, KafkaUnavailableError, KafkaRequestError) from kafka.conn import collect_hosts, KafkaConnection, DEFAULT_SOCKET_TIMEOUT_SECONDS from kafka.protocol import KafkaProtocol log = logging.getLogger("kafka") class KafkaClient(object): CLIENT_ID = "kafka-python" ID_GEN = count() # NOTE: The timeout given to the client should always be greater than the # one passed to SimpleConsumer.get_message(), otherwise you can get a # socket timeout. def __init__(self, hosts, client_id=CLIENT_ID, timeout=DEFAULT_SOCKET_TIMEOUT_SECONDS): # We need one connection to bootstrap self.client_id = client_id self.timeout = timeout self.hosts = collect_hosts(hosts) # create connections only when we need them self.conns = {} self.brokers = {} # broker_id -> BrokerMetadata self.topics_to_brokers = {} # topic_id -> broker_id self.topic_partitions = {} # topic_id -> [0, 1, 2, ...] self.load_metadata_for_topics() # bootstrap with all metadata ################## # Private API # ################## def _get_conn(self, host, port): "Get or create a connection to a broker using host and port" host_key = (host, port) if host_key not in self.conns: self.conns[host_key] = KafkaConnection(host, port) return self.conns[host_key] def _get_conn_for_broker(self, broker): """ Get or create a connection to a broker """ if (broker.host, broker.port) not in self.conns: self.conns[(broker.host, broker.port)] = \ KafkaConnection(broker.host, broker.port, timeout=self.timeout) return self._get_conn(broker.host, broker.port) def _get_leader_for_partition(self, topic, partition): key = TopicAndPartition(topic, partition) if key not in self.topics_to_brokers: self.load_metadata_for_topics(topic) if key not in self.topics_to_brokers: raise KafkaRequestError("Partition does not exist: %s" % str(key)) return self.topics_to_brokers[key] def _next_id(self): """ Generate a new correlation id """ return KafkaClient.ID_GEN.next() def _send_broker_unaware_request(self, requestId, request): """ Attempt to send a broker-agnostic request to one of the available brokers. Keep trying until you succeed. """ for (host, port) in self.hosts: try: conn = self._get_conn(host, port) conn.send(requestId, request) response = conn.recv(requestId) return response except Exception, e: log.warning("Could not send request [%r] to server %s:%i, " "trying next server: %s" % (request, host, port, e)) continue raise KafkaUnavailableError("All servers failed to process request") def _send_broker_aware_request(self, payloads, encoder_fn, decoder_fn): """ Group a list of request payloads by topic+partition and send them to the leader broker for that partition using the supplied encode/decode functions Params ====== payloads: list of object-like entities with a topic and partition attribute encode_fn: a method to encode the list of payloads to a request body, must accept client_id, correlation_id, and payloads as keyword arguments decode_fn: a method to decode a response body into response objects. The response objects must be object-like and have topic and partition attributes Return ====== List of response objects in the same order as the supplied payloads """ # Group the requests by topic+partition original_keys = [] payloads_by_broker = defaultdict(list) for payload in payloads: leader = self._get_leader_for_partition(payload.topic, payload.partition) if leader == -1: raise PartitionUnavailableError("Leader is unassigned for %s-%s" % payload.topic, payload.partition) payloads_by_broker[leader].append(payload) original_keys.append((payload.topic, payload.partition)) # Accumulate the responses in a dictionary acc = {} # keep a list of payloads that were failed to be sent to brokers failed_payloads = [] # For each broker, send the list of request payloads for broker, payloads in payloads_by_broker.items(): conn = self._get_conn_for_broker(broker) requestId = self._next_id() request = encoder_fn(client_id=self.client_id, correlation_id=requestId, payloads=payloads) failed = False # Send the request, recv the response try: conn.send(requestId, request) if decoder_fn is None: continue try: response = conn.recv(requestId) except ConnectionError, e: log.warning("Could not receive response to request [%s] " "from server %s: %s", request, conn, e) failed = True except ConnectionError, e: log.warning("Could not send request [%s] to server %s: %s", request, conn, e) failed = True if failed: failed_payloads += payloads self.reset_all_metadata() continue for response in decoder_fn(response): acc[(response.topic, response.partition)] = response if failed_payloads: raise FailedPayloadsError(failed_payloads) # Order the accumulated responses by the original key order return (acc[k] for k in original_keys) if acc else () def __repr__(self): return '' % (self.client_id) def _raise_on_response_error(self, resp): if resp.error == ErrorMapping.NO_ERROR: return if resp.error in (ErrorMapping.UNKNOWN_TOPIC_OR_PARTITON, ErrorMapping.NOT_LEADER_FOR_PARTITION): self.reset_topic_metadata(resp.topic) raise BrokerResponseError( "Request for %s failed with errorcode=%d" % (TopicAndPartition(resp.topic, resp.partition), resp.error)) ################# # Public API # ################# def reset_topic_metadata(self, *topics): for topic in topics: try: partitions = self.topic_partitions[topic] except KeyError: continue for partition in partitions: self.topics_to_brokers.pop(TopicAndPartition(topic, partition), None) del self.topic_partitions[topic] def reset_all_metadata(self): self.topics_to_brokers.clear() self.topic_partitions.clear() def has_metadata_for_topic(self, topic): return topic in self.topic_partitions def close(self): for conn in self.conns.values(): conn.close() def copy(self): """ Create an inactive copy of the client object A reinit() has to be done on the copy before it can be used again """ c = copy.deepcopy(self) for k, v in c.conns.items(): c.conns[k] = v.copy() return c def reinit(self): for conn in self.conns.values(): conn.reinit() def load_metadata_for_topics(self, *topics): """ Discover brokers and metadata for a set of topics. This function is called lazily whenever metadata is unavailable. """ request_id = self._next_id() request = KafkaProtocol.encode_metadata_request(self.client_id, request_id, topics) response = self._send_broker_unaware_request(request_id, request) (brokers, topics) = KafkaProtocol.decode_metadata_response(response) log.debug("Broker metadata: %s", brokers) log.debug("Topic metadata: %s", topics) self.brokers = brokers for topic, partitions in topics.items(): self.reset_topic_metadata(topic) if not partitions: continue self.topic_partitions[topic] = [] for partition, meta in partitions.items(): topic_part = TopicAndPartition(topic, partition) self.topics_to_brokers[topic_part] = brokers[meta.leader] self.topic_partitions[topic].append(partition) def send_produce_request(self, payloads=[], acks=1, timeout=1000, fail_on_error=True, callback=None): """ Encode and send some ProduceRequests ProduceRequests will be grouped by (topic, partition) and then sent to a specific broker. Output is a list of responses in the same order as the list of payloads specified Params ====== payloads: list of ProduceRequest fail_on_error: boolean, should we raise an Exception if we encounter an API error? callback: function, instead of returning the ProduceResponse, first pass it through this function Return ====== list of ProduceResponse or callback(ProduceResponse), in the order of input payloads """ encoder = partial( KafkaProtocol.encode_produce_request, acks=acks, timeout=timeout) if acks == 0: decoder = None else: decoder = KafkaProtocol.decode_produce_response resps = self._send_broker_aware_request(payloads, encoder, decoder) out = [] for resp in resps: if fail_on_error is True: self._raise_on_response_error(resp) if callback is not None: out.append(callback(resp)) else: out.append(resp) return out def send_fetch_request(self, payloads=[], fail_on_error=True, callback=None, max_wait_time=100, min_bytes=4096): """ Encode and send a FetchRequest Payloads are grouped by topic and partition so they can be pipelined to the same brokers. """ encoder = partial(KafkaProtocol.encode_fetch_request, max_wait_time=max_wait_time, min_bytes=min_bytes) resps = self._send_broker_aware_request( payloads, encoder, KafkaProtocol.decode_fetch_response) out = [] for resp in resps: if fail_on_error is True: self._raise_on_response_error(resp) if callback is not None: out.append(callback(resp)) else: out.append(resp) return out def send_offset_request(self, payloads=[], fail_on_error=True, callback=None): resps = self._send_broker_aware_request( payloads, KafkaProtocol.encode_offset_request, KafkaProtocol.decode_offset_response) out = [] for resp in resps: if fail_on_error is True: self._raise_on_response_error(resp) if callback is not None: out.append(callback(resp)) else: out.append(resp) return out def send_offset_commit_request(self, group, payloads=[], fail_on_error=True, callback=None): encoder = partial(KafkaProtocol.encode_offset_commit_request, group=group) decoder = KafkaProtocol.decode_offset_commit_response resps = self._send_broker_aware_request(payloads, encoder, decoder) out = [] for resp in resps: if fail_on_error is True: self._raise_on_response_error(resp) if callback is not None: out.append(callback(resp)) else: out.append(resp) return out def send_offset_fetch_request(self, group, payloads=[], fail_on_error=True, callback=None): encoder = partial(KafkaProtocol.encode_offset_fetch_request, group=group) decoder = KafkaProtocol.decode_offset_fetch_response resps = self._send_broker_aware_request(payloads, encoder, decoder) out = [] for resp in resps: if fail_on_error is True: self._raise_on_response_error(resp) if callback is not None: out.append(callback(resp)) else: out.append(resp) return out