513 lines
18 KiB
Python
513 lines
18 KiB
Python
import binascii
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import collections
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import copy
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import functools
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import logging
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import time
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import kafka.common
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from kafka.common import (TopicAndPartition, BrokerMetadata,
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ConnectionError, FailedPayloadsError,
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KafkaTimeoutError, KafkaUnavailableError,
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LeaderNotAvailableError, UnknownTopicOrPartitionError,
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NotLeaderForPartitionError, ReplicaNotAvailableError)
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from kafka.conn import collect_hosts, KafkaConnection, DEFAULT_SOCKET_TIMEOUT_SECONDS
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from kafka.protocol import KafkaProtocol
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from kafka.util import kafka_bytestring
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log = logging.getLogger("kafka")
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class KafkaClient(object):
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CLIENT_ID = b"kafka-python"
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# NOTE: The timeout given to the client should always be greater than the
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# one passed to SimpleConsumer.get_message(), otherwise you can get a
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# socket timeout.
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def __init__(self, hosts, client_id=CLIENT_ID,
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timeout=DEFAULT_SOCKET_TIMEOUT_SECONDS,
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correlation_id=0):
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# We need one connection to bootstrap
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self.client_id = kafka_bytestring(client_id)
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self.timeout = timeout
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self.hosts = collect_hosts(hosts)
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self.correlation_id = correlation_id
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# create connections only when we need them
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self.conns = {}
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self.brokers = {} # broker_id -> BrokerMetadata
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self.topics_to_brokers = {} # TopicAndPartition -> BrokerMetadata
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self.topic_partitions = {} # topic -> partition -> PartitionMetadata
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self.load_metadata_for_topics() # bootstrap with all metadata
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##################
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# Private API #
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##################
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def _get_conn(self, host, port):
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"Get or create a connection to a broker using host and port"
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host_key = (host, port)
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if host_key not in self.conns:
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self.conns[host_key] = KafkaConnection(
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host,
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port,
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timeout=self.timeout
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)
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return self.conns[host_key]
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def _get_leader_for_partition(self, topic, partition):
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"""
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Returns the leader for a partition or None if the partition exists
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but has no leader.
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UnknownTopicOrPartitionError will be raised if the topic or partition
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is not part of the metadata.
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LeaderNotAvailableError is raised if server has metadata, but there is
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no current leader
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"""
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key = TopicAndPartition(topic, partition)
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# Use cached metadata if it is there
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if self.topics_to_brokers.get(key) is not None:
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return self.topics_to_brokers[key]
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# Otherwise refresh metadata
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# If topic does not already exist, this will raise
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# UnknownTopicOrPartitionError if not auto-creating
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# LeaderNotAvailableError otherwise until partitions are created
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self.load_metadata_for_topics(topic)
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# If the partition doesn't actually exist, raise
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if partition not in self.topic_partitions.get(topic, []):
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raise UnknownTopicOrPartitionError(key)
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# If there's no leader for the partition, raise
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meta = self.topic_partitions[topic][partition]
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if meta.leader == -1:
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raise LeaderNotAvailableError(meta)
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# Otherwise return the BrokerMetadata
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return self.brokers[meta.leader]
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def _next_id(self):
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"""Generate a new correlation id"""
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# modulo to keep w/i int32
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self.correlation_id = (self.correlation_id + 1) % 2**31
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return self.correlation_id
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def _send_broker_unaware_request(self, payloads, encoder_fn, decoder_fn):
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"""
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Attempt to send a broker-agnostic request to one of the available
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brokers. Keep trying until you succeed.
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"""
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for (host, port) in self.hosts:
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requestId = self._next_id()
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try:
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conn = self._get_conn(host, port)
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request = encoder_fn(client_id=self.client_id,
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correlation_id=requestId,
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payloads=payloads)
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conn.send(requestId, request)
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response = conn.recv(requestId)
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return decoder_fn(response)
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except Exception:
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log.exception("Could not send request [%r] to server %s:%i, "
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"trying next server" % (requestId, host, port))
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raise KafkaUnavailableError("All servers failed to process request")
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def _send_broker_aware_request(self, payloads, encoder_fn, decoder_fn):
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"""
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Group a list of request payloads by topic+partition and send them to
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the leader broker for that partition using the supplied encode/decode
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functions
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Arguments:
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payloads: list of object-like entities with a topic (str) and
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partition (int) attribute
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encode_fn: a method to encode the list of payloads to a request body,
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must accept client_id, correlation_id, and payloads as
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keyword arguments
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decode_fn: a method to decode a response body into response objects.
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The response objects must be object-like and have topic
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and partition attributes
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Returns:
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List of response objects in the same order as the supplied payloads
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"""
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# Group the requests by topic+partition
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original_keys = []
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payloads_by_broker = collections.defaultdict(list)
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for payload in payloads:
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leader = self._get_leader_for_partition(payload.topic,
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payload.partition)
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payloads_by_broker[leader].append(payload)
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original_keys.append((payload.topic, payload.partition))
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# Accumulate the responses in a dictionary
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acc = {}
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# keep a list of payloads that were failed to be sent to brokers
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failed_payloads = []
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# For each broker, send the list of request payloads
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for broker, payloads in payloads_by_broker.items():
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conn = self._get_conn(broker.host.decode('utf-8'), broker.port)
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requestId = self._next_id()
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request = encoder_fn(client_id=self.client_id,
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correlation_id=requestId, payloads=payloads)
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failed = False
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# Send the request, recv the response
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try:
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conn.send(requestId, request)
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# decoder_fn=None signal that the server is expected to not
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# send a response. This probably only applies to
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# ProduceRequest w/ acks = 0
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if decoder_fn is None:
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continue
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try:
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response = conn.recv(requestId)
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except ConnectionError as e:
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log.warning("Could not receive response to request [%s] "
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"from server %s: %s", binascii.b2a_hex(request), conn, e)
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failed = True
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except ConnectionError as e:
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log.warning("Could not send request [%s] to server %s: %s",
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binascii.b2a_hex(request), conn, e)
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failed = True
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if failed:
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failed_payloads += payloads
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self.reset_all_metadata()
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continue
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for response in decoder_fn(response):
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acc[(response.topic, response.partition)] = response
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if failed_payloads:
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raise FailedPayloadsError(failed_payloads)
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# Order the accumulated responses by the original key order
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return (acc[k] for k in original_keys) if acc else ()
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def __repr__(self):
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return '<KafkaClient client_id=%s>' % (self.client_id)
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def _raise_on_response_error(self, resp):
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try:
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kafka.common.check_error(resp)
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except (UnknownTopicOrPartitionError, NotLeaderForPartitionError):
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self.reset_topic_metadata(resp.topic)
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raise
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#################
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# Public API #
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#################
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def close(self):
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for conn in self.conns.values():
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conn.close()
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def copy(self):
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"""
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Create an inactive copy of the client object
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A reinit() has to be done on the copy before it can be used again
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"""
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c = copy.deepcopy(self)
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for key in c.conns:
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c.conns[key] = self.conns[key].copy()
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return c
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def reinit(self):
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for conn in self.conns.values():
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conn.reinit()
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def reset_topic_metadata(self, *topics):
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for topic in topics:
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try:
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partitions = self.topic_partitions[topic]
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except KeyError:
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continue
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for partition in partitions:
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self.topics_to_brokers.pop(TopicAndPartition(topic, partition), None)
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del self.topic_partitions[topic]
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def reset_all_metadata(self):
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self.topics_to_brokers.clear()
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self.topic_partitions.clear()
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def has_metadata_for_topic(self, topic):
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topic = kafka_bytestring(topic)
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return (
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topic in self.topic_partitions
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and len(self.topic_partitions[topic]) > 0
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)
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def get_partition_ids_for_topic(self, topic):
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topic = kafka_bytestring(topic)
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if topic not in self.topic_partitions:
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return []
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return sorted(list(self.topic_partitions[topic]))
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def ensure_topic_exists(self, topic, timeout = 30):
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start_time = time.time()
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while not self.has_metadata_for_topic(topic):
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if time.time() > start_time + timeout:
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raise KafkaTimeoutError("Unable to create topic {0}".format(topic))
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try:
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self.load_metadata_for_topics(topic)
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except LeaderNotAvailableError:
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pass
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except UnknownTopicOrPartitionError:
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# Server is not configured to auto-create
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# retrying in this case will not help
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raise
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time.sleep(.5)
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def load_metadata_for_topics(self, *topics):
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"""
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Fetch broker and topic-partition metadata from the server,
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and update internal data:
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broker list, topic/partition list, and topic/parition -> broker map
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This method should be called after receiving any error
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Arguments:
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*topics (optional): If a list of topics is provided,
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the metadata refresh will be limited to the specified topics only.
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Exceptions:
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----------
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If the broker is configured to not auto-create topics,
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expect UnknownTopicOrPartitionError for topics that don't exist
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If the broker is configured to auto-create topics,
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expect LeaderNotAvailableError for new topics
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until partitions have been initialized.
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Exceptions *will not* be raised in a full refresh (i.e. no topic list)
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In this case, error codes will be logged as errors
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Partition-level errors will also not be raised here
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(a single partition w/o a leader, for example)
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"""
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topics = [kafka_bytestring(t) for t in topics]
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resp = self.send_metadata_request(topics)
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log.debug("Broker metadata: %s", resp.brokers)
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log.debug("Topic metadata: %s", resp.topics)
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self.brokers = dict([(broker.nodeId, broker)
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for broker in resp.brokers])
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for topic_metadata in resp.topics:
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topic = topic_metadata.topic
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partitions = topic_metadata.partitions
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self.reset_topic_metadata(topic)
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# Errors expected for new topics
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try:
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kafka.common.check_error(topic_metadata)
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except (UnknownTopicOrPartitionError, LeaderNotAvailableError) as e:
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# Raise if the topic was passed in explicitly
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if topic in topics:
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raise
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# Otherwise, just log a warning
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log.error("Error loading topic metadata for %s: %s", topic, type(e))
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continue
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self.topic_partitions[topic] = {}
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for partition_metadata in partitions:
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partition = partition_metadata.partition
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leader = partition_metadata.leader
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self.topic_partitions[topic][partition] = partition_metadata
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# Populate topics_to_brokers dict
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topic_part = TopicAndPartition(topic, partition)
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# Check for partition errors
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try:
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kafka.common.check_error(partition_metadata)
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# If No Leader, topics_to_brokers topic_partition -> None
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except LeaderNotAvailableError:
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log.error('No leader for topic %s partition %d', topic, partition)
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self.topics_to_brokers[topic_part] = None
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continue
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# If one of the replicas is unavailable -- ignore
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# this error code is provided for admin purposes only
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# we never talk to replicas, only the leader
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except ReplicaNotAvailableError:
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log.warning('Some (non-leader) replicas not available for topic %s partition %d', topic, partition)
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# If Known Broker, topic_partition -> BrokerMetadata
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if leader in self.brokers:
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self.topics_to_brokers[topic_part] = self.brokers[leader]
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# If Unknown Broker, fake BrokerMetadata so we dont lose the id
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# (not sure how this could happen. server could be in bad state)
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else:
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self.topics_to_brokers[topic_part] = BrokerMetadata(
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leader, None, None
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)
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def send_metadata_request(self, payloads=[], fail_on_error=True,
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callback=None):
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encoder = KafkaProtocol.encode_metadata_request
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decoder = KafkaProtocol.decode_metadata_response
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return self._send_broker_unaware_request(payloads, encoder, decoder)
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def send_produce_request(self, payloads=[], acks=1, timeout=1000,
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fail_on_error=True, callback=None):
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"""
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Encode and send some ProduceRequests
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ProduceRequests will be grouped by (topic, partition) and then
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sent to a specific broker. Output is a list of responses in the
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same order as the list of payloads specified
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Arguments:
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payloads: list of ProduceRequest
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fail_on_error: boolean, should we raise an Exception if we
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encounter an API error?
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callback: function, instead of returning the ProduceResponse,
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first pass it through this function
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Returns:
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list of ProduceResponse or callback(ProduceResponse), in the
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order of input payloads
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"""
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encoder = functools.partial(
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KafkaProtocol.encode_produce_request,
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acks=acks,
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timeout=timeout)
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if acks == 0:
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decoder = None
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else:
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decoder = KafkaProtocol.decode_produce_response
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resps = self._send_broker_aware_request(payloads, encoder, decoder)
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out = []
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for resp in resps:
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if fail_on_error is True:
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self._raise_on_response_error(resp)
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if callback is not None:
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out.append(callback(resp))
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else:
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out.append(resp)
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return out
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def send_fetch_request(self, payloads=[], fail_on_error=True,
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callback=None, max_wait_time=100, min_bytes=4096):
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"""
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Encode and send a FetchRequest
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Payloads are grouped by topic and partition so they can be pipelined
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to the same brokers.
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"""
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encoder = functools.partial(KafkaProtocol.encode_fetch_request,
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max_wait_time=max_wait_time,
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min_bytes=min_bytes)
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resps = self._send_broker_aware_request(
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payloads, encoder,
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KafkaProtocol.decode_fetch_response)
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out = []
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for resp in resps:
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if fail_on_error is True:
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self._raise_on_response_error(resp)
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if callback is not None:
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out.append(callback(resp))
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else:
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out.append(resp)
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return out
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def send_offset_request(self, payloads=[], fail_on_error=True,
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callback=None):
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resps = self._send_broker_aware_request(
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payloads,
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KafkaProtocol.encode_offset_request,
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KafkaProtocol.decode_offset_response)
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out = []
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for resp in resps:
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if fail_on_error is True:
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self._raise_on_response_error(resp)
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if callback is not None:
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out.append(callback(resp))
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else:
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out.append(resp)
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return out
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def send_offset_commit_request(self, group, payloads=[],
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fail_on_error=True, callback=None):
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encoder = functools.partial(KafkaProtocol.encode_offset_commit_request,
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group=group)
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decoder = KafkaProtocol.decode_offset_commit_response
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resps = self._send_broker_aware_request(payloads, encoder, decoder)
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out = []
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for resp in resps:
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if fail_on_error is True:
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self._raise_on_response_error(resp)
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if callback is not None:
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out.append(callback(resp))
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else:
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out.append(resp)
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return out
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def send_offset_fetch_request(self, group, payloads=[],
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fail_on_error=True, callback=None):
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encoder = functools.partial(KafkaProtocol.encode_offset_fetch_request,
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group=group)
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decoder = KafkaProtocol.decode_offset_fetch_response
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resps = self._send_broker_aware_request(payloads, encoder, decoder)
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out = []
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for resp in resps:
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if fail_on_error is True:
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self._raise_on_response_error(resp)
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if callback is not None:
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out.append(callback(resp))
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else:
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out.append(resp)
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return out
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