import binascii
import collections
import copy
import functools
import itertools
import logging
import time
import kafka.common
from kafka.common import (TopicAndPartition, BrokerMetadata,
ConnectionError, FailedPayloadsError,
KafkaTimeoutError, KafkaUnavailableError,
LeaderNotAvailableError, UnknownTopicOrPartitionError,
NotLeaderForPartitionError, ReplicaNotAvailableError)
from kafka.conn import collect_hosts, KafkaConnection, DEFAULT_SOCKET_TIMEOUT_SECONDS
from kafka.protocol import KafkaProtocol
log = logging.getLogger("kafka")
[docs]class KafkaClient(object):
CLIENT_ID = b"kafka-python"
ID_GEN = itertools.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 = {} # TopicAndPartition -> BrokerMetadata
self.topic_partitions = {} # topic -> partition -> PartitionMetadata
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,
timeout=self.timeout
)
return self.conns[host_key]
def _get_leader_for_partition(self, topic, partition):
"""
Returns the leader for a partition or None if the partition exists
but has no leader.
UnknownTopicOrPartitionError will be raised if the topic or partition
is not part of the metadata.
LeaderNotAvailableError is raised if server has metadata, but there is
no current leader
"""
key = TopicAndPartition(topic, partition)
# Use cached metadata if it is there
if self.topics_to_brokers.get(key) is not None:
return self.topics_to_brokers[key]
# Otherwise refresh metadata
# If topic does not already exist, this will raise
# UnknownTopicOrPartitionError if not auto-creating
# LeaderNotAvailableError otherwise until partitions are created
self.load_metadata_for_topics(topic)
# If the partition doesn't actually exist, raise
if partition not in self.topic_partitions[topic]:
raise UnknownTopicOrPartitionError(key)
# If there's no leader for the partition, raise
meta = self.topic_partitions[topic][partition]
if meta.leader == -1:
raise LeaderNotAvailableError(meta)
# Otherwise return the BrokerMetadata
return self.brokers[meta.leader]
def _next_id(self):
"""
Generate a new correlation id
"""
return next(KafkaClient.ID_GEN)
def _send_broker_unaware_request(self, payloads, encoder_fn, decoder_fn):
"""
Attempt to send a broker-agnostic request to one of the available
brokers. Keep trying until you succeed.
"""
for (host, port) in self.hosts:
requestId = self._next_id()
try:
conn = self._get_conn(host, port)
request = encoder_fn(client_id=self.client_id,
correlation_id=requestId,
payloads=payloads)
conn.send(requestId, request)
response = conn.recv(requestId)
return decoder_fn(response)
except Exception:
log.exception("Could not send request [%r] to server %s:%i, "
"trying next server" % (requestId, host, port))
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
Arguments:
payloads: list of object-like entities with a topic (str) and
partition (int) 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
Returns:
List of response objects in the same order as the supplied payloads
"""
# Group the requests by topic+partition
original_keys = []
payloads_by_broker = collections.defaultdict(list)
for payload in payloads:
leader = self._get_leader_for_partition(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(broker.host.decode('utf-8'), broker.port)
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 as e:
log.warning("Could not receive response to request [%s] "
"from server %s: %s", binascii.b2a_hex(request), conn, e)
failed = True
except ConnectionError as e:
log.warning("Could not send request [%s] to server %s: %s",
binascii.b2a_hex(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 '<KafkaClient client_id=%s>' % (self.client_id)
def _raise_on_response_error(self, resp):
try:
kafka.common.check_error(resp)
except (UnknownTopicOrPartitionError, NotLeaderForPartitionError):
self.reset_topic_metadata(resp.topic)
raise
#################
# Public API #
#################
[docs] def close(self):
for conn in self.conns.values():
conn.close()
[docs] 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 key in c.conns:
c.conns[key] = self.conns[key].copy()
return c
[docs] def reinit(self):
for conn in self.conns.values():
conn.reinit()
[docs] def get_partition_ids_for_topic(self, topic):
if topic not in self.topic_partitions:
return None
return sorted(list(self.topic_partitions[topic]))
[docs] def ensure_topic_exists(self, topic, timeout = 30):
start_time = time.time()
while not self.has_metadata_for_topic(topic):
if time.time() > start_time + timeout:
raise KafkaTimeoutError("Unable to create topic {0}".format(topic))
try:
self.load_metadata_for_topics(topic)
except LeaderNotAvailableError:
pass
except UnknownTopicOrPartitionError:
# Server is not configured to auto-create
# retrying in this case will not help
raise
time.sleep(.5)
[docs] 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
Arguments:
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
Returns:
list of ProduceResponse or callback(ProduceResponse), in the
order of input payloads
"""
encoder = functools.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
[docs] 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 = functools.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
[docs] 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
[docs] def send_offset_commit_request(self, group, payloads=[],
fail_on_error=True, callback=None):
encoder = functools.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
[docs] def send_offset_fetch_request(self, group, payloads=[],
fail_on_error=True, callback=None):
encoder = functools.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