Files
deb-python-kafka/kafka/client.py

357 lines
12 KiB
Python

import copy
from collections import defaultdict
from functools import partial
from itertools import count
import logging
import socket
import time
from kafka.common import ErrorMapping, TopicAndPartition
from kafka.common import ConnectionError, FailedPayloadsException
from kafka.conn import collect_hosts, KafkaConnection
from kafka.protocol import KafkaProtocol
log = logging.getLogger("kafka")
class KafkaClient(object):
CLIENT_ID = "kafka-python"
ID_GEN = count()
def __init__(self, hosts, bufsize=4096, client_id=CLIENT_ID):
# We need one connection to bootstrap
self.bufsize = bufsize
self.client_id = client_id
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 = defaultdict(list) # topic_id -> [0, 1, 2, ...]
self._load_metadata_for_topics()
##################
# 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, self.bufsize)
return self.conns[host_key]
def _get_conn_for_broker(self, broker):
"Get or create a connection to a broker"
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 Exception("Partition does not exist: %s" % str(key))
return self.topics_to_brokers[key]
def _load_metadata_for_topics(self, *topics):
"""
Discover brokers and metadata for a set of topics. This method will
recurse in the event of a retry.
"""
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)
if response is None:
raise Exception("All servers failed to process request")
(brokers, topics) = KafkaProtocol.decode_metadata_response(response)
log.debug("Broker metadata: %s", brokers)
log.debug("Topic metadata: %s", topics)
self.brokers = brokers
self.topics_to_brokers = {}
for topic, partitions in topics.items():
# Clear the list once before we add it. This removes stale entries
# and avoids duplicates
self.topic_partitions.pop(topic, None)
if not partitions:
log.info("Partition is unassigned, delay for 1s and retry")
time.sleep(1)
self._load_metadata_for_topics(topic)
break
for partition, meta in partitions.items():
if meta.leader == -1:
log.info("Partition is unassigned, delay for 1s and retry")
time.sleep(1)
self._load_metadata_for_topics(topic)
else:
topic_part = TopicAndPartition(topic, partition)
self.topics_to_brokers[topic_part] = brokers[meta.leader]
self.topic_partitions[topic].append(partition)
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:
conn = self._get_conn(host, port)
try:
conn.send(requestId, request)
response = conn.recv(requestId)
return response
except Exception, e:
log.warning("Could not send request [%r] to server %s, "
"trying next server: %s" % (request, conn, e))
continue
return None
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)
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)
# Send the request, recv the response
try:
conn.send(requestId, request)
if decoder_fn is None:
continue
response = conn.recv(requestId)
except ConnectionError, e: # ignore BufferUnderflow for now
log.warning("Could not send request [%s] to server %s: %s" % (request, conn, e))
failed_payloads += payloads
self.topics_to_brokers = {} # reset metadata
continue
for response in decoder_fn(response):
acc[(response.topic, response.partition)] = response
if failed_payloads:
raise FailedPayloadsException(failed_payloads)
# Order the accumulated responses by the original key order
return (acc[k] for k in original_keys) if acc else ()
#################
# Public API #
#################
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 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:
# Check for errors
if fail_on_error is True and resp.error != ErrorMapping.NO_ERROR:
raise Exception(
"ProduceRequest for %s failed with errorcode=%d" %
(TopicAndPartition(resp.topic, resp.partition),
resp.error))
# Run the callback
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:
# Check for errors
if fail_on_error is True and resp.error != ErrorMapping.NO_ERROR:
raise Exception(
"FetchRequest for %s failed with errorcode=%d" %
(TopicAndPartition(resp.topic, resp.partition),
resp.error))
# Run the callback
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 and resp.error != ErrorMapping.NO_ERROR:
raise Exception("OffsetRequest failed with errorcode=%s",
resp.error)
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 and resp.error != ErrorMapping.NO_ERROR:
raise Exception("OffsetCommitRequest failed with "
"errorcode=%s", resp.error)
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 and resp.error != ErrorMapping.NO_ERROR:
raise Exception("OffsetCommitRequest failed with errorcode=%s",
resp.error)
if callback is not None:
out.append(callback(resp))
else:
out.append(resp)
return out