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|
import base64
from collections import namedtuple, defaultdict
from functools import partial
from itertools import count, cycle
import logging
from operator import attrgetter
import socket
import struct
import time
import zlib
from .codec import gzip_encode, gzip_decode
from .codec import snappy_encode, snappy_decode
from .util import read_short_string, read_int_string
from .util import relative_unpack
from .util import write_short_string, write_int_string
from .util import group_by_topic_and_partition
from .util import BufferUnderflowError, ChecksumError
log = logging.getLogger("kafka")
###############
# Structs #
###############
# Request payloads
ProduceRequest = namedtuple("ProduceRequest", ["topic", "partition", "messages"])
FetchRequest = namedtuple("FetchRequest", ["topic", "partition", "offset", "max_bytes"])
OffsetRequest = namedtuple("OffsetRequest", ["topic", "partition", "time", "max_offsets"])
OffsetCommitRequest = namedtuple("OffsetCommitRequest", ["topic", "partition", "offset", "metadata"])
OffsetFetchRequest = namedtuple("OffsetFetchRequest", ["topic", "partition"])
# Response payloads
ProduceResponse = namedtuple("ProduceResponse", ["topic", "partition", "error", "offset"])
FetchResponse = namedtuple("FetchResponse", ["topic", "partition", "error", "highwaterMark", "messages"])
OffsetResponse = namedtuple("OffsetResponse", ["topic", "partition", "error", "offsets"])
OffsetCommitResponse = namedtuple("OffsetCommitResponse", ["topic", "partition", "error"])
OffsetFetchResponse = namedtuple("OffsetFetchResponse", ["topic", "partition", "offset", "metadata", "error"])
BrokerMetadata = namedtuple("BrokerMetadata", ["nodeId", "host", "port"])
PartitionMetadata = namedtuple("PartitionMetadata", ["topic", "partition", "leader", "replicas", "isr"])
# Other useful structs
OffsetAndMessage = namedtuple("OffsetAndMessage", ["offset", "message"])
Message = namedtuple("Message", ["magic", "attributes", "key", "value"])
TopicAndPartition = namedtuple("TopicAndPartition", ["topic", "partition"])
class ErrorMapping(object):
# Many of these are not actually used by the client
UNKNOWN = -1
NO_ERROR = 0
OFFSET_OUT_OF_RANGE = 1
INVALID_MESSAGE = 2
UNKNOWN_TOPIC_OR_PARTITON = 3
INVALID_FETCH_SIZE = 4
LEADER_NOT_AVAILABLE = 5
NOT_LEADER_FOR_PARTITION = 6
REQUEST_TIMED_OUT = 7
BROKER_NOT_AVAILABLE = 8
REPLICA_NOT_AVAILABLE = 9
MESSAGE_SIZE_TO_LARGE = 10
STALE_CONTROLLER_EPOCH = 11
OFFSET_METADATA_TOO_LARGE = 12
class KafkaProtocol(object):
"""
Class to encapsulate all of the protocol encoding/decoding. This class does not
have any state associated with it, it is purely for organization.
"""
PRODUCE_KEY = 0
FETCH_KEY = 1
OFFSET_KEY = 2
METADATA_KEY = 3
OFFSET_COMMIT_KEY = 6
OFFSET_FETCH_KEY = 7
ATTRIBUTE_CODEC_MASK = 0x03
CODEC_NONE = 0x00
CODEC_GZIP = 0x01
CODEC_SNAPPY = 0x02
###################
# Private API #
###################
@classmethod
def _encode_message_header(cls, client_id, correlation_id, request_key):
"""
Encode the common request envelope
"""
return struct.pack('>hhih%ds' % len(client_id),
request_key, # ApiKey
0, # ApiVersion
correlation_id, # CorrelationId
len(client_id), #
client_id) # ClientId
@classmethod
def _encode_message_set(cls, messages):
"""
Encode a MessageSet. Unlike other arrays in the protocol, MessageSets are
not length-prefixed
Format
======
MessageSet => [Offset MessageSize Message]
Offset => int64
MessageSize => int32
"""
message_set = ""
for message in messages:
encoded_message = KafkaProtocol._encode_message(message)
message_set += struct.pack('>qi%ds' % len(encoded_message), 0, len(encoded_message), encoded_message)
return message_set
@classmethod
def _encode_message(cls, message):
"""
Encode a single message.
The magic number of a message is a format version number. The only supported
magic number right now is zero
Format
======
Message => Crc MagicByte Attributes Key Value
Crc => int32
MagicByte => int8
Attributes => int8
Key => bytes
Value => bytes
"""
if message.magic == 0:
msg = struct.pack('>BB', message.magic, message.attributes)
msg += write_int_string(message.key)
msg += write_int_string(message.value)
crc = zlib.crc32(msg)
msg = struct.pack('>i%ds' % len(msg), crc, msg)
else:
raise Exception("Unexpected magic number: %d" % message.magic)
return msg
@classmethod
def _decode_message_set_iter(cls, data):
"""
Iteratively decode a MessageSet
Reads repeated elements of (offset, message), calling decode_message to decode a
single message. Since compressed messages contain futher MessageSets, these two methods
have been decoupled so that they may recurse easily.
"""
cur = 0
while cur < len(data):
try:
((offset, ), cur) = relative_unpack('>q', data, cur)
(msg, cur) = read_int_string(data, cur)
for (offset, message) in KafkaProtocol._decode_message(msg, offset):
yield OffsetAndMessage(offset, message)
except BufferUnderflowError: # If we get a partial read of a message, stop
raise StopIteration()
@classmethod
def _decode_message(cls, data, offset):
"""
Decode a single Message
The only caller of this method is decode_message_set_iter. They are decoupled to
support nested messages (compressed MessageSets). The offset is actually read from
decode_message_set_iter (it is part of the MessageSet payload).
"""
((crc, magic, att), cur) = relative_unpack('>iBB', data, 0)
if crc != zlib.crc32(data[4:]):
raise ChecksumError("Message checksum failed")
(key, cur) = read_int_string(data, cur)
(value, cur) = read_int_string(data, cur)
if att & KafkaProtocol.ATTRIBUTE_CODEC_MASK == KafkaProtocol.CODEC_NONE:
yield (offset, Message(magic, att, key, value))
elif att & KafkaProtocol.ATTRIBUTE_CODEC_MASK == KafkaProtocol.CODEC_GZIP:
gz = gzip_decode(value)
for (offset, message) in KafkaProtocol._decode_message_set_iter(gz):
yield (offset, message)
elif att & KafkaProtocol.ATTRIBUTE_CODEC_MASK == KafkaProtocol.CODEC_SNAPPY:
snp = snappy_decode(value)
for (offset, message) in KafkaProtocol._decode_message_set_iter(snp):
yield (offset, message)
##################
# Public API #
##################
@classmethod
def create_message(cls, payload, key=None):
"""
Construct a Message
Params
======
payload: bytes, the payload to send to Kafka
key: bytes, a key used for partition routing (optional)
"""
return Message(0, 0, key, payload)
@classmethod
def create_gzip_message(cls, payloads, key=None):
"""
Construct a Gzipped Message containing multiple Messages
The given payloads will be encoded, compressed, and sent as a single atomic
message to Kafka.
Params
======
payloads: list(bytes), a list of payload to send be sent to Kafka
key: bytes, a key used for partition routing (optional)
"""
message_set = KafkaProtocol._encode_message_set(
[KafkaProtocol.create_message(payload) for payload in payloads])
gzipped = gzip_encode(message_set)
return Message(0, 0x00 | (KafkaProtocol.ATTRIBUTE_CODEC_MASK & KafkaProtocol.CODEC_GZIP), key, gzipped)
@classmethod
def create_snappy_message(cls, payloads, key=None):
"""
Construct a Snappy Message containing multiple Messages
The given payloads will be encoded, compressed, and sent as a single atomic
message to Kafka.
Params
======
payloads: list(bytes), a list of payload to send be sent to Kafka
key: bytes, a key used for partition routing (optional)
"""
message_set = KafkaProtocol._encode_message_set(
[KafkaProtocol.create_message(payload) for payload in payloads])
snapped = snappy_encode(message_set)
return Message(0, 0x00 | (KafkaProtocol.ATTRIBUTE_CODEC_MASK & KafkaProtocol.CODEC_SNAPPY), key, snapped)
@classmethod
def encode_produce_request(cls, client_id, correlation_id, payloads=[], acks=1, timeout=1000):
"""
Encode some ProduceRequest structs
Params
======
client_id: string
correlation_id: string
payloads: list of ProduceRequest
acks: How "acky" you want the request to be
0: immediate response
1: written to disk by the leader
2+: waits for this many number of replicas to sync
-1: waits for all replicas to be in sync
timeout: Maximum time the server will wait for acks from replicas. This is _not_ a socket timeout
"""
grouped_payloads = group_by_topic_and_partition(payloads)
message = cls._encode_message_header(client_id, correlation_id, KafkaProtocol.PRODUCE_KEY)
message += struct.pack('>hii', acks, timeout, len(grouped_payloads))
for topic, topic_payloads in grouped_payloads.items():
message += struct.pack('>h%dsi' % len(topic), len(topic), topic, len(topic_payloads))
for partition, payload in topic_payloads.items():
message_set = KafkaProtocol._encode_message_set(payload.messages)
message += struct.pack('>ii%ds' % len(message_set), partition, len(message_set), message_set)
return struct.pack('>i%ds' % len(message), len(message), message)
@classmethod
def decode_produce_response(cls, data):
"""
Decode bytes to a ProduceResponse
Params
======
data: bytes to decode
"""
((correlation_id, num_topics), cur) = relative_unpack('>ii', data, 0)
for i in range(num_topics):
((strlen,), cur) = relative_unpack('>h', data, cur)
topic = data[cur:cur+strlen]
cur += strlen
((num_partitions,), cur) = relative_unpack('>i', data, cur)
for i in range(num_partitions):
((partition, error, offset), cur) = relative_unpack('>ihq', data, cur)
yield ProduceResponse(topic, partition, error, offset)
@classmethod
def encode_fetch_request(cls, client_id, correlation_id, payloads=[], max_wait_time=100, min_bytes=4096):
"""
Encodes some FetchRequest structs
Params
======
client_id: string
correlation_id: string
payloads: list of FetchRequest
max_wait_time: int, how long to block waiting on min_bytes of data
min_bytes: int, the minimum number of bytes to accumulate before returning the response
"""
grouped_payloads = group_by_topic_and_partition(payloads)
message = cls._encode_message_header(client_id, correlation_id, KafkaProtocol.FETCH_KEY)
message += struct.pack('>iiii', -1, max_wait_time, min_bytes, len(grouped_payloads)) # -1 is the replica id
for topic, topic_payloads in grouped_payloads.items():
message += write_short_string(topic)
message += struct.pack('>i', len(topic_payloads))
for partition, payload in topic_payloads.items():
message += struct.pack('>iqi', partition, payload.offset, payload.max_bytes)
return struct.pack('>i%ds' % len(message), len(message), message)
@classmethod
def decode_fetch_response_iter(cls, data):
"""
Decode bytes to a FetchResponse
Params
======
data: bytes to decode
"""
((correlation_id, num_topics), cur) = relative_unpack('>ii', data, 0)
for i in range(num_topics):
(topic, cur) = read_short_string(data, cur)
((num_partitions,), cur) = relative_unpack('>i', data, cur)
for i in range(num_partitions):
((partition, error, highwater_mark_offset), cur) = relative_unpack('>ihq', data, cur)
(message_set, cur) = read_int_string(data, cur)
yield FetchResponse(topic, partition, error, highwater_mark_offset,
KafkaProtocol._decode_message_set_iter(message_set))
@classmethod
def encode_offset_request(cls, client_id, correlation_id, payloads=[]):
grouped_payloads = group_by_topic_and_partition(payloads)
message = cls._encode_message_header(client_id, correlation_id, KafkaProtocol.OFFSET_KEY)
message += struct.pack('>ii', -1, len(grouped_payloads)) # -1 is the replica id
for topic, topic_payloads in grouped_payloads.items():
message += write_short_string(topic)
message += struct.pack('>i', len(topic_payloads))
for partition, payload in topic_payloads.items():
message += struct.pack('>iqi', partition, payload.time, payload.max_offsets)
return struct.pack('>i%ds' % len(message), len(message), message)
@classmethod
def decode_offset_response(cls, data):
"""
Decode bytes to an OffsetResponse
Params
======
data: bytes to decode
"""
((correlation_id, num_topics), cur) = relative_unpack('>ii', data, 0)
for i in range(num_topics):
(topic, cur) = read_short_string(data, cur)
((num_partitions,), cur) = relative_unpack('>i', data, cur)
for i in range(num_partitions):
((partition, error, num_offsets,), cur) = relative_unpack('>ihi', data, cur)
offsets = []
for j in range(num_offsets):
((offset,), cur) = relative_unpack('>q', data, cur)
offsets.append(offset)
yield OffsetResponse(topic, partition, error, tuple(offsets))
@classmethod
def encode_metadata_request(cls, client_id, correlation_id, topics=[]):
"""
Encode a MetadataRequest
Params
======
client_id: string
correlation_id: string
topics: list of strings
"""
message = cls._encode_message_header(client_id, correlation_id, KafkaProtocol.METADATA_KEY)
message += struct.pack('>i', len(topics))
for topic in topics:
message += struct.pack('>h%ds' % len(topic), len(topic), topic)
return write_int_string(message)
@classmethod
def decode_metadata_response(cls, data):
"""
Decode bytes to a MetadataResponse
Params
======
data: bytes to decode
"""
((correlation_id, numBrokers), cur) = relative_unpack('>ii', data, 0)
# Broker info
brokers = {}
for i in range(numBrokers):
((nodeId, ), cur) = relative_unpack('>i', data, cur)
(host, cur) = read_short_string(data, cur)
((port,), cur) = relative_unpack('>i', data, cur)
brokers[nodeId] = BrokerMetadata(nodeId, host, port)
# Topic info
((num_topics,), cur) = relative_unpack('>i', data, cur)
topicMetadata = {}
for i in range(num_topics):
((topicError,), cur) = relative_unpack('>h', data, cur)
(topicName, cur) = read_short_string(data, cur)
((num_partitions,), cur) = relative_unpack('>i', data, cur)
partitionMetadata = {}
for j in range(num_partitions):
((partitionErrorCode, partition, leader, numReplicas), cur) = relative_unpack('>hiii', data, cur)
(replicas, cur) = relative_unpack('>%di' % numReplicas, data, cur)
((numIsr,), cur) = relative_unpack('>i', data, cur)
(isr, cur) = relative_unpack('>%di' % numIsr, data, cur)
partitionMetadata[partition] = PartitionMetadata(topicName, partition, leader, replicas, isr)
topicMetadata[topicName] = partitionMetadata
return (brokers, topicMetadata)
@classmethod
def encode_offset_commit_request(cls, client_id, correlation_id, group, payloads):
"""
Encode some OffsetCommitRequest structs
Params
======
client_id: string
correlation_id: string
group: string, the consumer group you are committing offsets for
payloads: list of OffsetCommitRequest
"""
grouped_payloads= group_by_topic_and_partition(payloads)
message = cls._encode_message_header(client_id, correlation_id, KafkaProtocol.OFFSET_COMMIT_KEY)
message += write_short_string(group)
message += struct.pack('>i', len(grouped_payloads))
for topic, topic_payloads in grouped_payloads.items():
message += write_short_string(topic)
message += struct.pack('>i', len(topic_payloads))
for partition, payload in topic_payloads.items():
message += struct.pack('>iq', partition, payload.offset)
message += write_short_string(payload.metadata)
return struct.pack('>i%ds' % len(message), len(message), message)
@classmethod
def decode_offset_commit_response(cls, data):
"""
Decode bytes to an OffsetCommitResponse
Params
======
data: bytes to decode
"""
data = data[2:] # TODO remove me when versionId is removed
((correlation_id,), cur) = relative_unpack('>i', data, 0)
(client_id, cur) = read_short_string(data, cur)
((num_topics,), cur) = relative_unpack('>i', data, cur)
for i in xrange(num_topics):
(topic, cur) = read_short_string(data, cur)
((num_partitions,), cur) = relative_unpack('>i', data, cur)
for i in xrange(num_partitions):
((partition, error), cur) = relative_unpack('>ih', data, cur)
yield OffsetCommitResponse(topic, partition, error)
@classmethod
def encode_offset_fetch_request(cls, client_id, correlation_id, group, payloads):
"""
Encode some OffsetFetchRequest structs
Params
======
client_id: string
correlation_id: string
group: string, the consumer group you are fetching offsets for
payloads: list of OffsetFetchRequest
"""
grouped_payloads = group_by_topic_and_partition(payloads)
message = cls._encode_message_header(client_id, correlation_id, KafkaProtocol.OFFSET_FETCH_KEY)
message += write_short_string(group)
message += struct.pack('>i', len(grouped_payloads))
for topic, topic_payloads in grouped_payloads.items():
message += write_short_string(topic)
message += struct.pack('>i', len(topic_payloads))
for partition, payload in topic_payloads.items():
message += struct.pack('>i', partition)
return struct.pack('>i%ds' % len(message), len(message), message)
@classmethod
def decode_offset_fetch_response(cls, data):
"""
Decode bytes to an OffsetFetchResponse
Params
======
data: bytes to decode
"""
data = data[2:] # TODO remove me when versionId is removed
((correlation_id,), cur) = relative_unpack('>i', data, 0)
(client_id, cur) = read_short_string(data, cur)
((num_topics,), cur) = relative_unpack('>i', data, cur)
for i in range(num_topics):
(topic, cur) = read_short_string(data, cur)
((num_partitions,), cur) = relative_unpack('>i', data, cur)
for i in range(num_partitions):
((partition, offset), cur) = relative_unpack('>iq', data, cur)
(metadata, cur) = read_short_string(data, cur)
((error,), cur) = relative_unpack('>h', data, cur)
yield OffsetFetchResponse(topic, partition, offset, metadata, error)
class KafkaConnection(object):
"""
A socket connection to a single Kafka broker
This class is _not_ thread safe. Each call to `send` must be followed
by a call to `recv` in order to get the correct response. Eventually,
we can do something in here to facilitate multiplexed requests/responses
since the Kafka API includes a correlation id.
"""
def __init__(self, host, port, bufsize=4096):
self.host = host
self.port = port
self.bufsize = bufsize
self._sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self._sock.connect((host, port))
self._sock.settimeout(10)
def __str__(self):
return "<KafkaConnection host=%s port=%d>" % (self.host, self.port)
###################
# Private API #
###################
def _consume_response(self):
"""
Fully consumer the response iterator
"""
data = ""
for chunk in self._consume_response_iter():
data += chunk
return data
def _consume_response_iter(self):
"""
This method handles the response header and error messages. It
then returns an iterator for the chunks of the response
"""
log.debug("Handling response from Kafka")
# Read the size off of the header
resp = self._sock.recv(4)
if resp == "":
raise Exception("Got no response from Kafka")
(size,) = struct.unpack('>i', resp)
messageSize = size - 4
log.debug("About to read %d bytes from Kafka", messageSize)
# Read the remainder of the response
total = 0
while total < messageSize:
resp = self._sock.recv(self.bufsize)
log.debug("Read %d bytes from Kafka", len(resp))
if resp == "":
raise BufferUnderflowError("Not enough data to read this response")
total += len(resp)
yield resp
##################
# Public API #
##################
# TODO multiplex socket communication to allow for multi-threaded clients
def send(self, requestId, payload):
"Send a request to Kafka"
sent = self._sock.sendall(payload)
if sent == 0:
raise RuntimeError("Kafka went away")
self.data = self._consume_response()
def recv(self, requestId):
"Get a response from Kafka"
return self.data
def close(self):
"Close this connection"
self._sock.close()
class KafkaClient(object):
CLIENT_ID = "kafka-python"
ID_GEN = count()
def __init__(self, host, port, bufsize=4096):
# We need one connection to bootstrap
self.bufsize = bufsize
self.conns = { # (host, port) -> KafkaConnection
(host, port): KafkaConnection(host, port, bufsize)
}
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()
def close(self):
for conn in self.conns.values():
conn.close()
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, self.bufsize)
return self.conns[(broker.host, broker.port)]
def next_id(self):
"Generate a new correlation id"
return KafkaClient.ID_GEN.next()
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.
"""
requestId = self.next_id()
request = KafkaProtocol.encode_metadata_request(KafkaClient.CLIENT_ID, requestId, topics)
response = self.try_send_request(requestId, 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.update(brokers)
self.topics_to_brokers = {}
for topic, partitions in topics.items():
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:
self.topics_to_brokers[TopicAndPartition(topic, partition)] = brokers[meta.leader]
self.topic_partitions[topic].append(partition)
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 send_produce_request(self, payloads=[], 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
"""
# Group the produce requests by which broker they go to
original_keys = []
payloads_by_broker = defaultdict(list)
for payload in payloads:
payloads_by_broker[self.get_leader_for_partition(payload.topic, payload.partition)] += payloads
original_keys.append((payload.topic, payload.partition))
# Accumulate the responses in a dictionary
acc = {}
# 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 = KafkaProtocol.encode_produce_request(KafkaClient.CLIENT_ID, requestId, payloads)
# Send the request
conn.send(requestId, request)
response = conn.recv(requestId)
for produce_response in KafkaProtocol.decode_produce_response(response):
# Check for errors
if fail_on_error == True and produce_response.error != ErrorMapping.NO_ERROR:
raise Exception("ProduceRequest for %s failed with errorcode=%d" %
(TopicAndPartition(produce_response.topic, produce_response.partition), produce_response.error))
# Run the callback
if callback is not None:
acc[(produce_response.topic, produce_response.partition)] = callback(produce_response)
else:
acc[(produce_response.topic, produce_response.partition)] = produce_response
# Order the accumulated responses by the original key order
return (acc[k] for k in original_keys)
def send_fetch_request(self, payloads=[], fail_on_error=True, callback=None):
"""
Encode and send a FetchRequest
Payloads are grouped by topic and partition so they can be pipelined to the same
brokers.
"""
# Group the produce requests by which broker they go to
original_keys = []
payloads_by_broker = defaultdict(list)
for payload in payloads:
payloads_by_broker[self.get_leader_for_partition(payload.topic, payload.partition)].append(payload)
original_keys.append((payload.topic, payload.partition))
# Accumulate the responses in a dictionary, keyed by topic+partition
acc = {}
# 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 = KafkaProtocol.encode_fetch_request(KafkaClient.CLIENT_ID, requestId, payloads)
# Send the request
conn.send(requestId, request)
response = conn.recv(requestId)
for fetch_response in KafkaProtocol.decode_fetch_response_iter(response):
# Check for errors
if fail_on_error == True and fetch_response.error != ErrorMapping.NO_ERROR:
raise Exception("FetchRequest %s failed with errorcode=%d" %
(TopicAndPartition(fetch_response.topic, fetch_response.partition), fetch_response.error))
# Run the callback
if callback is not None:
acc[(fetch_response.topic, fetch_response.partition)] = callback(fetch_response)
else:
acc[(fetch_response.topic, fetch_response.partition)] = fetch_response
# Order the accumulated responses by the original key order
return (acc[k] for k in original_keys)
def try_send_request(self, requestId, request):
"""
Attempt to send a broker-agnostic request to one of the available brokers.
Keep trying until you succeed.
"""
for conn in self.conns.values():
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_offset_request(self, payloads=[], fail_on_error=True, callback=None):
requestId = self.next_id()
request = KafkaProtocol.encode_offset_request(KafkaClient.CLIENT_ID, requestId, payloads)
response = self.try_send_request(requestId, request)
if response is None:
if fail_on_error is True:
raise Exception("All servers failed to process request")
else:
return None
out = []
for offset_response in KafkaProtocol.decode_offset_response(response):
if fail_on_error == True and offset_response.error != ErrorMapping.NO_ERROR:
raise Exception("OffsetRequest failed with errorcode=%s", offset_response.error)
if callback is not None:
out.append(callback(offset_response))
else:
out.append(offset_response)
return out
def send_offset_commit_request(self, group, payloads=[], fail_on_error=True, callback=None):
requestId = self.next_id()
request = KafkaProtocol.encode_offset_commit_request(KafkaClient.CLIENT_ID, requestId, group, payloads)
response = self.try_send_request(requestId, request)
if response is None:
if fail_on_error is True:
raise Exception("All servers failed to process request")
else:
return None
out = []
for offset_commit_response in KafkaProtocol.decode_offset_commit_response(response):
log.debug(offset_commit_response)
if fail_on_error == True and offset_commit_response.error != ErrorMapping.NO_ERROR:
raise Exception("OffsetCommitRequest failed with errorcode=%s", offset_commit_response.error)
if callback is not None:
out.append(callback(offset_commit_response))
else:
out.append(offset_commit_response)
return out
def send_offset_fetch_request(self, group, payloads=[], fail_on_error=True, callback=None):
requestId = self.next_id()
request = KafkaProtocol.encode_offset_fetch_request(KafkaClient.CLIENT_ID, requestId, group, payloads)
response = self.try_send_request(requestId, request)
if response is None:
if fail_on_error is True:
raise Exception("All servers failed to process request")
else:
return None
out = []
for offset_fetch_response in KafkaProtocol.decode_offset_fetch_response(response):
if fail_on_error == True and offset_fetch_response.error != ErrorMapping.NO_ERROR:
raise Exception("OffsetFetchRequest for topic=%s, partition=%d failed with errorcode=%s" % (
offset_fetch_response.topic, offset_fetch_response.partition, offset_fetch_response.error))
if callback is not None:
out.append(callback(offset_fetch_response))
else:
out.append(offset_fetch_response)
return out
class SimpleProducer(object):
"""
A simple, round-robbin producer. Each message goes to exactly one partition
"""
def __init__(self, client, topic):
self.client = client
self.topic = topic
self.client.load_metadata_for_topics(topic)
self.next_partition = cycle(self.client.topic_partitions[topic])
def send_message(self, msg):
req = ProduceRequest(self.topic, self.next_partition.next(),
messages=[KafkaProtocol.create_message(msg)])
resp = self.client.send_produce_request([req]).next()
class SimpleConsumer(object):
"""
A simple consumer implementation that consumes all partitions for a topic
"""
def __init__(self, client, group, topic):
self.client = client
self.topic = topic
self.group = group
self.client.load_metadata_for_topics(topic)
self.offsets = {}
def get_or_init_offset_callback(resp):
if resp.error == ErrorMapping.NO_ERROR:
return resp.offset
elif resp.error == ErrorMapping.UNKNOWN_TOPIC_OR_PARTITON:
return 0
else:
raise Exception("OffsetFetchRequest for topic=%s, partition=%d failed with errorcode=%s" % (
resp.topic, resp.partition, resp.error))
for partition in self.client.topic_partitions[topic]:
req = OffsetFetchRequest(topic, partition)
(offset,) = self.client.send_offset_fetch_request(group, [req],
callback=get_or_init_offset_callback, fail_on_error=False)
self.offsets[partition] = offset
def __iter__(self):
iters = {}
for partition, offset in self.offsets.items():
iters[partition] = self.__iter_partition__(partition, offset)
while True:
for it in iters.values():
yield it.next()
def __iter_partition__(self, partition, offset):
while True:
req = FetchRequest(self.topic, partition, offset, 1024)
(resp,) = self.client.send_fetch_request([req])
assert resp.topic == self.topic
assert resp.partition == partition
next_offset = None
for message in resp.messages:
next_offset = message.offset
yield message
if next_offset is None:
raise StopIteration("No more messages")
else:
offset = next_offset + 1
# Commit offset here?
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