614 lines
22 KiB
Python
614 lines
22 KiB
Python
from collections import defaultdict
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from itertools import izip_longest, repeat
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import logging
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import time
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from threading import Lock
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from multiprocessing import Process, Queue, Event, Value
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from Queue import Empty
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from kafka.common import (
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ErrorMapping, FetchRequest,
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OffsetRequest, OffsetCommitRequest,
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ConsumerFetchSizeTooSmall, ConsumerNoMoreData
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)
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from kafka.util import ReentrantTimer
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log = logging.getLogger("kafka")
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AUTO_COMMIT_MSG_COUNT = 100
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AUTO_COMMIT_INTERVAL = 5000
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FETCH_DEFAULT_BLOCK_TIMEOUT = 1
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FETCH_MAX_WAIT_TIME = 100
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FETCH_MIN_BYTES = 4096
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class FetchContext(object):
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"""
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Class for managing the state of a consumer during fetch
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"""
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def __init__(self, consumer, block, timeout):
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self.consumer = consumer
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self.block = block
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if block and not timeout:
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timeout = FETCH_DEFAULT_BLOCK_TIMEOUT
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self.timeout = timeout * 1000
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def __enter__(self):
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"""Set fetch values based on blocking status"""
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if self.block:
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self.consumer.fetch_max_wait_time = self.timeout
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self.consumer.fetch_min_bytes = 1
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else:
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self.consumer.fetch_min_bytes = 0
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def __exit__(self, type, value, traceback):
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"""Reset values to default"""
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self.consumer.fetch_max_wait_time = FETCH_MAX_WAIT_TIME
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self.consumer.fetch_min_bytes = FETCH_MIN_BYTES
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class Consumer(object):
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"""
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Base class to be used by other consumers. Not to be used directly
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This base class provides logic for
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* initialization and fetching metadata of partitions
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* Auto-commit logic
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* APIs for fetching pending message count
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"""
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def __init__(self, client, group, topic, partitions=None, auto_commit=True,
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auto_commit_every_n=AUTO_COMMIT_MSG_COUNT,
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auto_commit_every_t=AUTO_COMMIT_INTERVAL):
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self.client = client
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self.topic = topic
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self.group = group
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self.client._load_metadata_for_topics(topic)
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self.offsets = {}
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if not partitions:
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partitions = self.client.topic_partitions[topic]
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# Variables for handling offset commits
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self.commit_lock = Lock()
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self.commit_timer = None
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self.count_since_commit = 0
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self.auto_commit = auto_commit
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self.auto_commit_every_n = auto_commit_every_n
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self.auto_commit_every_t = auto_commit_every_t
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# Set up the auto-commit timer
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if auto_commit is True and auto_commit_every_t is not None:
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self.commit_timer = ReentrantTimer(auto_commit_every_t,
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self.commit)
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self.commit_timer.start()
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def get_or_init_offset_callback(resp):
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if resp.error == ErrorMapping.NO_ERROR:
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return resp.offset
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elif resp.error == ErrorMapping.UNKNOWN_TOPIC_OR_PARTITON:
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return 0
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else:
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raise Exception("OffsetFetchRequest for topic=%s, "
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"partition=%d failed with errorcode=%s" % (
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resp.topic, resp.partition, resp.error))
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# Uncomment for 0.8.1
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#
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#for partition in partitions:
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# req = OffsetFetchRequest(topic, partition)
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# (offset,) = self.client.send_offset_fetch_request(group, [req],
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# callback=get_or_init_offset_callback,
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# fail_on_error=False)
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# self.offsets[partition] = offset
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for partition in partitions:
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self.offsets[partition] = 0
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def commit(self, partitions=None):
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"""
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Commit offsets for this consumer
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partitions: list of partitions to commit, default is to commit
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all of them
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"""
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# short circuit if nothing happened. This check is kept outside
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# to prevent un-necessarily acquiring a lock for checking the state
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if self.count_since_commit == 0:
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return
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with self.commit_lock:
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# Do this check again, just in case the state has changed
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# during the lock acquiring timeout
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if self.count_since_commit == 0:
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return
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reqs = []
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if not partitions: # commit all partitions
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partitions = self.offsets.keys()
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for partition in partitions:
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offset = self.offsets[partition]
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log.debug("Commit offset %d in SimpleConsumer: "
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"group=%s, topic=%s, partition=%s" %
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(offset, self.group, self.topic, partition))
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reqs.append(OffsetCommitRequest(self.topic, partition,
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offset, None))
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resps = self.client.send_offset_commit_request(self.group, reqs)
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for resp in resps:
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assert resp.error == 0
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self.count_since_commit = 0
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def _auto_commit(self):
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"""
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Check if we have to commit based on number of messages and commit
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"""
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# Check if we are supposed to do an auto-commit
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if not self.auto_commit or self.auto_commit_every_n is None:
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return
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if self.count_since_commit > self.auto_commit_every_n:
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self.commit()
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def stop(self):
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if self.commit_timer is not None:
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self.commit_timer.stop()
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self.commit()
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def pending(self, partitions=None):
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"""
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Gets the pending message count
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partitions: list of partitions to check for, default is to check all
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"""
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if not partitions:
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partitions = self.offsets.keys()
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total = 0
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reqs = []
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for partition in partitions:
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reqs.append(OffsetRequest(self.topic, partition, -1, 1))
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resps = self.client.send_offset_request(reqs)
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for resp in resps:
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partition = resp.partition
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pending = resp.offsets[0]
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offset = self.offsets[partition]
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total += pending - offset - (1 if offset > 0 else 0)
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return total
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class SimpleConsumer(Consumer):
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"""
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A simple consumer implementation that consumes all/specified partitions
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for a topic
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client: a connected KafkaClient
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group: a name for this consumer, used for offset storage and must be unique
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topic: the topic to consume
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partitions: An optional list of partitions to consume the data from
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auto_commit: default True. Whether or not to auto commit the offsets
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auto_commit_every_n: default 100. How many messages to consume
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before a commit
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auto_commit_every_t: default 5000. How much time (in milliseconds) to
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wait before commit
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fetch_size_bytes: number of bytes to request in a FetchRequest
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Auto commit details:
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If both auto_commit_every_n and auto_commit_every_t are set, they will
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reset one another when one is triggered. These triggers simply call the
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commit method on this class. A manual call to commit will also reset
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these triggers
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"""
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def __init__(self, client, group, topic, auto_commit=True, partitions=None,
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auto_commit_every_n=AUTO_COMMIT_MSG_COUNT,
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auto_commit_every_t=AUTO_COMMIT_INTERVAL,
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fetch_size_bytes=FETCH_MIN_BYTES):
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self.partition_info = False # Do not return partition info in msgs
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self.fetch_max_wait_time = FETCH_MAX_WAIT_TIME
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self.fetch_min_bytes = fetch_size_bytes
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self.fetch_started = defaultdict(bool) # defaults to false
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super(SimpleConsumer, self).__init__(
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client, group, topic,
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partitions=partitions,
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auto_commit=auto_commit,
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auto_commit_every_n=auto_commit_every_n,
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auto_commit_every_t=auto_commit_every_t)
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def provide_partition_info(self):
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"""
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Indicates that partition info must be returned by the consumer
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"""
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self.partition_info = True
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def seek(self, offset, whence):
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"""
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Alter the current offset in the consumer, similar to fseek
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offset: how much to modify the offset
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whence: where to modify it from
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0 is relative to the earliest available offset (head)
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1 is relative to the current offset
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2 is relative to the latest known offset (tail)
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"""
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if whence == 1: # relative to current position
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for partition, _offset in self.offsets.items():
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self.offsets[partition] = _offset + offset
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elif whence in (0, 2): # relative to beginning or end
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# divide the request offset by number of partitions,
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# distribute the remained evenly
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(delta, rem) = divmod(offset, len(self.offsets))
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deltas = {}
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for partition, r in izip_longest(self.offsets.keys(),
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repeat(1, rem), fillvalue=0):
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deltas[partition] = delta + r
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reqs = []
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for partition in self.offsets.keys():
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if whence == 0:
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reqs.append(OffsetRequest(self.topic, partition, -2, 1))
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elif whence == 2:
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reqs.append(OffsetRequest(self.topic, partition, -1, 1))
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# The API returns back the next available offset
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# For eg: if the current offset is 18, the API will return
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# back 19. So, if we have to seek 5 points before, we will
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# end up going back to 14, instead of 13. Adjust this
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deltas[partition] -= 1
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else:
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pass
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resps = self.client.send_offset_request(reqs)
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for resp in resps:
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self.offsets[resp.partition] = \
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resp.offsets[0] + deltas[resp.partition]
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else:
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raise ValueError("Unexpected value for `whence`, %d" % whence)
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def get_messages(self, count=1, block=True, timeout=0.1):
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"""
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Fetch the specified number of messages
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count: Indicates the maximum number of messages to be fetched
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block: If True, the API will block till some messages are fetched.
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timeout: If None, and block=True, the API will block infinitely.
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If >0, API will block for specified time (in seconds)
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"""
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messages = []
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iterator = self.__iter__()
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# HACK: This splits the timeout between available partitions
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timeout = timeout * 1.0 / len(self.offsets)
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with FetchContext(self, block, timeout):
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while count > 0:
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try:
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messages.append(next(iterator))
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except StopIteration:
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break
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count -= 1
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return messages
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def __iter__(self):
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"""
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Create an iterate per partition. Iterate through them calling next()
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until they are all exhausted.
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"""
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iters = {}
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for partition, offset in self.offsets.items():
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iters[partition] = self.__iter_partition__(partition, offset)
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if len(iters) == 0:
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return
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while True:
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if len(iters) == 0:
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break
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for partition, it in iters.items():
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try:
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if self.partition_info:
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yield (partition, it.next())
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else:
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yield it.next()
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except StopIteration:
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log.debug("Done iterating over partition %s" % partition)
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del iters[partition]
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# skip auto-commit since we didn't yield anything
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continue
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# Count, check and commit messages if necessary
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self.count_since_commit += 1
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self._auto_commit()
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def __iter_partition__(self, partition, offset):
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"""
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Iterate over the messages in a partition. Create a FetchRequest
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to get back a batch of messages, yield them one at a time.
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After a batch is exhausted, start a new batch unless we've reached
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the end of this partition.
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"""
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# The offset that is stored in the consumer is the offset that
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# we have consumed. In subsequent iterations, we are supposed to
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# fetch the next message (that is from the next offset)
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# However, for the 0th message, the offset should be as-is.
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# An OffsetFetchRequest to Kafka gives 0 for a new queue. This is
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# problematic, since 0 is offset of a message which we have not yet
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# consumed.
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if self.fetch_started[partition]:
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offset += 1
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fetch_size = self.fetch_min_bytes
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while True:
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# use MaxBytes = client's bufsize since we're only
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# fetching one topic + partition
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req = FetchRequest(
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self.topic, partition, offset, self.client.bufsize)
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(resp,) = self.client.send_fetch_request(
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[req],
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max_wait_time=self.fetch_max_wait_time,
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min_bytes=fetch_size)
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assert resp.topic == self.topic
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assert resp.partition == partition
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next_offset = None
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try:
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for message in resp.messages:
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next_offset = message.offset
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# update the offset before the message is yielded. This
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# is so that the consumer state is not lost in certain
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# cases.
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#
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# For eg: the message is yielded and consumed by the
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# caller, but the caller does not come back into the
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# generator again. The message will be consumed but the
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# status will not be updated in the consumer
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self.fetch_started[partition] = True
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self.offsets[partition] = message.offset
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yield message
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except ConsumerFetchSizeTooSmall, e:
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fetch_size *= 1.5
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log.warn(
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"Fetch size too small, increasing to %d (1.5x) and retry",
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fetch_size)
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continue
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except ConsumerNoMoreData, e:
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log.debug("Iteration was ended by %r", e)
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if next_offset is None:
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break
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else:
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offset = next_offset + 1
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class MultiProcessConsumer(Consumer):
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"""
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A consumer implementation that consumes partitions for a topic in
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parallel using multiple processes
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client: a connected KafkaClient
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group: a name for this consumer, used for offset storage and must be unique
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topic: the topic to consume
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auto_commit: default True. Whether or not to auto commit the offsets
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auto_commit_every_n: default 100. How many messages to consume
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before a commit
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auto_commit_every_t: default 5000. How much time (in milliseconds) to
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wait before commit
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num_procs: Number of processes to start for consuming messages.
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The available partitions will be divided among these processes
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partitions_per_proc: Number of partitions to be allocated per process
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(overrides num_procs)
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Auto commit details:
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If both auto_commit_every_n and auto_commit_every_t are set, they will
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reset one another when one is triggered. These triggers simply call the
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commit method on this class. A manual call to commit will also reset
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these triggers
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"""
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def __init__(self, client, group, topic, auto_commit=True,
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auto_commit_every_n=AUTO_COMMIT_MSG_COUNT,
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auto_commit_every_t=AUTO_COMMIT_INTERVAL,
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num_procs=1, partitions_per_proc=0):
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# Initiate the base consumer class
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super(MultiProcessConsumer, self).__init__(
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client, group, topic,
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partitions=None,
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auto_commit=auto_commit,
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auto_commit_every_n=auto_commit_every_n,
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auto_commit_every_t=auto_commit_every_t)
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# Variables for managing and controlling the data flow from
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# consumer child process to master
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self.queue = Queue(1024) # Child consumers dump messages into this
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self.start = Event() # Indicates the consumers to start fetch
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self.exit = Event() # Requests the consumers to shutdown
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self.pause = Event() # Requests the consumers to pause fetch
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self.size = Value('i', 0) # Indicator of number of messages to fetch
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partitions = self.offsets.keys()
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# If unspecified, start one consumer per partition
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# The logic below ensures that
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# * we do not cross the num_procs limit
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# * we have an even distribution of partitions among processes
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if not partitions_per_proc:
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partitions_per_proc = round(len(partitions) * 1.0 / num_procs)
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if partitions_per_proc < num_procs * 0.5:
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partitions_per_proc += 1
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# The final set of chunks
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chunker = lambda *x: [] + list(x)
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chunks = map(chunker, *[iter(partitions)] * int(partitions_per_proc))
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self.procs = []
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for chunk in chunks:
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chunk = filter(lambda x: x is not None, chunk)
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proc = Process(target=self._consume, args=(chunk,))
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proc.daemon = True
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proc.start()
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self.procs.append(proc)
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def _consume(self, partitions):
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"""
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A child process worker which consumes messages based on the
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notifications given by the controller process
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"""
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# Make the child processes open separate socket connections
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self.client.reinit()
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# We will start consumers without auto-commit. Auto-commit will be
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# done by the master controller process.
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consumer = SimpleConsumer(self.client, self.group, self.topic,
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partitions=partitions,
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auto_commit=False,
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auto_commit_every_n=None,
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auto_commit_every_t=None)
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# Ensure that the consumer provides the partition information
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consumer.provide_partition_info()
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while True:
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# Wait till the controller indicates us to start consumption
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self.start.wait()
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# If we are asked to quit, do so
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if self.exit.is_set():
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break
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# Consume messages and add them to the queue. If the controller
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# indicates a specific number of messages, follow that advice
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count = 0
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for partition, message in consumer:
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self.queue.put((partition, message))
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count += 1
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# We have reached the required size. The controller might have
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# more than what he needs. Wait for a while.
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# Without this logic, it is possible that we run into a big
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# loop consuming all available messages before the controller
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# can reset the 'start' event
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if count == self.size.value:
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self.pause.wait()
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break
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# In case we did not receive any message, give up the CPU for
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# a while before we try again
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if count == 0:
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time.sleep(0.1)
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consumer.stop()
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def stop(self):
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# Set exit and start off all waiting consumers
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self.exit.set()
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self.pause.set()
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self.start.set()
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for proc in self.procs:
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proc.join()
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proc.terminate()
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super(MultiProcessConsumer, self).stop()
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def __iter__(self):
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"""
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Iterator to consume the messages available on this consumer
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"""
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# Trigger the consumer procs to start off.
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# We will iterate till there are no more messages available
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|
self.size.value = 0
|
|
self.pause.set()
|
|
|
|
while True:
|
|
self.start.set()
|
|
try:
|
|
# We will block for a small while so that the consumers get
|
|
# a chance to run and put some messages in the queue
|
|
# TODO: This is a hack and will make the consumer block for
|
|
# at least one second. Need to find a better way of doing this
|
|
partition, message = self.queue.get(block=True, timeout=1)
|
|
except Empty:
|
|
break
|
|
|
|
# Count, check and commit messages if necessary
|
|
self.offsets[partition] = message.offset
|
|
self.start.clear()
|
|
yield message
|
|
|
|
self.count_since_commit += 1
|
|
self._auto_commit()
|
|
|
|
self.start.clear()
|
|
|
|
def get_messages(self, count=1, block=True, timeout=10):
|
|
"""
|
|
Fetch the specified number of messages
|
|
|
|
count: Indicates the maximum number of messages to be fetched
|
|
block: If True, the API will block till some messages are fetched.
|
|
timeout: If None, and block=True, the API will block infinitely.
|
|
If >0, API will block for specified time (in seconds)
|
|
"""
|
|
messages = []
|
|
|
|
# Give a size hint to the consumers. Each consumer process will fetch
|
|
# a maximum of "count" messages. This will fetch more messages than
|
|
# necessary, but these will not be committed to kafka. Also, the extra
|
|
# messages can be provided in subsequent runs
|
|
self.size.value = count
|
|
self.pause.clear()
|
|
|
|
while count > 0:
|
|
# Trigger consumption only if the queue is empty
|
|
# By doing this, we will ensure that consumers do not
|
|
# go into overdrive and keep consuming thousands of
|
|
# messages when the user might need only a few
|
|
if self.queue.empty():
|
|
self.start.set()
|
|
|
|
try:
|
|
partition, message = self.queue.get(block, timeout)
|
|
except Empty:
|
|
break
|
|
|
|
messages.append(message)
|
|
|
|
# Count, check and commit messages if necessary
|
|
self.offsets[partition] = message.offset
|
|
self.count_since_commit += 1
|
|
self._auto_commit()
|
|
count -= 1
|
|
|
|
self.size.value = 0
|
|
self.start.clear()
|
|
self.pause.set()
|
|
|
|
return messages
|