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from __future__ import absolute_import
try:
from itertools import zip_longest as izip_longest, repeat # pylint: disable=E0611
except ImportError:
from itertools import izip_longest as izip_longest, repeat # pylint: disable=E0611
import logging
import sys
import time
import warnings
from kafka.vendor import six
from kafka.vendor.six.moves import queue # pylint: disable=import-error
from .base import (
Consumer,
FETCH_DEFAULT_BLOCK_TIMEOUT,
AUTO_COMMIT_MSG_COUNT,
AUTO_COMMIT_INTERVAL,
FETCH_MIN_BYTES,
FETCH_BUFFER_SIZE_BYTES,
MAX_FETCH_BUFFER_SIZE_BYTES,
FETCH_MAX_WAIT_TIME,
ITER_TIMEOUT_SECONDS,
NO_MESSAGES_WAIT_TIME_SECONDS
)
from ..common import (
FetchRequestPayload, KafkaError, OffsetRequestPayload,
ConsumerFetchSizeTooSmall,
UnknownTopicOrPartitionError, NotLeaderForPartitionError,
OffsetOutOfRangeError, FailedPayloadsError, check_error
)
from kafka.protocol.message import PartialMessage
log = logging.getLogger(__name__)
class FetchContext(object):
"""
Class for managing the state of a consumer during fetch
"""
def __init__(self, consumer, block, timeout):
warnings.warn('deprecated - this class will be removed in a future'
' release', DeprecationWarning)
self.consumer = consumer
self.block = block
if block:
if not timeout:
timeout = FETCH_DEFAULT_BLOCK_TIMEOUT
self.timeout = timeout * 1000
def __enter__(self):
"""Set fetch values based on blocking status"""
self.orig_fetch_max_wait_time = self.consumer.fetch_max_wait_time
self.orig_fetch_min_bytes = self.consumer.fetch_min_bytes
if self.block:
self.consumer.fetch_max_wait_time = self.timeout
self.consumer.fetch_min_bytes = 1
else:
self.consumer.fetch_min_bytes = 0
def __exit__(self, type, value, traceback):
"""Reset values"""
self.consumer.fetch_max_wait_time = self.orig_fetch_max_wait_time
self.consumer.fetch_min_bytes = self.orig_fetch_min_bytes
class SimpleConsumer(Consumer):
"""
A simple consumer implementation that consumes all/specified partitions
for a topic
Arguments:
client: a connected SimpleClient
group: a name for this consumer, used for offset storage and must be unique
If you are connecting to a server that does not support offset
commit/fetch (any prior to 0.8.1.1), then you *must* set this to None
topic: the topic to consume
Keyword Arguments:
partitions: An optional list of partitions to consume the data from
auto_commit: default True. Whether or not to auto commit the offsets
auto_commit_every_n: default 100. How many messages to consume
before a commit
auto_commit_every_t: default 5000. How much time (in milliseconds) to
wait before commit
fetch_size_bytes: number of bytes to request in a FetchRequest
buffer_size: default 4K. Initial number of bytes to tell kafka we
have available. This will double as needed.
max_buffer_size: default 16K. Max number of bytes to tell kafka we have
available. None means no limit.
iter_timeout: default None. How much time (in seconds) to wait for a
message in the iterator before exiting. None means no
timeout, so it will wait forever.
auto_offset_reset: default largest. Reset partition offsets upon
OffsetOutOfRangeError. Valid values are largest and smallest.
Otherwise, do not reset the offsets and raise OffsetOutOfRangeError.
Auto commit details:
If both auto_commit_every_n and auto_commit_every_t are set, they will
reset one another when one is triggered. These triggers simply call the
commit method on this class. A manual call to commit will also reset
these triggers
"""
def __init__(self, client, group, topic, auto_commit=True, partitions=None,
auto_commit_every_n=AUTO_COMMIT_MSG_COUNT,
auto_commit_every_t=AUTO_COMMIT_INTERVAL,
fetch_size_bytes=FETCH_MIN_BYTES,
buffer_size=FETCH_BUFFER_SIZE_BYTES,
max_buffer_size=MAX_FETCH_BUFFER_SIZE_BYTES,
iter_timeout=None,
auto_offset_reset='largest'):
warnings.warn('deprecated - this class will be removed in a future'
' release. Use KafkaConsumer instead.',
DeprecationWarning)
super(SimpleConsumer, self).__init__(
client, group, topic,
partitions=partitions,
auto_commit=auto_commit,
auto_commit_every_n=auto_commit_every_n,
auto_commit_every_t=auto_commit_every_t)
if max_buffer_size is not None and buffer_size > max_buffer_size:
raise ValueError('buffer_size (%d) is greater than '
'max_buffer_size (%d)' %
(buffer_size, max_buffer_size))
self.buffer_size = buffer_size
self.max_buffer_size = max_buffer_size
self.fetch_max_wait_time = FETCH_MAX_WAIT_TIME
self.fetch_min_bytes = fetch_size_bytes
self.fetch_offsets = self.offsets.copy()
self.iter_timeout = iter_timeout
self.auto_offset_reset = auto_offset_reset
self.queue = queue.Queue()
def __repr__(self):
return '<SimpleConsumer group=%s, topic=%s, partitions=%s>' % \
(self.group, self.topic, str(self.offsets.keys()))
def reset_partition_offset(self, partition):
"""Update offsets using auto_offset_reset policy (smallest|largest)
Arguments:
partition (int): the partition for which offsets should be updated
Returns: Updated offset on success, None on failure
"""
LATEST = -1
EARLIEST = -2
if self.auto_offset_reset == 'largest':
reqs = [OffsetRequestPayload(self.topic, partition, LATEST, 1)]
elif self.auto_offset_reset == 'smallest':
reqs = [OffsetRequestPayload(self.topic, partition, EARLIEST, 1)]
else:
# Let's raise an reasonable exception type if user calls
# outside of an exception context
if sys.exc_info() == (None, None, None):
raise OffsetOutOfRangeError('Cannot reset partition offsets without a '
'valid auto_offset_reset setting '
'(largest|smallest)')
# Otherwise we should re-raise the upstream exception
# b/c it typically includes additional data about
# the request that triggered it, and we do not want to drop that
raise # pylint: disable=E0704
# send_offset_request
log.info('Resetting topic-partition offset to %s for %s:%d',
self.auto_offset_reset, self.topic, partition)
try:
(resp, ) = self.client.send_offset_request(reqs)
except KafkaError as e:
log.error('%s sending offset request for %s:%d',
e.__class__.__name__, self.topic, partition)
else:
self.offsets[partition] = resp.offsets[0]
self.fetch_offsets[partition] = resp.offsets[0]
return resp.offsets[0]
def seek(self, offset, whence=None, partition=None):
"""
Alter the current offset in the consumer, similar to fseek
Arguments:
offset: how much to modify the offset
whence: where to modify it from, default is None
* None is an absolute offset
* 0 is relative to the earliest available offset (head)
* 1 is relative to the current offset
* 2 is relative to the latest known offset (tail)
partition: modify which partition, default is None.
If partition is None, would modify all partitions.
"""
if whence is None: # set an absolute offset
if partition is None:
for tmp_partition in self.offsets:
self.offsets[tmp_partition] = offset
else:
self.offsets[partition] = offset
elif whence == 1: # relative to current position
if partition is None:
for tmp_partition, _offset in self.offsets.items():
self.offsets[tmp_partition] = _offset + offset
else:
self.offsets[partition] += offset
elif whence in (0, 2): # relative to beginning or end
reqs = []
deltas = {}
if partition is None:
# divide the request offset by number of partitions,
# distribute the remained evenly
(delta, rem) = divmod(offset, len(self.offsets))
for tmp_partition, r in izip_longest(self.offsets.keys(),
repeat(1, rem),
fillvalue=0):
deltas[tmp_partition] = delta + r
for tmp_partition in self.offsets.keys():
if whence == 0:
reqs.append(OffsetRequestPayload(self.topic, tmp_partition, -2, 1))
elif whence == 2:
reqs.append(OffsetRequestPayload(self.topic, tmp_partition, -1, 1))
else:
pass
else:
deltas[partition] = offset
if whence == 0:
reqs.append(OffsetRequestPayload(self.topic, partition, -2, 1))
elif whence == 2:
reqs.append(OffsetRequestPayload(self.topic, partition, -1, 1))
else:
pass
resps = self.client.send_offset_request(reqs)
for resp in resps:
self.offsets[resp.partition] = \
resp.offsets[0] + deltas[resp.partition]
else:
raise ValueError('Unexpected value for `whence`, %d' % whence)
# Reset queue and fetch offsets since they are invalid
self.fetch_offsets = self.offsets.copy()
self.count_since_commit += 1
if self.auto_commit:
self.commit()
self.queue = queue.Queue()
def get_messages(self, count=1, block=True, timeout=0.1):
"""
Fetch the specified number of messages
Keyword Arguments:
count: Indicates the maximum number of messages to be fetched
block: If True, the API will block till all messages are fetched.
If block is a positive integer the API will block until that
many messages are fetched.
timeout: When blocking is requested the function will block for
the specified time (in seconds) until count messages is
fetched. If None, it will block forever.
"""
messages = []
if timeout is not None:
timeout += time.time()
new_offsets = {}
log.debug('getting %d messages', count)
while len(messages) < count:
block_time = timeout - time.time()
log.debug('calling _get_message block=%s timeout=%s', block, block_time)
block_next_call = block is True or block > len(messages)
result = self._get_message(block_next_call, block_time,
get_partition_info=True,
update_offset=False)
log.debug('got %s from _get_messages', result)
if not result:
if block_next_call and (timeout is None or time.time() <= timeout):
continue
break
partition, message = result
_msg = (partition, message) if self.partition_info else message
messages.append(_msg)
new_offsets[partition] = message.offset + 1
# Update and commit offsets if necessary
self.offsets.update(new_offsets)
self.count_since_commit += len(messages)
self._auto_commit()
log.debug('got %d messages: %s', len(messages), messages)
return messages
def get_message(self, block=True, timeout=0.1, get_partition_info=None):
return self._get_message(block, timeout, get_partition_info)
def _get_message(self, block=True, timeout=0.1, get_partition_info=None,
update_offset=True):
"""
If no messages can be fetched, returns None.
If get_partition_info is None, it defaults to self.partition_info
If get_partition_info is True, returns (partition, message)
If get_partition_info is False, returns message
"""
start_at = time.time()
while self.queue.empty():
# We're out of messages, go grab some more.
log.debug('internal queue empty, fetching more messages')
with FetchContext(self, block, timeout):
self._fetch()
if not block or time.time() > (start_at + timeout):
break
try:
partition, message = self.queue.get_nowait()
if update_offset:
# Update partition offset
self.offsets[partition] = message.offset + 1
# Count, check and commit messages if necessary
self.count_since_commit += 1
self._auto_commit()
if get_partition_info is None:
get_partition_info = self.partition_info
if get_partition_info:
return partition, message
else:
return message
except queue.Empty:
log.debug('internal queue empty after fetch - returning None')
return None
def __iter__(self):
if self.iter_timeout is None:
timeout = ITER_TIMEOUT_SECONDS
else:
timeout = self.iter_timeout
while True:
message = self.get_message(True, timeout)
if message:
yield message
elif self.iter_timeout is None:
# We did not receive any message yet but we don't have a
# timeout, so give up the CPU for a while before trying again
time.sleep(NO_MESSAGES_WAIT_TIME_SECONDS)
else:
# Timed out waiting for a message
break
def _fetch(self):
# Create fetch request payloads for all the partitions
partitions = dict((p, self.buffer_size)
for p in self.fetch_offsets.keys())
while partitions:
requests = []
for partition, buffer_size in six.iteritems(partitions):
requests.append(FetchRequestPayload(self.topic, partition,
self.fetch_offsets[partition],
buffer_size))
# Send request
responses = self.client.send_fetch_request(
requests,
max_wait_time=int(self.fetch_max_wait_time),
min_bytes=self.fetch_min_bytes,
fail_on_error=False
)
retry_partitions = {}
for resp in responses:
try:
check_error(resp)
except UnknownTopicOrPartitionError:
log.error('UnknownTopicOrPartitionError for %s:%d',
resp.topic, resp.partition)
self.client.reset_topic_metadata(resp.topic)
raise
except NotLeaderForPartitionError:
log.error('NotLeaderForPartitionError for %s:%d',
resp.topic, resp.partition)
self.client.reset_topic_metadata(resp.topic)
continue
except OffsetOutOfRangeError:
log.warning('OffsetOutOfRangeError for %s:%d. '
'Resetting partition offset...',
resp.topic, resp.partition)
self.reset_partition_offset(resp.partition)
# Retry this partition
retry_partitions[resp.partition] = partitions[resp.partition]
continue
except FailedPayloadsError as e:
log.warning('FailedPayloadsError for %s:%d',
e.payload.topic, e.payload.partition)
# Retry this partition
retry_partitions[e.payload.partition] = partitions[e.payload.partition]
continue
partition = resp.partition
buffer_size = partitions[partition]
# Check for partial message
if resp.messages and isinstance(resp.messages[-1].message, PartialMessage):
# If buffer is at max and all we got was a partial message
# raise ConsumerFetchSizeTooSmall
if (self.max_buffer_size is not None and
buffer_size == self.max_buffer_size and
len(resp.messages) == 1):
log.error('Max fetch size %d too small', self.max_buffer_size)
raise ConsumerFetchSizeTooSmall()
if self.max_buffer_size is None:
buffer_size *= 2
else:
buffer_size = min(buffer_size * 2, self.max_buffer_size)
log.warning('Fetch size too small, increase to %d (2x) '
'and retry', buffer_size)
retry_partitions[partition] = buffer_size
resp.messages.pop()
for message in resp.messages:
if message.offset < self.fetch_offsets[partition]:
log.debug('Skipping message %s because its offset is less than the consumer offset',
message)
continue
# Put the message in our queue
self.queue.put((partition, message))
self.fetch_offsets[partition] = message.offset + 1
partitions = retry_partitions
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