m2m模型翻译
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 

71 lines
3.0 KiB

from __future__ import absolute_import
import collections
import threading
from kafka import errors as Errors
from kafka.future import Future
class FutureProduceResult(Future):
def __init__(self, topic_partition):
super(FutureProduceResult, self).__init__()
self.topic_partition = topic_partition
self._latch = threading.Event()
def success(self, value):
ret = super(FutureProduceResult, self).success(value)
self._latch.set()
return ret
def failure(self, error):
ret = super(FutureProduceResult, self).failure(error)
self._latch.set()
return ret
def wait(self, timeout=None):
# wait() on python2.6 returns None instead of the flag value
return self._latch.wait(timeout) or self._latch.is_set()
class FutureRecordMetadata(Future):
def __init__(self, produce_future, relative_offset, timestamp_ms, checksum, serialized_key_size, serialized_value_size, serialized_header_size):
super(FutureRecordMetadata, self).__init__()
self._produce_future = produce_future
# packing args as a tuple is a minor speed optimization
self.args = (relative_offset, timestamp_ms, checksum, serialized_key_size, serialized_value_size, serialized_header_size)
produce_future.add_callback(self._produce_success)
produce_future.add_errback(self.failure)
def _produce_success(self, offset_and_timestamp):
offset, produce_timestamp_ms, log_start_offset = offset_and_timestamp
# Unpacking from args tuple is minor speed optimization
(relative_offset, timestamp_ms, checksum,
serialized_key_size, serialized_value_size, serialized_header_size) = self.args
# None is when Broker does not support the API (<0.10) and
# -1 is when the broker is configured for CREATE_TIME timestamps
if produce_timestamp_ms is not None and produce_timestamp_ms != -1:
timestamp_ms = produce_timestamp_ms
if offset != -1 and relative_offset is not None:
offset += relative_offset
tp = self._produce_future.topic_partition
metadata = RecordMetadata(tp[0], tp[1], tp, offset, timestamp_ms, log_start_offset,
checksum, serialized_key_size,
serialized_value_size, serialized_header_size)
self.success(metadata)
def get(self, timeout=None):
if not self.is_done and not self._produce_future.wait(timeout):
raise Errors.KafkaTimeoutError(
"Timeout after waiting for %s secs." % (timeout,))
assert self.is_done
if self.failed():
raise self.exception # pylint: disable-msg=raising-bad-type
return self.value
RecordMetadata = collections.namedtuple(
'RecordMetadata', ['topic', 'partition', 'topic_partition', 'offset', 'timestamp', 'log_start_offset',
'checksum', 'serialized_key_size', 'serialized_value_size', 'serialized_header_size'])