63 lines
2.4 KiB
Python
63 lines
2.4 KiB
Python
from __future__ import absolute_import
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import logging
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from kafka.partitioner import HashedPartitioner
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from .base import (
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Producer, BATCH_SEND_DEFAULT_INTERVAL,
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BATCH_SEND_MSG_COUNT
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)
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log = logging.getLogger("kafka")
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class KeyedProducer(Producer):
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"""
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A producer which distributes messages to partitions based on the key
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Args:
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client - The kafka client instance
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partitioner - A partitioner class that will be used to get the partition
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to send the message to. Must be derived from Partitioner
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async - If True, the messages are sent asynchronously via another
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thread (process). We will not wait for a response to these
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ack_timeout - Value (in milliseconds) indicating a timeout for waiting
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for an acknowledgement
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batch_send - If True, messages are send in batches
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batch_send_every_n - If set, messages are send in batches of this size
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batch_send_every_t - If set, messages are send after this timeout
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"""
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def __init__(self, client, partitioner=None, async=False,
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req_acks=Producer.ACK_AFTER_LOCAL_WRITE,
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ack_timeout=Producer.DEFAULT_ACK_TIMEOUT,
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codec=None,
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batch_send=False,
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batch_send_every_n=BATCH_SEND_MSG_COUNT,
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batch_send_every_t=BATCH_SEND_DEFAULT_INTERVAL):
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if not partitioner:
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partitioner = HashedPartitioner
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self.partitioner_class = partitioner
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self.partitioners = {}
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super(KeyedProducer, self).__init__(client, async, req_acks,
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ack_timeout, codec, batch_send,
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batch_send_every_n,
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batch_send_every_t)
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def _next_partition(self, topic, key):
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if topic not in self.partitioners:
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if not self.client.has_metadata_for_topic(topic):
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self.client.load_metadata_for_topics(topic)
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self.partitioners[topic] = self.partitioner_class(self.client.get_partition_ids_for_topic(topic))
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partitioner = self.partitioners[topic]
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return partitioner.partition(key, self.client.get_partition_ids_for_topic(topic))
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def send(self, topic, key, msg):
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partition = self._next_partition(topic, key)
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return self.send_messages(topic, partition, msg)
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def __repr__(self):
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return '<KeyedProducer batch=%s>' % self.async
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