Kafka日志压缩未启动 [英] Kafka Log Compaction not starting

问题描述

我有一个主题，其内容如下:

I have a topic with the following description:

Topic:test-topic    PartitionCount:1    ReplicationFactor:1 Configs:min.cleanable.dirty.ratio=0.01,min.compaction.lag.ms=86400000,cleanup.policy=compact
    Topic: test-topic   Partition: 0    Leader: 1   Replicas: 1 Isr: 1

我的经纪人具有log.cleaner.enable = true

My broker has log.cleaner.enable=true

本主题有870778条消息，其中存在许多重复的密钥(有些重复达到数千个).根据Kafka docs 所述，Kafka应该在这些条件下部署日志压缩，并修剪除具有给定密钥的最新消息.数周(甚至数月)之后，就不会发生这种情况.我在这里缺少什么来启动日志压缩?

This topic has 870778 messages within which lots of duplicate keys exist (some reaching thousands of duplicates). According to Kafka docs, Kafka should be deploying log compaction under these conditions and pruning all but the newest message with a given key. This is not happening after several weeks, if not months. What am I missing here to jump-start log compaction?

经纪人配置:

# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
# 
#    http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# see kafka.server.KafkaConfig for additional details and defaults

############################# Server Basics #############################

# The id of the broker. This must be set to a unique integer for each broker.
broker.id=1

############################# Socket Server Settings #############################

# The port the socket server listens on
port=<port>

# Hostname the broker will bind to. If not set, the server will bind to all interfaces
#host.name=localhost

# Hostname the broker will advertise to producers and consumers. If not set, it uses the
# value for "host.name" if configured.  Otherwise, it will use the value returned from
# java.net.InetAddress.getCanonicalHostName().
#advertised.host.name=<hostname routable by clients>

# The port to publish to ZooKeeper for clients to use. If this is not set,
# it will publish the same port that the broker binds to.
#advertised.port=<port accessible by clients>

# The number of threads handling network requests
num.network.threads=8

# The number of threads doing disk I/O
num.io.threads=8

# The send buffer (SO_SNDBUF) used by the socket server
socket.send.buffer.bytes=1048576

# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=1048576

# The maximum size of a request that the socket server will accept (protection against OOM)
socket.request.max.bytes=104857600

############################# Log Basics #############################

# A comma seperated list of directories under which to store log files
log.dirs=<dir-path>

# The default number of log partitions per topic. More partitions allow greater
# parallelism for consumption, but this will also result in more files across
# the brokers.
num.partitions=30

############################# Log Flush Policy #############################

# Messages are immediately written to the filesystem but by default we only fsync() to sync
# the OS cache lazily. The following configurations control the flush of data to disk. 
# There are a few important trade-offs here:
#    1. Durability: Unflushed data may be lost if you are not using replication.
#    2. Latency: Very large flush intervals may lead to latency spikes when the flush does occur as there will be a lot of data to flush.
#    3. Throughput: The flush is generally the most expensive operation, and a small flush interval may lead to exceessive seeks. 
# The settings below allow one to configure the flush policy to flush data after a period of time or
# every N messages (or both). This can be done globally and overridden on a per-topic basis.

# The number of messages to accept before forcing a flush of data to disk
log.flush.interval.messages=20000
inter.broker.protocol.version=0.8.2.0
log.message.format.version=0.8.2.0

# The maximum amount of time a message can sit in a log before we force a flush
log.flush.interval.ms=10000
message.max.bytes=1000000
auto.create.topics.enable=false
log.index.interval.bytes=4096
log.index.size.max.bytes=10485760
log.flush.scheduler.interval.ms=2000
log.roll.hours=24
log.retention.check.interval.ms=300000
log.segment.bytes=1073741824
############################# Log Retention Policy #############################

# The following configurations control the disposal of log segments. The policy can
# be set to delete segments after a period of time, or after a given size has accumulated.
# A segment will be deleted whenever *either* of these criteria are met. Deletion always happens
# from the end of the log.

# The minimum age of a log file to be eligible for deletion
log.retention.hours=24

# A size-based retention policy for logs. Segments are pruned from the log as long as the remaining
# segments don't drop below log.retention.bytes.
#log.retention.bytes=1073741824

# The maximum size of a log segment file. When this size is reached a new log segment will be created.
log.segment.bytes=536870912

# The interval at which log segments are checked to see if they can be deleted according 
# to the retention policies

# By default the log cleaner is disabled and the log retention policy will default to just delete segments after their retention expires.
# If log.cleaner.enable=true is set the cleaner will be enabled and individual logs can then be marked for log compaction.
log.cleaner.enable=true

default.replication.factor=3
num.replica.fetchers=4
replica.fetch.max.bytes=1048576
replica.fetch.wait.max.ms=2000
replica.high.watermark.checkpoint.interval.ms=5000
replica.socket.timeout.ms=60000
replica.socket.receive.buffer.bytes=65536
replica.lag.time.max.ms=30000
replica.lag.max.messages=12000

controller.socket.timeout.ms=60000
controller.message.queue.size=20

auto.leader.rebalance.enable=true
leader.imbalance.per.broker.percentage=5
leader.imbalance.check.interval.seconds=300

############################# Zookeeper #############################

# Zookeeper connection string (see zookeeper docs for details).
# This is a comma separated host:port pairs, each corresponding to a zk
# server. e.g. "127.0.0.1:3000,127.0.0.1:3001,127.0.0.1:3002".
# You can also append an optional chroot string to the urls to specify the
# root directory for all kafka znodes.

zookeeper.connect=<connection-string>

# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=1000000
#zk.sync.time.ms=2000

kafka.metrics.reporters=com.airbnb.kafka.KafkaStatsdMetricsReporter

# enable the reporter, (false)
external.kafka.statsd.reporter.enabled=true

# the host of the StatsD server (localhost)
external.kafka.statsd.host=statsd
# the port of the StatsD server (8995)
external.kafka.statsd.port=<port>

# a prefix for all metrics names (empty)
external.kafka.statsd.metrics.prefix=<connection-string>

推荐答案

要运行压缩，您至少需要2个段文件(一个完成并运行一个).

To have compaction running you need to have at least 2 segment files (one finished and one running).

根据您的配置

log.segment.bytes=1073741824
log.segment.bytes=536870912

(请检查为什么具有两个相同的属性).

(please check why you have two identical properties).

您需要拥有一个完整的512Mb文件，以便kafka可以对其进行压缩.请检查您是否至少有2个要压缩的主题分区文件

You need to have one file 512Mb full so kafka can run compaction on it. Please check that you have at least 2 segment files for topic-partition you want to be compacted

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