Windows系统下模拟Kafka集群参数调优

　　配置kafka运行环境
　　kafka的包中已经包含了zookeeper但是我还是喜欢单独下载一个zookeeper 下载kafka
　　https://archive.apache.org/dist/kafka/2.6.3/kafka_2.12-2.6.3.tgz 下载zookeeper
　　https://www.apache.org/dyn/closer.lua/zookeeper/zookeeper-3.6.3/apache-zookeeper-3.6.3-bin.tar.gz 配置zookeeper
　　解压下载的zookeeper安装包
　　复制三份并修改文件夹的名字(其实可以用三份配置但是我喜欢复制三份) 修改点一 新建zkData文件夹
　　在每一份的目录下新建zkData文件夹
　　修改点二 新建myid文件
　　在每一份的zkData文件夹中新建myid文件，并分别把内容修改为 1 2 3
　　修改点三 修改配置文件
　　将conf目录下的zoo_sample.cfg 文件修改为 zoo.cfg,并修改文件内容
　　修改文件内容
　　第一处 dataDir 修改为zkData文件夹 注意路径要用双反斜杠
　　第二处 端口号 因为是在一台机器上跑多个实例所以端口号不能冲突
　　第三处添加入下内容
　　server.1=localhost:2881:3881server.2=localhost:2882:3882server.3=localhost:2883:3883
　　配置参数说明
　　server.A=B:C:D
　　A是一个数字，表示这个是第几号服务器；
　　集群模式下配置一个文件myid，这个文件在dataDir目录下，这个文件里面有一个数据就是A的值，Zookeeper启动时读取此文件，拿到里面的数据与zoo.cfg里面的配置信息比较从而判断到底是哪个server。
　　B是这个服务器的地址；
　　C是这个服务器Follower与集群中的Leader服务器交换信息的端口；
　　D是万一集群中的Leader服务器挂了，需要一个端口来重新进行选举，选出一个新的Leader，而这个端口就是用来执行选举时服务器相互通信的端口。
　　修改后的三个文件内容 # The number of milliseconds of each ticktickTime=2000# The number of ticks that the initial # synchronization phase can takeinitLimit=10# The number of ticks that can pass between # sending a request and getting an acknowledgementsyncLimit=5# the directory where the snapshot is stored.# do not use /tmp for storage, /tmp here is just # example sakes.dataDir=D:soft-repositoryzookeeperapache-zookeeper-3.6.3-bin-1zkData# the port at which the clients will connectclientPort=2181# the maximum number of client connections.# increase this if you need to handle more clients#maxClientCnxns=60## Be sure to read the maintenance section of the # administrator guide before turning on autopurge.## http://zookeeper.apache.org/doc/current/zookeeperAdmin.html#sc_maintenance## The number of snapshots to retain in dataDir#autopurge.snapRetainCount=3# Purge task interval in hours# Set to ＂0＂ to disable auto purge feature#autopurge.purgeInterval=1## Metrics Providers## https://prometheus.io Metrics Exporter#metricsProvider.className=org.apache.zookeeper.metrics.prometheus.PrometheusMetricsProvider#metricsProvider.httpPort=7000#metricsProvider.exportJvmInfo=trueserver.1=localhost:2881:3881server.2=localhost:2882:3882server.3=localhost:2883:3883启动zookeeper集群
　　在cmd中进入每一份的zookeeper文件夹中，执行binzkServer.cmd
　　配置kafka
　　在D盘根目录复制解压后的kafka三份 修改configserver.properties
　　broker.id=0
　　log.dirs=/tmp/kafka-logs-1
　　zookeeper.connect=localhost:2181,localhost:2182,localhost:2183/kafka
　　port=9091
　　端口号三份分别为9091 9092 9093 # 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 address the socket server listens on. It will get the value returned from # java.net.InetAddress.getCanonicalHostName() if not configured.#   FORMAT:#     listeners = listener_name://host_name:port#   EXAMPLE:#     listeners = PLAINTEXT://your.host.name:9092#listeners=PLAINTEXT://:9092# Hostname and port the broker will advertise to producers and consumers. If not set, # it uses the value for ＂listeners＂ if configured.  Otherwise, it will use the value# returned from java.net.InetAddress.getCanonicalHostName().#advertised.listeners=PLAINTEXT://your.host.name:9092# Maps listener names to security protocols, the default is for them to be the same. See the config documentation for more details#listener.security.protocol.map=PLAINTEXT:PLAINTEXT,SSL:SSL,SASL_PLAINTEXT:SASL_PLAINTEXT,SASL_SSL:SASL_SSL# The number of threads that the server uses for receiving requests from the network and sending responses to the networknum.network.threads=3# The number of threads that the server uses for processing requests, which may include disk I/Onum.io.threads=8# The send buffer (SO_SNDBUF) used by the socket serversocket.send.buffer.bytes=102400# The receive buffer (SO_RCVBUF) used by the socket serversocket.receive.buffer.bytes=102400# The maximum size of a request that the socket server will accept (protection against OOM)socket.request.max.bytes=104857600############################# Log Basics ############################## A comma separated list of directories under which to store log fileslog.dirs=/tmp/kafka-logs-1# 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=1# The number of threads per data directory to be used for log recovery at startup and flushing at shutdown.# This value is recommended to be increased for installations with data dirs located in RAID array.num.recovery.threads.per.data.dir=1############################# Internal Topic Settings  ############################## The replication factor for the group metadata internal topics ＂__consumer_offsets＂ and ＂__transaction_state＂# For anything other than development testing, a value greater than 1 is recommended to ensure availability such as 3.offsets.topic.replication.factor=1transaction.state.log.replication.factor=1transaction.state.log.min.isr=1############################# 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 excessive 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=10000# The maximum amount of time a message can sit in a log before we force a flush#log.flush.interval.ms=1000############################# 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 due to agelog.retention.hours=168# A size-based retention policy for logs. Segments are pruned from the log unless the remaining# segments drop below log.retention.bytes. Functions independently of log.retention.hours.#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=1073741824# The interval at which log segments are checked to see if they can be deleted according# to the retention policieslog.retention.check.interval.ms=300000############################# 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=localhost:2181,localhost:2182,localhost:2183/kafka# Timeout in ms for connecting to zookeeperzookeeper.connection.timeout.ms=18000############################# Group Coordinator Settings ############################## The following configuration specifies the time, in milliseconds, that the GroupCoordinator will delay the initial consumer rebalance.# The rebalance will be further delayed by the value of group.initial.rebalance.delay.ms as new members join the group, up to a maximum of max.poll.interval.ms.# The default value for this is 3 seconds.# We override this to 0 here as it makes for a better out-of-the-box experience for development and testing.# However, in production environments the default value of 3 seconds is more suitable as this will help to avoid unnecessary, and potentially expensive, rebalances during application startup.group.initial.rebalance.delay.ms=0port=9091启动kafkabinwindowskafka-server-start.bat configserver.propertiestopic查看topicbinwindowskafka-topics.bat --bootstrap-server localhost:9091 --list创建topicbinwindowskafka-topics.bat --bootstrap-server localhost:9091 --create --partitions 1 --replication-factor 1 --topic hello-test查看topic的详情binwindowskafka-topics.bat --bootstrap-server localhost:9091 --describe --topic hello-test修改分区数
　　注意：分区数只能增加，不能减少 binwindowskafka-topics.bat --bootstrap-server localhost:9091 --alter --topic hello-test --partitions 3删除topicbinwindowskafka-topics.bat --bootstrap-server localhost:9091 --delete --topic hello集群压力测试
　　用 Kafka自带的脚本，对 Kafka 进行压测。
　　生产者压测脚本：kafka-producer-perf-test.sh
　　消费者压测脚本：kafka-consumer-perf-test.sh Kafka Producer 压力测试创建一个 hello-test topic，设置为 3 个分区 3 个副本binwindowskafka-topics.bat --bootstrap-server localhost:9091 --create --replication-factor 3 --partitions 3 --topic hello-test测试生产者binwindowskafka-producer-perf-test.bat --topic hello-test --record-size 1024 --num-records 1000000 --throughput -1 --producer-props bootstrap.servers=localhost:9091,localhost:9092,localhost:9093 batch.size=16384 linger.ms=0
　　–record-size 是一条信息有多大，单位是字节，本次测试设置为 1k。
　　–num-records 是总共发送多少条信息，本次测试设置为 100 万条。
　　–throughput 是每秒多少条信息，设成-1，表示不限流，尽可能快的生产数据，可测出生产者最大吞吐量。
　　–producer-props 后面可以配置生产者相关参数，batch.size 配置为 16k 调整 batch.size 大小
　　batch.size 默认值是 16k 将 batch.size 设置为 32k binwindowskafka-producer-perf-test.bat --topic hello-test --record-size 1024 --num-records 1000000 --throughput 10000 --producer-props bootstrap.servers=localhost:9091,localhost:9092,localhost:9093 batch.size=32768 linger.ms=0
　　batch.size 默认值是 16k。将 batch.size 设置为 4k。 binwindowskafka-producer-perf-test.bat --topic hello-test --record-size 1024 --num-records 1000000 --throughput 10000 --producer-props bootstrap.servers=localhost:9091,localhost:9092,localhost:9093 batch.size=4096 linger.ms=0调整linger.ms
　　linger.ms 默认是 0ms。将 linger.ms 设置为 50ms。 binwindowskafka-producer-perf-test.bat --topic hello-test --record-size 1024 --num-records 1000000 --throughput 10000 --producer-props bootstrap.servers=localhost:9091,localhost:9092,localhost:9093 batch.size=4096 linger.ms=50压缩方式
　　调整压缩方式 默认的压缩方式是 none。将compression.type 设置为 snappy。 binwindowskafka-producer-perf-test.bat --topic hello-test --record-size 1024 --num-records 1000000 --throughput 10000 --producer-props bootstrap.servers=localhost:9091,localhost:9092,localhost:9093 batch.size=4096 linger.ms=50 compression.type=snappy
　　默认的压缩方式是 none。将compression.typee 设置为 zstd。 binwindowskafka-producer-perf-test.bat --topic hello-test --record-size 1024 --num-records 1000000 --throughput 10000 --producer-props bootstrap.servers=localhost:9091,localhost:9092,localhost:9093 batch.size=4096 linger.ms=50 compression.type=zstd
　　默认的压缩方式是 none。将compression.type 设置为 gzip。 binwindowskafka-producer-perf-test.bat --topic hello-test --record-size 1024 --num-records 1000000 --throughput 10000 --producer-props bootstrap.servers=localhost:9091,localhost:9092,localhost:9093 batch.size=4096 linger.ms=50 compression.type=gzip
　　默认的压缩方式是 none。将compression.type 设置为 lz4 binwindowskafka-producer-perf-test.bat --topic hello-test --record-size 1024 --num-records 1000000 --throughput 10000 --producer-props bootstrap.servers=localhost:9091,localhost:9092,localhost:9093 batch.size=4096 linger.ms=50 compression.type=lz4调整缓存大小buffer.memory
　　调整缓存大小 默认生产者端缓存大小 32m。将 buffer.memory 设置为 64m。 binwindowskafka-producer-perf-test.bat --topic hello-test --record-size 1024 --num-records 1000000 --throughput -1 --producer-props bootstrap.servers=localhost:9091,localhost:9092,localhost:9093 batch.size=4096 linger.ms=50 buffer.memory=67108864测试Consumer性能默认情况的吞吐量binwindowskafka-consumer-perf-test.bat --bootstrap-server localhost:9091,localhost:9092,localhost:9093 --topic hello-test --messages 10000000 --consumer.config config/consumer.properties --timeout 10000
　　–bootstrap-server 指定 Kafka 集群地址
　　–topic 指定 topic 的名称
　　–messages 总共要消费的消息个数
　　调整 max.poll.records
　　一次拉取条数为 2000
　　修改config/consumer.properties 文件中的一次拉取条数为 2000 max.poll.records=2000
　　一次拉取条数为 20000
　　修改config/consumer.properties 文件中的一次拉取条数为 20000 max.poll.records=20000
　　一次拉取条数为 200000
　　修改config/consumer.properties 文件中的一次拉取条数为 200000 max.poll.records=200000
　　可以看到每秒的消息数量已经不会提升了
　　一次拉取条数为 100000
　　修改config/consumer.properties 文件中的一次拉取条数为 100000 max.poll.records=100000
　　fetch.max.bytes
　　修改/opt/module/kafka/config/consumer.properties 文件中的拉取一批数据大小 100m fetch.max.bytes=104857600