一、环境搭建

kafka的搭建依赖zookeeper，所以我们先配置zookeeper

# The number of milliseconds of each tick
tickTime=2000
# The number of ticks that the initial 
# synchronization phase can take
initLimit=10
# The number of ticks that can pass between 
# sending a request and getting an acknowledgement
syncLimit=5
# the directory where the snapshot is stored.
# do not use /tmp for storage, /tmp here is just 
# example sakes.
dataDir=/home/mq/zkdata
# the port at which the clients will connect
clientPort=2181

server.1=172.18.182.32:2888:3888
server.2=172.18.182.33:2888:3888
server.3=172.18.182.31:2888:3888

zookeeper正常启动后用zkServer.sh status查看状态。
然后配置Kafka的server.properties文件.

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

# The id of the broker. This must be set to a unique integer for each broker.
broker.id=0
delete.topic.enable=true
############################# 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
advertised.listeners=PLAINTEXT://172.18.182.32:9092

port=9092
host.name=172.18.182.32

# 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 network
num.network.threads=3

# The number of threads that the server uses for processing requests, which may include disk I/O
num.io.threads=8

# The send buffer (SO_SNDBUF) used by the socket server
socket.send.buffer.bytes=102400

# The receive buffer (SO_RCVBUF) used by the socket server
socket.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 files
log.dirs=/tmp/kafka-logs

# 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=1
transaction.state.log.replication.factor=1
transaction.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 age
log.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 policies
log.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=172.18.182.32:2181,172.18.182.33:2181,172.18.182.31:2181

# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000


############################# 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=0

之后启动三台kafka

/bin/kafka-server-start.sh -daemon kafka_2.12-2.4.0/config/server.properties

如果jps发现没启动，前台启动查看报错日志，或者取kafka/logs里面查看.

二、常用命令

# 启动kafka
bin/kafka-server-start.sh -daemon config/server.properties
# 创建一个topic
bin/kafka-topics.sh --create --bootstrap-server 172.18.182.32:2181,172.18.182.33:2181,172.18.182.31:2181 --replication-factor 2 --partitions 2 --topic queuing-user-create
# topic列表
bin/kafka-topics.sh --list --zookeeper 172.18.182.32:2181,172.18.182.33:2181,172.18.182.31:2181
# topic描述，如果加--topic则可以看某个topic
# PartitionCount：分区数量，ReplicationFactor：副本数量，Partition：分区编号，Leader：是否是负责读写的分区，如果只有一个则为None，Replicas：这个分区的副本在哪些节点，Isr：数据已同步的节点。
bin/kafka-topics.sh --describe --zookeeper 172.18.182.32:2181,172.18.182.33:2181,172.18.182.31:2181
Topic: queuing-survey-answer-status     PartitionCount: 2   ReplicationFactor: 2    Configs: 
    Topic: queuing-survey-answer-status Partition: 0    Leader: 1   Replicas: 1,2   Isr: 1
    Topic: queuing-survey-answer-status Partition: 1    Leader: 0   Replicas: 2,0   Isr: 0
Topic: queuing-survey-anwser    PartitionCount: 1   ReplicationFactor: 1    Configs: 
    Topic: queuing-survey-anwser    Partition: 0    Leader: none    Replicas: 2 Isr: 2
# 开启一个调试生产者
bin/kafka-console-producer.sh --broker-list 172.18.182.32:2181,172.18.182.33:2181,172.18.182.31:2181 --topic queuing-survey-anwser
# 开启一个调试消费者，也可以9092
bin/kafka-console-consumer.sh --bootstrap-server 172.18.182.32:2181,172.18.182.33:2181,172.18.182.31:2181  --topic queuing-user-create --from-beginning
# 日志查看
bin/kafka-run-class.sh kafka.tools.DumpLogSegments --files /tmp/kafka-logs/queuing-survey-answer-status-1/00000000000000000000.log --print-data-log
# 消费组查看
bin/kafka-consumer-groups.sh --bootstrap-server 172.18.182.32:9092,172.18.182.33:9092,172.18.182.31:9092 --group UserCenterProd --describe
# 手动设置offset
bin/kafka-consumer-groups.sh --bootstrap-server 172.18.182.32:9092,172.18.182.33:9092,172.18.182.31:9092 --group UserCenterProd --reset-offsets --topic queuing-user-add --to-offset 20 --execute

三、基础概念

• broker：即节点
• partition：分区，消息会根据key进入不同的分区，由不同的消费者（也可以相同，自动分配）消费。
  --replication-factor：备份，一般小于等于broker的数量。
• ISR：leader会追踪和维护ISR中所有follower的滞后状态。如果滞后太多（数量滞后和时间滞后两个维度，replica.lag.time.max.ms和replica.lag.max.message可配置），leader会把该replica从ISR中移除。被移除ISR的replica一直在追赶leader。如下图，leader写入数据后并不会commit，只有ISR列表中的所有folower同步之后才会commit，把滞后的follower移除ISR主要是避免写消息延迟。设置ISR主要是为了broker宕掉之后，重新选举partition的leader从ISR列表中选择。（转自 https://blog.csdn.net/dshf_1/article/details/82467558 ）
• consumer group: 同一个消费组中的不同消费者负责topic的一部分partition；如果是不同消费组，则独立计算offset，即对一个topic消费多次。
• zookeeper：分布式协调框架，负责协调管理并保存kafka的元数据，比如哪些broker在运行，创建了哪些topic，它们有哪些分区，leader在哪。

四、集群环境建议

五、最重要的集群参数配置

1）broker端参数

2）topic端参数

3）JVM参数

在启动kafka前配置java的默认堆大小

$> export KAFKA_HEAP_OPTS=--Xms6g  --Xmx6g
$> export KAFKA_JVM_PERFORMANCE_OPTS= -server -XX:+UseG1GC -XX:MaxGCPauseMillis=20 -XX:InitiatingHeapOccupancyPercent=35 -XX:+ExplicitGCInvokesConcurrent -Djava.awt.headless=true
$> bin/kafka-server-start.sh config/server.properties

4）操作系统参数

ulimit -n 1000000

文件系统可以选择XFS
swappiess设置为1
落盘时间可以适当延长