【kafka】——概述&安装

一、概述

1. 定义

Kafka传统定义：Kafka是一个分布式的基于发布/订阅模式的消息队列（Message Queue），主要应用于大数据实时处理领域。
发布/订阅：消息的发布者不会将消息直接发送给特定的订阅者，而是将发布的消息分为不同的类别，订阅者只接受感兴趣的消息。
kafka最新定义：Kafka是一个开源的分布式事件流平台 （Event sSreaming Platform）,被数千家公司用于高性能数据管道、流分析、数据集成和关键任务应用。

2. 消息队列两种模式

<1> 点对点模式

消费者主动拉去数据，消息收到后清楚消息

<2> 发布/订阅模式

可以有多个topic主题
消费者消费数据后，不删除数
每个消费者相互独立，都可以消费到数据

3. 基础架构

<1> 为了方便扩展，并提高吞吐量，一个topic分为了多个partition
<2> 配合分区的设计，提出消费者组的概念，组内每个消费者并行消费
<3> 一个分区的消息，只能由一个消费者消费
<4> 为了提高可靠性，为每个partition增加若干个副本，类似NameNode HA
<5> Zookeeper记录Kafka集群中的运行状态，leader follower 等信息
<6> 2.8.0 之前的Kafak必须和Zookeeper 配合使用，2.8.0 及以后为可选。

二、入门

1. 安装

<1>集群规划

<2> 官网下载

https://kafka.apache.org/

<3> 解压

cd /opt/software
tar -zxv kafka_2.12-3.0.0.tgz -C /opt/module/

<4>重命名

cd /opt/module
mv kafka_2.12-3.0.0/ kafka

<5> 修改配置文件

1. broker.id须要是唯一的
2. log.dirs
3. zookeeper.connect

cd /opt/module/kafka/config
cp server.properties server.properties.bak
vim server.properties

# 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=0

############################# 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 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=/opt/module/kafka/datas

# 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=hadoop102:2181,hadoop103:2181,hadoop104:2181/kafka

# Timeout in ms for connecting to zookeeper
zookeeper.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=0

<6> 创建目录

cd /opt/module/kafka
mkdir datas

<7> 分发

将安装包分发到其他server。并修改对应broker.id

<8> 配置环境变量

1. 打开文件

sudo vim /etc/profile.d/my_env.sh

2. 追加以下内容

#KAFKA_HOME
export KAFKA_HOME=/opt/module/kafka
export PATH=$PATH:$KAFKA_HOME/bin

3. 分发配置文件（或者直接在其他server 修改环境变量）

sudo /root/bin/xsync /etc/profile.d/my_env.sh

4. 在所有server执行命令

source /etc/profile

<9> 启动

cd /opt/module/kafka
bin/kafka-server-start.sh -daemon config/server.properties

<10> 停止

cd /opt/module/kafka
bin/kafka-server-stop.sh

需要等待kafka进程彻底停止后再停止zookeeper，否则kafka进程将无法停止，只能通过kill-9 结束进程。

2. 启停脚本

vi kf.sh

#!/bin/bash

case $1 in
"start")
    {
        for i in hadoop102 hadoop103 hadoop104; do
            echo "----------------- kafka $i start -----------------"
            ssh $i "/opt/module/kafka/bin/kafka-server-start.sh -daemon /opt/module/kafka/config/server.properties"
        done

    }
    ;;
"stop")
    {
        for i in hadoop102 hadoop103 hadoop104; do
            echo "----------------- kafka $i start -----------------"
            ssh $i "/opt/module/kafka/bin/kafka-server-stop.sh"
        done
    }
    ;;

esac

chmod 777 kf.sh

3. 命令行操作

<1> topic命令行操作

1. 查看操作topic命令参数

cd /opt/module/kafka 
bin/kafka-topics.sh

2. 查看所有topic

bin/kafka-topics.sh --bootstrap-server hadoop102:9092,hadoop103:9092,hadoop104:9092 --list

3. 创建topic

bin/kafka-topics.sh --bootstrap-server hadoop102:9092,hadoop103:9092,hadoop104:9092 --topic test_topic --create --partitions 1 --replication-factor 3

topic名为test_topic ，分区为1，副本为3

4. 查看topic详细信息

bin/kafka-topics.sh --bootstrap-server hadoop102:9092,hadoop103:9092,hadoop104:9092 --topic test_topic --describe

5. 修改topic
分区数只能增加不能减少，不能通过命令行方式修改副本

bin/kafka-topics.sh --bootstrap-server hadoop102:9092,hadoop103:9092,hadoop104:9092 --topic test_topic --alter --partitions 3

<2> producer命令行操作

1. 查看操作producer命令参数

cd /opt/module/kafka 
bin/kafka-console-producer.sh

2. 连接topic生产数据

bin/kafka-console-producer.sh --bootstrap-server hadoop102:9092,hadoop103:9092,hadoop104:9092 --topic test_topic

<3> consumer命令行操作

1. 查看操作consumer命令参数

cd /opt/module/kafka 
bin/kafka-console-consumer.sh

2. 连接topic消费数据

bin/kafka-console-consumer.sh --bootstrap-server hadoop102:9092,hadoop103:9092,hadoop104:9092 --topic test_topic