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{大数据}Kafka

发布时间: 2018-01-18 17:33:50

​Kafka是什么:

kafka + storm/spark streaming

    Apache Kafka是一个开源消息系统,由Scala写成。是由Apache软件基金会开发的一个开源消息系统项目。

    Kafka最初是由LinkedIn开发,并于2011年初开源。2012年10月从Apache Incubator毕业。该项目的目标是为处理实时数据提供一个统一、高通量、低等待的平台。

    Kafka是一个分布式消息队列:生产者、消费者的功能。它提供了类似于JMS的特性,但是在设计实现上完全不同,此外它并不是JMS规范的实现。

    Kafka对消息保存时根据Topic进行归类,发送消息者称为Producer,消息接受者称为Consumer,此外kafka集群有多个kafka实例组成,每个实例(server)成为broker。

    无论是kafka集群,还是producer和consumer都依赖于zookeeper集群保存一些meta(元数据)信息,来保证系统可用性


Kafka核心组件:

    Topic :消息根据Topic进行归类

     Producer:发送消息者

    Consumer:消息接受者

    broker:每个kafka实例(server)

    Zookeeper:依赖集群保存meta信息。


Kafka集群部署:

1. 集群部署的基本流程

    下载安装包、解压安装包、修改配置文件、分发安装包、启动集群

    2. Kafka集群部署 

        1) 下载安装包

                http://kafka.apache.org/downloads

        2) 解压安装包

                [hadoop@hdp08 ~]$ tar zxvf kafka_2.12-1.0.0.tgz -C apps

        3) 修改配置文件

                [hadoop@hdp08 kafka]$ vi config/server.properties

输入以下内容:

# 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

#用来监听链接的端口,producer或consumer将在此端口建立连接

port=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


# 处理网络请求的线程数量

num.network.threads=3


# 用来处理磁盘IO的线程数量

num.io.threads=8


# 发送socket的缓冲区大小

socket.send.buffer.bytes=102400


# 接受socket的缓冲区大小

socket.receive.buffer.bytes=102400


# The maximum size of a request that the socket server will accept (protection against OOM)

# 请求socket的缓冲区大小

socket.request.max.bytes=104857600



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


# kafka运行日志存放的路径

log.dirs=/home/hadoop/apps/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

# topic在当前broker上的分片个数

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.

# 用来恢复和清理data下数据的线程数量

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 for 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 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=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

# segment文件保留的最长时间,超时将被删除

log.retention.hours=168

#滚动生成新的segment文件的最大时间

log.roll.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=hdp08:2181,hdp09:2181,hdp10:2181


# 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.

         4) 分发安装包​        

            [hadoop@hdp08 apps]$ scp -r kafka hadoop@hdp09:/home/hadoop/apps

            [hadoop@hdp08 apps]$ scp -r kafka hadoop@hdp10:/home/hadoop/apps

​        5) 再次修改配置文件(重要)

            依次修改各服务器上配置文件的的broker.id,分别是1,2,3不得重复。​

​        6) 启动集群依次在各节点上启动kafka

            bin/kafka-server-start.sh  config/server.properties

​        7) Kafka常用操作命令l 查看当前服务器中的所有topic

                bin/kafka-topics.sh --list --zookeeper  hdp08:2181

            创建topic

                bin/kafka-topics.sh --create --zookeeper hdp08:2181 --replication-factor 1 --partitions 3 --topic first

            删除topic

                bin/kafka-topics.sh --delete --zookeeper hdp08:2181 --topic first

            需要server.properties中设置delete.topic.enable=true否则只是标记删除或者直接重启。

             通过shell命令发送消息

                bin/kafka-console-producer.sh --broker-list hdp08:9092 --topic first

            通过shell消费消息

                bin/kafka-console-consumer.sh --zookeeper hdp08:2181 --from-beginning --topic first

            查看消费位置

                bin/kafka-run-class.sh kafka.tools.ConsumerOffsetChecker --zookeeper hdp08:2181 --                group testGroup

            查看某个Topic的详情

                bin/kafka-topics.sh --topic first --describe --zookeeper hdp08:2181

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