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Kafka的3节点集群详细启动步骤(Zookeeper是外装)

 

 

 

  首先,声明,kafka集群是搭建在hadoop1、hadoop2和hadoop3机器上。

kafka_2.10-0.8.1.1.tgz的1或3节点集群的下载、安装和配置(图文详细教程)绝对干货

 

 

 

  如下分别是各自的配置信息。(网上说,还需要配置zookeeper.properties,其实不需要,因为,zookeeper集群那边已经配置好了。)

[hadoop@hadoop1 config]$ pwd
/home/hadoop/kafka/config
[hadoop@hadoop1 config]$ ll
total 32
-rw-r--r-- 1 hadoop hadoop 1199 Sep  3  2015 consumer.properties
-rw-r--r-- 1 hadoop hadoop 3846 Sep  3  2015 log4j.properties
-rw-r--r-- 1 hadoop hadoop 2228 Sep  3  2015 producer.properties
-rw-r--r-- 1 hadoop hadoop 5712 May  1 10:00 server.properties
-rw-r--r-- 1 hadoop hadoop 3325 Sep  3  2015 test-log4j.properties
-rw-r--r-- 1 hadoop hadoop  993 Sep  3  2015 tools-log4j.properties
-rw-r--r-- 1 hadoop hadoop 1023 Sep  3  2015 zookeeper.properties
[hadoop@hadoop1 config]$ 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=1

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

# The port the socket server listens on
port=9092

# Hostname the broker will bind to. If not set, the server will bind to all interfaces
host.name=192.168.80.121

# 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=3
 
# 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=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 seperated list of directories under which to store log files
log.dirs=/home/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=5

# 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

############################# 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
log.retention.hours=168

# 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=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

# 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=false

export HBASE_MANAGES_ZK=false
offsets.storage=kafka
dual.commit.enabled=true
delete.topic.enable=true

############################# 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=192.168.80.121:2181,192.168.80.122:2181,192.168.80.123:2181

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

 

 

 

 

 

 

# 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=2

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

# The port the socket server listens on
port=9092

# Hostname the broker will bind to. If not set, the server will bind to all interfaces
host.name=192.168.80.122

# 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=3
 
# 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=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 seperated list of directories under which to store log files
log.dirs=/home/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=5

# 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

############################# 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
log.retention.hours=168

# 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=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

# 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=false

export HBASE_MANAGES_ZK=false
offsets.storage=kafka
dual.commit.enabled=true
delete.topic.enable=true

############################# 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=192.168.80.121:2181,192.168.80.122:2181,192.168.80.123:2181

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

 

 

 

 

 

 

 

 

 

 

# 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=3

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

# The port the socket server listens on
port=9092

# Hostname the broker will bind to. If not set, the server will bind to all interfaces
host.name=192.168.80.123

# 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=3
 
# 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=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 seperated list of directories under which to store log files
log.dirs=/home/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=5

# 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

############################# 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
log.retention.hours=168

# 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=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

# 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=false


export HBASE_MANAGES_ZK=false
offsets.storage=kafka
dual.commit.enabled=true
delete.topic.enable=true


############################# 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=192.168.80.121:2181,192.168.80.122:2181,192.168.80.123:2181

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

 

 

 

 

 

   Kafka的3节点集群详细启动步骤

 

第一步、首先启动kafka进程

[hadoop@hadoop1 kafka]$ nohup bin/kafka-server-start.sh config/server.properties > kafka.log 2>&1 &

[2] 4609



[hadoop@hadoop2 kafka]$ nohup bin/kafka-server-start.sh config/server.properties > kafka.log 2>&1 &

[2] 10077

[hadoop@hadoop3 kafka]$ nohup bin/kafka-server-start.sh config/server.properties > kafka.log 2>&1 &

[1] 8079

 

第二步、创建topics 

[hadoop@hadoop1 bin]$ ./kafka-topics.sh --zookeeper hadoop1:2181,hadoop2:2181,hadoop3:2181 --create --topic t-behavior --replication-factor 3 --partitions 3

 

  或者

[hadoop@hadoop1 bin]$ ./kafka-topics.sh --zookeeper hadoop1:2181 --create --topic t-behavior --replication-factor 3 --partitions 3

 

 

 

 

第三步:查看topic 和 topic详情

[hadoop@hadoop1 bin]$ ./kafka-topics.sh --zookeeper hadoop1:2181,hadoop2:2181,hadoop3:2181 --list

t-behavior

 

[hadoop@hadoop1 bin]$ ./kafka-topics.sh --zookeeper hadoop1:2181,hadoop2:2181,hadoop3:2181 --describe --topic t-behavior

 

  或者
[hadoop@hadoop1 bin]$ 

./kafka-topics.sh --zookeeper hadoop1:2181 --list

t-behavior

 

[hadoop@hadoop1 bin]$ ./kafka-topics.sh --zookeeper hadoop1:2181 --describe --topic t-behavior

Topic:t-behavior PartitionCount:1 ReplicationFactor:3 Configs:
Topic: t-behavior Partition: 0 Leader: 3 Replicas: 3,2,1 Isr: 3,1,2

 

 

 

第四步:开启Kafka producer生产者(在hadoop1和hadoop2和hadoop3都可以)
  模拟producer发送消息
用命令行的方式手动的往kafka的topic里面发送消息:

[hadoop@hadoop2 bin]$ ./kafka-console-producer.sh --broker-list hadoop1:9092,hadoop1:9092,hadoop1:9092 --topic t-behavior

[2015-09-24 14:03:24,616] WARN Property topic is not valid (kafka.utils.VerifiableProperties)
This is Kafka producer.
Hello

 

或者

[hadoop@hadoop2 bin]$ ./kafka-console-producer.sh --broker-list hadoop1:9092 --topic t-behavior

 


第五步:开启Kafka consumer消费者(在hadoop1和hadoop2和hadoop3都可以)

[hadoop@hadoop3 bin]$./kafka-console-consumer.sh --zookeeper hadoop1:2181,hadoop2:2181,hadoop3:2181 --topic t-behavior --from-beginning

This is Kafka producer.
Hello

 

或者

[hadoop@hadoop3 bin]$./kafka-console-consumer.sh --zookeeper hadoop1:2181 --topic t-behavior

 

 

 

第六步:停止kafka
cd $KAFKA_HOME/bin

./kafka-server-stop.sh

或者找到kafka的进程,直接kill掉即可。

 

 

    

彻底删除topic:
  1、删除kafka存储目录(server.properties文件log.dirs配置,默认为"/tmp/kafka-logs")相关topic目录
  2、如果配置了delete.topic.enable=true直接通过命令删除,如果命令删除不掉,直接通过zookeeper-client 删除掉broker下的topic即可。
[hadoop@hadoop1 bin]$ ./kafka-topics.sh --delete --zookeeper hadoop1:2181,hadoop2:2181,hadoop3:2181 --topic t-behavior

 

 

 

 

 

  其实啊,现在越来越多的优秀插件出来了。

  可以不需这么命令行去做了,直接界面化多么的好!

基于Web的Kafka管理器工具之Kafka-manager安装之后第一次进入web UI的初步配置(图文详解)

 

posted @ 2017-05-01 10:58  大数据和AI躺过的坑  阅读(5823)  评论(0编辑  收藏  举报