Hadoop 2.7.7 完全分布式部署

组件版本**

组件 版本 下载地址
Hadoop 2.7.7 https://archive.apache.org/dist/hadoop/common/hadoop-2.7.7/hadoop-2.7.7.tar.gz
JDK 1.8 https://www.oracle.com/java/technologies/javase/javase-jdk8-downloads.html

**机器环境 **

IP 主机名 密码
192.168.222.201 master password
192.168.222.202 slave1 password
192.169.222.203 slave2 password

1、机器基础环境

参考地址:https://blog.csdn.net/su_mingyang/article/details/118070573

  1. 关闭防火墙,设置开机不自启(三台虚拟机都要做该操作)
  2. 配置hosts文件(三天能够互相通信)
  3. 配置SSH
  4. 时间同步配置NTP或使用date手动调整

2、安装java(三台机器都要安装)

参考地址:https://blog.csdn.net/su_mingyang/article/details/120872313

3、部署hadoop完全分布式

3.1 解压hadoop文件

[root@master ~]#

命令:

tar -xzf /chinaskills/hadoop-2.7.7.tar.gz -C /usr/local/src/

3.2 重命名为hadoop

[root@master ~]#

命令:

mv /usr/local/src/hadoop-2.7.7 /usr/local/src/hadoop

3.3 配置hadoop环境变量(仅当前用户生效)

[root@master ~]#

命令:

vi /root/.bash_profile 

配置内容:

export HADOOP_HOME=/usr/local/src/hadoop
export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin

3.4 加载环境变量

[root@master ~]#

命令:

source /root/.bash_profile

3.5 查看hadoop的版本信息

[root@master ~]#

命令:

hadoop version 

输出信息:

Hadoop 2.7.7
Subversion Unknown -r c1aad84bd27cd79c3d1a7dd58202a8c3ee1ed3ac
Compiled by stevel on 2018-07-18T22:47Z
Compiled with protoc 2.5.0
From source with checksum 792e15d20b12c74bd6f19a1fb886490
This command was run using /usr/local/src/hadoop/share/hadoop/common/hadoop-common-2.7.7.jar

3.6 配置hadoop-env.sh

[root@master ~]#

命令:

vi /usr/local/src/hadoop/etc/hadoop/hadoop-env.sh 

配置内容:

export JAVA_HOME=/usr/local/src/java

3.7 配置core-site.xml

[root@master ~]#

命令:

vi /usr/local/src/hadoop/etc/hadoop/core-site.xml

配置内容:

<property>
  
  <name>fs.defaultFSname>
  <value>hdfs://master:9000value>
property>
<property>
  
  <name>hadoop.tmp.dirname>
  <value>/usr/local/src/hadoop/dfs/tmpvalue>
property>

3.8 配置hdfs-site.xml

[root@master ~]#

命令:

vi /usr/local/src/hadoop/etc/hadoop/hdfs-site.xml 

配置内容:

<property>
  
  <name>dfs.replicationname>
  <value>3value>
property>
<property>
  
  <name>dfs.namenode.name.dirname>
  <value>/usr/local/src/hadoop/dfs/namevalue>
property>
<property>
  
  <name>dfs.datanode.data.dirname>
  <value>/usr/local/src/hadoop/dfs/datavalue>
property>

3.9 配置mapred-site.xml

[root@master ~]#

命令:

cp /usr/local/src/hadoop/etc/hadoop/mapred-site.xml.template /usr/local/src/hadoop/etc/hadoop/mapred-site.xml
vi /usr/local/src/hadoop/etc/hadoop/mapred-site.xml

配置内容:

<property>
  <name>mapreduce.framework.namename>
  <value>yarnvalue>
property>

3.10 配置yarn-site.xml

[root@master ~]#

命令:

 vi /usr/local/src/hadoop/etc/hadoop/yarn-site.xml 

配置内容:

<property>
  <name>yarn.nodemanager.aux-servicesname>
  <value>mapreduce_shufflevalue>
property>
<property>  
    <name>yarn.resourcemanager.addressname>  
    <value>master:8032value>  
property> 
<property>
    <name>yarn.resourcemanager.scheduler.addressname>  
    <value>master:8030value>  
property>
<property>
    <name>yarn.resourcemanager.resource-tracker.addressname>  
    <value>master:8031value>  
property>

<property>
    <name>yarn.nodemanager.vmem-check-enabledname>
    <value>falsevalue>
property>

3.11 配置slaves

[root@master ~]#

命令:

 vi /usr/local/src/hadoop/etc/hadoop/slaves

配置内容:

master
slave1
slave2

3.12 将文件分发给slave1和slave2

[root@master ~]#

命令:

scp -r /usr/local/src/hadoop slave1:/usr/local/src/  
scp -r /usr/local/src/hadoop slave2:/usr/local/src/ 
scp /root/.bash_profile  slave1:/root/
scp /root/.bash_profile  slave2:/root/

3.13 对namenode进行格式化

[root@master ~]#

命令:

hdfs namenode -format

最后十行输出信息:

21/10/19 01:18:21 INFO namenode.FSImage: Allocated new BlockPoolId: BP-1164747633-192.168.222.201-1634577501149
21/10/19 01:18:21 INFO common.Storage: Storage directory /usr/local/src/hadoop/dfs/name has been successfully formatted.
21/10/19 01:18:21 INFO namenode.FSImageFormatProtobuf: Saving image file /usr/local/src/hadoop/dfs/name/current/fsimage.ckpt_0000000000000000000 using no compression
21/10/19 01:18:21 INFO namenode.FSImageFormatProtobuf: Image file /usr/local/src/hadoop/dfs/name/current/fsimage.ckpt_0000000000000000000 of size 320 bytes saved in 0 seconds.
21/10/19 01:18:21 INFO namenode.NNStorageRetentionManager: Going to retain 1 images with txid >= 0
21/10/19 01:18:21 INFO util.ExitUtil: Exiting with status 0
21/10/19 01:18:21 INFO namenode.NameNode: SHUTDOWN_MSG: 
/************************************************************
SHUTDOWN_MSG: Shutting down NameNode at master/192.168.222.201
************************************************************/

3.14 启动集群

[root@master ~]#

命令:

start-all.sh

输出信息:

This script is Deprecated. Instead use start-dfs.sh and start-yarn.sh
Starting namenodes on [master]
master: starting namenode, logging to /usr/local/src/hadoop/logs/hadoop-root-namenode-master.out
slave2: starting datanode, logging to /usr/local/src/hadoop/logs/hadoop-root-datanode-slave2.out
slave1: starting datanode, logging to /usr/local/src/hadoop/logs/hadoop-root-datanode-slave1.out
master: starting datanode, logging to /usr/local/src/hadoop/logs/hadoop-root-datanode-master.out
Starting secondary namenodes [0.0.0.0]
The authenticity of host '0.0.0.0 (0.0.0.0)' can't be established.
ECDSA key fingerprint is d3:a9:ba:a4:63:70:24:88:37:25:a2:60:2e:e1:e9:31.
Are you sure you want to continue connecting (yes/no)? yes
0.0.0.0: Warning: Permanently added '0.0.0.0' (ECDSA) to the list of known hosts.
0.0.0.0: starting secondarynamenode, logging to /usr/local/src/hadoop/logs/hadoop-root-secondarynamenode-master.out
starting yarn daemons
starting resourcemanager, logging to /usr/local/src/hadoop/logs/yarn-root-resourcemanager-master.out
slave2: starting nodemanager, logging to /usr/local/src/hadoop/logs/yarn-root-nodemanager-slave2.out
slave1: starting nodemanager, logging to /usr/local/src/hadoop/logs/yarn-root-nodemanager-slave1.out
master: starting nodemanager, logging to /usr/local/src/hadoop/logs/yarn-root-nodemanager-master.out

3.15 查看节点信息

[root@master ~]# jps
4448 DataNode
4325 NameNode
4853 NodeManager
4599 SecondaryNameNode
4744 ResourceManager
5128 Jps
[root@slave1 ~]# jps
3474 DataNode
3570 NodeManager
3682 Jps
[root@slave2 ~]# jps
3418 DataNode
3514 NodeManager
3626 Jps

3.16 运行pi程序测试

[root@master ~]#

命令:

hadoop jar /usr/local/src/hadoop/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.7.jar pi 10 10

输出结果:

Number of Maps  = 10
Samples per Map = 10
Wrote input for Map #0
Wrote input for Map #1
Wrote input for Map #2
Wrote input for Map #3
Wrote input for Map #4
Wrote input for Map #5
Wrote input for Map #6
Wrote input for Map #7
Wrote input for Map #8
Wrote input for Map #9
Starting Job
21/10/19 01:22:10 INFO client.RMProxy: Connecting to ResourceManager at master/192.168.222.201:8032
21/10/19 01:22:11 INFO input.FileInputFormat: Total input paths to process : 10
21/10/19 01:22:11 INFO mapreduce.JobSubmitter: number of splits:10
21/10/19 01:22:11 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1634577560934_0001
21/10/19 01:22:11 INFO impl.YarnClientImpl: Submitted application application_1634577560934_0001
21/10/19 01:22:11 INFO mapreduce.Job: The url to track the job: http://master:8088/proxy/application_1634577560934_0001/
21/10/19 01:22:11 INFO mapreduce.Job: Running job: job_1634577560934_0001
21/10/19 01:22:20 INFO mapreduce.Job: Job job_1634577560934_0001 running in uber mode : false
21/10/19 01:22:20 INFO mapreduce.Job:  map 0% reduce 0%
21/10/19 01:22:31 INFO mapreduce.Job:  map 20% reduce 0%
21/10/19 01:22:41 INFO mapreduce.Job:  map 20% reduce 7%
21/10/19 01:22:50 INFO mapreduce.Job:  map 40% reduce 7%
21/10/19 01:22:51 INFO mapreduce.Job:  map 100% reduce 7%
21/10/19 01:22:52 INFO mapreduce.Job:  map 100% reduce 100%
21/10/19 01:22:52 INFO mapreduce.Job: Job job_1634577560934_0001 completed successfully
21/10/19 01:22:52 INFO mapreduce.Job: Counters: 49
	File System Counters
		FILE: Number of bytes read=226
		FILE: Number of bytes written=1352945
		FILE: Number of read operations=0
		FILE: Number of large read operations=0
		FILE: Number of write operations=0
		HDFS: Number of bytes read=2600
		HDFS: Number of bytes written=215
		HDFS: Number of read operations=43
		HDFS: Number of large read operations=0
		HDFS: Number of write operations=3
	Job Counters 
		Launched map tasks=10
		Launched reduce tasks=1
		Data-local map tasks=10
		Total time spent by all maps in occupied slots (ms)=242528
		Total time spent by all reduces in occupied slots (ms)=19189
		Total time spent by all map tasks (ms)=242528
		Total time spent by all reduce tasks (ms)=19189
		Total vcore-milliseconds taken by all map tasks=242528
		Total vcore-milliseconds taken by all reduce tasks=19189
		Total megabyte-milliseconds taken by all map tasks=248348672
		Total megabyte-milliseconds taken by all reduce tasks=19649536
	Map-Reduce Framework
		Map input records=10
		Map output records=20
		Map output bytes=180
		Map output materialized bytes=280
		Input split bytes=1420
		Combine input records=0
		Combine output records=0
		Reduce input groups=2
		Reduce shuffle bytes=280
		Reduce input records=20
		Reduce output records=0
		Spilled Records=40
		Shuffled Maps =10
		Failed Shuffles=0
		Merged Map outputs=10
		GC time elapsed (ms)=3019
		CPU time spent (ms)=5370
		Physical memory (bytes) snapshot=2012909568
		Virtual memory (bytes) snapshot=22836789248
		Total committed heap usage (bytes)=1383833600
	Shuffle Errors
		BAD_ID=0
		CONNECTION=0
		IO_ERROR=0
		WRONG_LENGTH=0
		WRONG_MAP=0
		WRONG_REDUCE=0
	File Input Format Counters 
		Bytes Read=1180
	File Output Format Counters 
		Bytes Written=97
Job Finished in 41.825 seconds
Estimated value of Pi is 3.20000000000000000000

3.17 查看web界面

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