Hadoop2.2.0使用之初体验

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离10月15日Hadoop发布2.2.0这个稳定版本已经过去2个月了，最近终于抽了点时间搭建了一个3节点的集群，体验了一把YARN上如何跑Map/Reduce程序了。

每次搭建Hadoop测试集群都或多或少的碰到一些问题，几乎没有一次是一步到位的了，这次也不例外，也碰到过几个问题，不过Google很快帮忙解决了。

安装使用Hadoop2.2.0务必要先搞清除OS是32位还是64位的，由于Apache社区的版本是使用32位的Linux来编译的，所以如果是使用64位的机器跑Hadoop节点的时候，加载本地库就会存在问题，需要自行下载源代码来编辑Hadoop源码来获取部署包。如果OS是32位的则简单多了，直接使用社区版本即可。对于源代码编辑Hadoop2.2.0的源代，码，需要准备好maven、protoc2.5.0等环境。具体可以参见：hadoop2.2.0 centos 编译安装详解

这次的机器是机房的3台备用机器:

OS：64位的CentOS 6.4

【192.168.1.216】 RAM32G/CPU2*4Core/STAT300G （NameNode/SecondaryNameNode/DataNode/ResourceManager）

【192.168.1.217】 RAM8G/CPU2*4Core/STAT500G （DataNode/NodeManager）

【192.168.1.218】 RAM8G/CPU2*4Core/STAT500G （DataNode/NodeManager）

（1）修改hostname

在3台机器的/etc/hosts文件末尾都加入：

192.168.1.216 lrts216
192.168.1.217 lrts217
192.168.1.218 lrts218

A：修改192.168.1.217 hostname

在192.168.1.216这台机器上修改hostname，以root用户来执行：hostname lrts216

同时修改/etc/sysconfig/network文件：

NETWORKING=yes
HOSTNAME=lrts216

B：修改192.168.1.217 hostname

在192.168.1.217这台机器上修改hostname，以root用户来执行：hostname lrts217

同时修改/etc/sysconfig/network文件：

NETWORKING=yes
HOSTNAME=lrts217

C：修改192.168.1.218 hostname

在192.168.1.218这台机器上修改hostname，以root用户来执行：hostname lrts218

同时修改/etc/sysconfig/network文件：

NETWORKING=yes
HOSTNAME=lrts218

（2）配置SSH无密码登录

在3台机器上创建hadoop用户组，以及hadoop用户，家目录统一为/home/hadoop

以root用户分别在3台机器上执行如下命令：

groupadd hadoop

useradd -g hadoop -d /home/hadoop hadoop

lrts216:

以用户hadoop登录lrts216，在/home/hadoop目录下执行下述命令：

ssh-keygen -t rsa

一路回车下去即可在目录/home/hadoop/.ssh/下建立两个文件 id_rsa.pub和id_rsa。

进入/home/hadoop/.ssh目录，用SCP命令把is_rsa.pub文件复制到lrts217和lrts218上去。

scp id_rsa.pub hadoop@lrts217:/home/hadoop/.ssh/lrts216keys

scp id_rsa.pub hadoop@lrts218:/home/hadoop/.ssh/lrts216keys

当然这里都少不了要输入密码哦

lrts217:

以用户hadoop登录lrts217，在/home/hadoop目录下执行下述命令：

ssh-keygen -t rsa

一路回车下去即可在目录/home/hadoop/.ssh/下建立两个文件 id_rsa.pub和id_rsa。

进入/home/hadoop/.ssh目录，用SCP命令把is_rsa.pub文件复制到lrts216上去。

scp id_rsa.pub hadoop@lrts216:/home/hadoop/.ssh/lrts217keys

当然这里都少不了要输入密码哦

lrts218:

以用户hadoop登录lrts218，在/home/hadoop目录下执行下述命令：

ssh-keygen -t rsa

一路回车下去即可在目录/home/hadoop/.ssh/下建立两个文件 id_rsa.pub和id_rsa。

进入/home/hadoop/.ssh目录，用SCP命令把is_rsa.pub文件复制到lrts216上去。

scp id_rsa.pub hadoop@lrts216:/home/hadoop/.ssh/lrts218keys

当然这里都少不了要输入密码哦

上述方式分别为lrts216、lrts217、lrts218机器生成了rsa密钥，并且把lrts216的id_rsa.pub复制到lrts217/lrts218上去了，而把lrts217和lrts218上的id_rsa.pub复制到lrts216上去了，接下来还需要执行如下步骤才算完事。

lrts216:

以hadoop用户登录lrts216，并且进入目录/home/hadoop/.ssh下，执行如下命令：

cat id_rsa.pub >> authorized_keys
cat lrts217keys >> authorized_keys
cat lrts218keys >> authorized_keys
chmod 644 authorized_keys

lrts217:

以hadoop用户登录lrts217，并且进入目录/home/hadoop/.ssh下，执行如下命令：

cat id_rsa.pub >> authorized_keys
cat lrts216keys >> authorized_keys
chmod 644 authorized_keys

lrts218:

以hadoop用户登录lrts218，并且进入目录/home/hadoop/.ssh下，执行如下命令：

cat id_rsa.pub >> authorized_keys
cat lrts216keys >> authorized_keys
chmod 644 authorized_keys

至此，以用户hadoop登录lrts216后即可以无密钥认证方式访问lrts217和lrts218了，同样以用户hadoop登录lrts217和lrts218也可以无密钥认证方式访问lrts216。

上述的SSH配置非常容易遗漏，遗漏了后续启动Hadoop必然会报各种hostname找不到的错误了，反正是网络错误要优先来排查这个点上配置是否靠谱了。

（3）下载Hadoop2.2.0

从hadoop官网上下载hadoop-2.2.0.tar.gz

进入/home/hadoop/目录，执行：wget http://mirrors.cnnic.cn/apache/hadoop/common/hadoop-2.2.0/hadoop-2.2.0.tar.gz即可下载

使用tar -zxvf hadoop-2.2.0.tar.gz来解压缩，解压缩后的目录为/home/hadoop/hadoop-2.2.0

（4）配置JDK（3台机器相同）

我使用的是jdk-7u45-linux-x64.gz

最终的JAVA_HOME目录为/usr/local/jdk1.7.0_45

以root用户登录3台机器，修改/etc/profile文件，在末尾加入：

export JAVA_HOME=/usr/local/jdk1.7.0_45
export PATH=$PATH:$JAVA_HOME/jre/bin:$JAVA_HOME/bin

执行java -version可以看到如下结果则表示成功！如果这个都搞不定，也别玩什么hadoop了，还早着呢！

[root@lrts216 ~]# java -version
java version "1.7.0_45"
Java(TM) SE Runtime Environment (build 1.7.0_45-b18)
Java HotSpot(TM) 64-Bit Server VM (build 24.45-b08, mixed mode)

其实，到这里为止，所有的配置与之前的版本的Hadoop一模一样的，我又写一次，无非是觉得每次折腾的时候，都或多或少会碰到问题，所以也就把详细的过程都记录下来，权当加强记忆吧了！之前也写过一篇在Redhat AS6上搭建Hadoop集群总结，前半部分基本是一致的。

从下面开始与原来的版本相比就有些不同了。

（5）配置环境变量（3台机器同配置）

分别修改的如下文件/home/hadoop/.bash_profile，在文件末尾加入：

# Hadoopexport HADOOP_PREFIX="/home/hadoop/hadoop-2.2.0"export PATH=$PATH:$HADOOP_PREFIX/binexport PATH=$PATH:$HADOOP_PREFIX/sbinexport HADOOP_MAPRED_HOME=${HADOOP_PREFIX}export HADOOP_COMMON_HOME=${HADOOP_PREFIX}export HADOOP_HDFS_HOME=${HADOOP_PREFIX}export YARN_HOME=${HADOOP_PREFIX}# Native Pathexport HADOOP_COMMON_LIB_NATIVE_DIR=${HADOOP_PREFIX}/lib/nativeexport HADOOP_OPTS="-Djava.library.path=$HADOOP_PREFIX/lib/native"

修改如下两个文件（该修改的修改，该添加的添加）

/home/hadoop/hadoop-2.2.0/etc/hadoop/hadoop-env.sh

/home/hadoop/hadoop-2.2.0/etc/hadoop/yarn-env.sh

原来的内容：

# The java implementation to use.export JAVA_HOME=${JAVA_HOME}

修改为：

# The java implementation to use.export JAVA_HOME=/usr/local/jdk1.7.0_45

追加如下部分：

export HADOOP_COMMON_LIB_NATIVE_DIR=${HADOOP_PREFIX}/lib/nativeexport HADOOP_OPTS="-Djava.library.path=$HADOOP_PREFIX/lib/native"

（6）配置hadoop那些xml文件（3台机器同配置）

现在提到的配置文件，统一指目录hadoop-2.2.0/etc/hadoop下的同名文件。

core-site.xml

<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="configuration.xsl"?><configuration><property><name>fs.defaultFS</name><value>hdfs://lrts216:9000</value></property><property><name>io.file.buffer.size</name><value>131072</value></property><property><name>hadoop.tmp.dir</name><value>file:/home/hadoop/hadoop-2.2.0/tmp</value><description>Abase for other temporary directories.</description></property></configuration>

core-site.xml

<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="configuration.xsl"?><configuration><property><name>dfs.namenode.secondary.http-address</name><value>lrts218:50090</value></property><property><name>dfs.namenode.name.dir</name><value>file:/home/hadoop/hadoop-2.2.0/dfs/name</value></property><property><name>dfs.datanode.data.dir</name><value>file:/home/hadoop/hadoop-2.2.0/dfs/data</value></property><property><name>dfs.replication</name><value>2</value></property></configuration>

yarn-site.xml

<?xml version="1.0"?><configuration><property><name>yarn.nodemanager.aux-services</name><value>mapreduce_shuffle</value></property><property><name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name><value>org.apache.hadoop.mapred.ShuffleHandler</value></property><property><name>yarn.resourcemanager.address</name><value>lrts216:8032</value></property><property><name>yarn.resourcemanager.scheduler.address</name><value>lrts216:8030</value></property><property><name>yarn.resourcemanager.resource-tracker.address</name><value>lrts216:8031</value></property><property><name>yarn.resourcemanager.admin.address</name><value>lrts216:8033</value></property><property><name>yarn.resourcemanager.webapp.address</name><value>lrts216:8088</value></property></configuration>

slaves

lrts216lrts217lrts218

（7）启动HDFS和YARN

先进入hadoop-2.2.0/bin/目录执行如下命令：./hdfs namenode -format，完成格式化命名节点。

进入hadoop-2.2.0/sbin/目录，执行./start-dfs.ssh和./start-yarm.sh来启动hdfs和yarn。

启动成功则在lrts216节点上执行jps命令查看Java进程，能看到如下进程则表示启动成功了。

[hadoop@lrts216 sbin]$ jps
5859 NodeManager
5741 ResourceManager
4163 NameNode
4467 SecondaryNameNode
31747 Jps
4290 DataNode

进入目录/home/hadoop/hadoop-2.2.0，执行如下命令即可看到hadoop集群的概况

[hadoop@lrts216 hadoop-2.2.0]$ pwd/home/hadoop/hadoop-2.2.0[hadoop@lrts216 hadoop-2.2.0]$ bin/hdfs dfsadmin -report13/12/21 13:48:56 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicableConfigured Capacity: 710826487808 (662.01 GB)Present Capacity: 604646686720 (563.12 GB)DFS Remaining: 604646334464 (563.12 GB)DFS Used: 352256 (344 KB)DFS Used%: 0.00%Under replicated blocks: 0Blocks with corrupt replicas: 0Missing blocks: 0-------------------------------------------------Datanodes available: 2 (3 total, 1 dead)Live datanodes:Name: 192.168.1.216:50010 (lrts216)Hostname: lrts216Decommission Status : NormalConfigured Capacity: 227023720448 (211.43 GB)DFS Used: 176128 (172 KB)Non DFS Used: 79267975168 (73.82 GB)DFS Remaining: 147755569152 (137.61 GB)DFS Used%: 0.00%DFS Remaining%: 65.08%Last contact: Sat Dec 21 13:48:55 CST 2013Name: 192.168.1.218:50010 (lrts218)Hostname: lrts218Decommission Status : NormalConfigured Capacity: 483802767360 (450.58 GB)DFS Used: 176128 (172 KB)Non DFS Used: 26911825920 (25.06 GB)DFS Remaining: 456890765312 (425.51 GB)DFS Used%: 0.00%DFS Remaining%: 94.44%Last contact: Sat Dec 21 13:48:54 CST 2013Dead datanodes:Name: 192.168.1.217:50010 (lrts217)Hostname: lrts217Decommission Status : NormalConfigured Capacity: 0 (0 B)DFS Used: 0 (0 B)Non DFS Used: 0 (0 B)DFS Remaining: 0 (0 B)DFS Used%: 100.00%DFS Remaining%: 0.00%Last contact: Sat Dec 21 13:19:59 CST 2013

（8）执行wordcount程序
[hadoop@lrts216 bin]$ hdfs dfs -mkdir -p /lrts/zhangzk
13/12/19 22:20:41 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
[hadoop@lrts216 bin]$ hdfs dfs -ls /
13/12/19 22:20:48 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Found 1 items
drwxr-xr-x - hadoop supergroup 0 2013-12-19 22:20 /lrts
[hadoop@lrts216 bin]$ hdfs dfs -put hdfs.cmd /lrts/zhangzk/
13/12/19 22:21:16 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
[hadoop@lrts216 bin]$ ll
total 252
-rwxr--r--. 1 hadoop hadoop 78809 Oct 7 14:38 container-executor
-rwxr--r--. 1 hadoop hadoop 4857 Oct 7 14:38 hadoop
-rwxr--r--. 1 hadoop hadoop 7530 Oct 7 14:38 hadoop.cmd
-rwxr--r--. 1 hadoop hadoop 7954 Oct 7 14:38 hdfs
-rwxr--r--. 1 hadoop hadoop 5138 Oct 7 14:38 hdfs.cmd
-rwxr--r--. 1 hadoop hadoop 4989 Oct 7 14:38 mapred
-rwxr--r--. 1 hadoop hadoop 5560 Oct 7 14:38 mapred.cmd
-rwxr--r--. 1 hadoop hadoop 1776 Oct 7 14:38 rcc
-rwxr--r--. 1 hadoop hadoop 95102 Oct 7 14:38 test-container-executor
-rwxr--r--. 1 hadoop hadoop 8548 Oct 7 14:38 yarn
-rwxr--r--. 1 hadoop hadoop 8322 Oct 7 14:38 yarn.cmd
[hadoop@lrts216 bin]$ hadoop jar /home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.2.0.jar wordcount /lrts/zhangzk /lrts/out
13/12/19 22:24:55 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
13/12/19 22:24:56 INFO client.RMProxy: Connecting to ResourceManager at lrts216/192.168.1.216:8032
13/12/19 22:24:57 INFO input.FileInputFormat: Total input paths to process : 1
13/12/19 22:24:57 INFO mapreduce.JobSubmitter: number of splits:1
13/12/19 22:24:57 INFO Configuration.deprecation: user.name is deprecated. Instead, use mapreduce.job.user.name
13/12/19 22:24:57 INFO Configuration.deprecation: mapred.jar is deprecated. Instead, use mapreduce.job.jar
13/12/19 22:24:57 INFO Configuration.deprecation: mapred.output.value.class is deprecated. Instead, use mapreduce.job.output.value.class
13/12/19 22:24:57 INFO Configuration.deprecation: mapreduce.combine.class is deprecated. Instead, use mapreduce.job.combine.class
13/12/19 22:24:57 INFO Configuration.deprecation: mapreduce.map.class is deprecated. Instead, use mapreduce.job.map.class
13/12/19 22:24:57 INFO Configuration.deprecation: mapred.job.name is deprecated. Instead, use mapreduce.job.name
13/12/19 22:24:57 INFO Configuration.deprecation: mapreduce.reduce.class is deprecated. Instead, use mapreduce.job.reduce.class
13/12/19 22:24:57 INFO Configuration.deprecation: mapred.input.dir is deprecated. Instead, use mapreduce.input.fileinputformat.inputdir
13/12/19 22:24:57 INFO Configuration.deprecation: mapred.output.dir is deprecated. Instead, use mapreduce.output.fileoutputformat.outputdir
13/12/19 22:24:57 INFO Configuration.deprecation: mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
13/12/19 22:24:57 INFO Configuration.deprecation: mapred.output.key.class is deprecated. Instead, use mapreduce.job.output.key.class
13/12/19 22:24:57 INFO Configuration.deprecation: mapred.working.dir is deprecated. Instead, use mapreduce.job.working.dir
13/12/19 22:24:57 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1387462237922_0001
13/12/19 22:24:58 INFO impl.YarnClientImpl: Submitted application application_1387462237922_0001 to ResourceManager at lrts216/192.168.1.216:8032
13/12/19 22:24:58 INFO mapreduce.Job: The url to track the job: http://lrts216:8088/proxy/application_1387462237922_0001/
13/12/19 22:24:58 INFO mapreduce.Job: Running job: job_1387462237922_0001
13/12/19 22:25:06 INFO mapreduce.Job: Job job_1387462237922_0001 running in uber mode : false
13/12/19 22:25:06 INFO mapreduce.Job: map 0% reduce 0%
13/12/19 22:25:11 INFO mapreduce.Job: map 100% reduce 0%
13/12/19 22:25:17 INFO mapreduce.Job: map 100% reduce 100%
13/12/19 22:25:17 INFO mapreduce.Job: Job job_1387462237922_0001 completed successfully
13/12/19 22:25:18 INFO mapreduce.Job: Counters: 43
File System Counters
FILE: Number of bytes read=4715
FILE: Number of bytes written=167555
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
HDFS: Number of bytes read=5244
HDFS: Number of bytes written=3660
HDFS: Number of read operations=6
HDFS: Number of large read operations=0
HDFS: Number of write operations=2
Job Counters
Launched map tasks=1
Launched reduce tasks=1
Rack-local map tasks=1
Total time spent by all maps in occupied slots (ms)=2410
Total time spent by all reduces in occupied slots (ms)=2941
Map-Reduce Framework
Map input records=171
Map output records=523
Map output bytes=6735
Map output materialized bytes=4715
Input split bytes=106
Combine input records=523
Combine output records=264
Reduce input groups=264
Reduce shuffle bytes=4715
Reduce input records=264
Reduce output records=264
Spilled Records=528
Shuffled Maps =1
Failed Shuffles=0
Merged Map outputs=1
GC time elapsed (ms)=35
CPU time spent (ms)=750
Physical memory (bytes) snapshot=398831616
Virtual memory (bytes) snapshot=1765736448
Total committed heap usage (bytes)=354942976
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=5138
File Output Format Counters
Bytes Written=3660
[hadoop@lrts216 bin]$ hdfs dfs -ls /lrts/out
13/12/19 22:26:17 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Found 2 items
-rw-r--r-- 2 hadoop supergroup 0 2013-12-19 22:25 /lrts/out/_SUCCESS
-rw-r--r-- 2 hadoop supergroup 3660 2013-12-19 22:25 /lrts/out/part-r-00000
[hadoop@lrts216 bin]$ hdfs dfs -cat /lrts/out/part-r-00000
13/12/19 22:27:30 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
"%1" 2
"%HADOOP_BIN_PATH:~-1%" 1
"--config" 2
"AS 1
"License"); 1
"\" 1
%* 2
%1 1
%1, 1

%2 1

安装参考：

http://www.yongbok.net/blog/how-to-install-hadoop-2-2-0-pseudo-distributed-mode/

http://hadoop.apache.org/docs/r2.2.0/hadoop-project-dist/hadoop-common/ClusterSetup.html

由于我使用的OS是centos 64位的，所以其中出了些问题，需要自行编译hadoop。

参考资料如下：

http://blog.csdn.net/w13770269691/article/details/16883663

http://blog.csdn.net/bamuta/article/details/13506843

http://blog.csdn.net/lalaguozhe/article/details/10580727

http://hadoop.apache.org/docs/r2.2.0/hadoop-project-dist/hadoop-common/NativeLibraries.html

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