在ubuntu12.04LTS上编译64位hadoop-2.3.0并安装测试 单节点

先看一下安装完之后的版本情况

$ java -version

java version "1.7.0_51"
Java(TM) SE Runtime Environment (build 1.7.0_51-b13)
Java HotSpot(TM) 64-Bit Server VM (build 24.51-b03, mixed mode)

$ hadoop version

Hadoop 2.3.0
Subversion Unknown -r Unknown
Compiled by hduser on 2014-03-01T09:07Z
Compiled with protoc 2.5.0
From source with checksum dfe46336fbc6a044bc124392ec06b85
This command was run using /home/hduser/hadoop/hadoop-2.3.0/share/hadoop/common/hadoop-common-2.3.0.jar

编译hadoop

我基本按照这位大神写的博文一步步做的

http://blog.changecong.com/2013/10/ubuntu-%E7%BC%96%E8%AF%91%E5%AE%89%E8%A3%85-hadoop-2-2-0/

但是当用maven编译hadoop源码时候报错了

$ mvn package -Pdist,native -DskipTests -Dtar

貌似是因为maven的一个plugin：javadoc找不到，我也不是很懂，之前没有用过maven。

就胡乱搜索一把，按照这篇博文的做法http://www.cnblogs.com/lucius/p/3435296.html

修改了maven源为一个国内源，结果就编译成功了。

我的settings.xml中修改的部分。

  <mirrors>
	<mirror>
		<id>nexus-osc</id>
		<mirrorOf>*</mirrorOf>
		<name>Nexusosc</name>
		<url>http://maven.oschina.net/content/groups/public/</url>
	</mirror>
  </mirrors>
  
  <profiles>
	<profile>
		<id>jdk-1.7</id>
		<activation>
			<jdk>1.7</jdk>
		</activation>
		<repositories>
			<repository>
				<id>nexus</id>
				<name>local private nexus</name>
				<url>http://maven.oschina.net/content/groups/public/</url>
				<releases>
					<enabled>true</enabled>
				</releases>
				<snapshots>
					<enabled>false</enabled>
				</snapshots>
			</repository>
	       </repositories>
	       <pluginRepositories>
			<pluginRepository>
				<id>nexus</id>
				<name>local private nexus</name>
				<url>http://maven.oschina.net/content/groups/public/</url>
				<releases>
					<enabled>true</enabled>
				</releases>
				<snapshots>
					<enabled>false</enabled>
				</snapshots>
			</pluginRepository>
	       </pluginRepositories>
	</profile>
  </profiles>

安装配置hadoop

当然要设置一堆环境变量，按照做http://www.cnblogs.com/lucius/p/3435296.html就可以了。

～/.bashrc添加

# hadoop variable settings
export HADOOP_HOME="$HOME/hadoop/hadoop-2.3.0"
export HADOOP_PREFIX=$HADOOP_HOME
export YARN_HOME=$HADOOP_HOME
export HADOOP_MAPRED_HOME=$HADOOP_HOME
export HADOOP_COMMON_HOME=$HADOOP_HOME
export HADOOP_HDFS_HOME=$HADOOP_HOME
export HADOOP_CONF_DIR="$HADOOP_HOME/etc/hadoop/"
export YARN_CONF_DIR=$HADOOP_CONF_DIR
export PATH="$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH"

然后修改etc下的配置文件

hadoop-evn.sh

# The java implementation to use.
export JAVA_HOME=/usr/lib/java/jdk1.7.0_51

core-site.xml

<configuration>
	<property>
		<name>hadoop.tmp.dir</name>
		<value>/home/hduser/hadoop/hadoop-2.3.0/tmp/hadoop-${user.name}</value>
		<description>A base for other temporary directories</description>
	</property>

	<property>
		<name>fs.defaultFS</name>
		<value>hdfs://localhost:9000</value>
	</property>
</configuration>

备注：要在安装目录下新建一个文件夹tmp $ mkdir /home/hduser/hadoop/hadoop-2.3.0/tmp

mapred-site.xml

<configuration>
	<property>
		<name>mapreduce.framework.name</name>
		<value>yarn</value>
	</property>
</configuration>

yarn-site.xml

<configuration>

<!-- Site specific YARN configuration properties -->
	
	<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>

</configuration>

一上来我把mapreduce_shuffle写成了mapreduce.shuffle，结果测试的时候一直卡在如下状态 Tracking UI - UNASSIGNED

14/03/02 21:35:04 INFO client.RMProxy: Connecting to ResourceManager at /0.0.0.0:8032
14/03/02 21:35:05 INFO input.FileInputFormat: Total input paths to process : 1
14/03/02 21:35:05 INFO mapreduce.JobSubmitter: number of splits:1
14/03/02 21:35:05 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1393682087091_0005
14/03/02 21:35:05 INFO impl.YarnClientImpl: Submitted application application_1393682087091_0005
14/03/02 21:35:05 INFO mapreduce.Job: The url to track the job: http://abalone-ubuntu:8088/proxy/application_1393682087091_0005/
14/03/02 21:35:05 INFO mapreduce.Job: Running job: job_1393682087091_0005

就是不往下执行map和reduce阶段，最后发现是因为配置文件写错了，我晕倒。

和这个情况很类似：http://stackoverflow.com/questions/20506992/cant-run-a-mapreduce-job-with-yarn

测试hadoop

1. # 第一次运行前，需要格式化文件系统
	$ hdfs namenode -format

2. # 开启hadoop
	$ start-dfs.sh
	$ start-yarn.sh

3. # 可以在浏览器里查看job的工作情况，URL为
	localhost:8088

4. # 关闭hadoop
	$ stop-yarn.sh
	$ stop-dfs.sh

5. # 对hdfs一些基本操作
	$ hdfs dfs -mkdir /tmp  # make directory
	$ hdfs dfs -copyFromLocal file.txt /tmp  # copy from local file system.
	$ hdfs dfs -ls /tmp  # list content on hdfs

6. # 跑一个自带的测试用例
        $ hadoop jar $HADOOP_HOME/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.3.0.jar pi 2 5
Number of Maps  = 2
Samples per Map = 5
Wrote input for Map #0
Wrote input for Map #1
Starting Job
14/03/02 22:16:52 INFO client.RMProxy: Connecting to ResourceManager at /0.0.0.0:8032
14/03/02 22:16:53 INFO input.FileInputFormat: Total input paths to process : 2
14/03/02 22:16:53 INFO mapreduce.JobSubmitter: number of splits:2
14/03/02 22:16:53 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1393682087091_0006
14/03/02 22:16:53 INFO impl.YarnClientImpl: Submitted application application_1393682087091_0006
14/03/02 22:16:53 INFO mapreduce.Job: The url to track the job: http://abalone-ubuntu:8088/proxy/application_1393682087091_0006/
14/03/02 22:16:53 INFO mapreduce.Job: Running job: job_1393682087091_0006
14/03/02 22:16:59 INFO mapreduce.Job: Job job_1393682087091_0006 running in uber mode : false
14/03/02 22:16:59 INFO mapreduce.Job:  map 0% reduce 0%
14/03/02 22:17:04 INFO mapreduce.Job:  map 100% reduce 0%
14/03/02 22:17:09 INFO mapreduce.Job:  map 100% reduce 100%
14/03/02 22:17:09 INFO mapreduce.Job: Job job_1393682087091_0006 completed successfully
14/03/02 22:17:09 INFO mapreduce.Job: Counters: 49
    File System Counters
        FILE: Number of bytes read=50
        FILE: Number of bytes written=257571
        FILE: Number of read operations=0
        FILE: Number of large read operations=0
        FILE: Number of write operations=0
        HDFS: Number of bytes read=530
        HDFS: Number of bytes written=215
        HDFS: Number of read operations=11
        HDFS: Number of large read operations=0
        HDFS: Number of write operations=3
    Job Counters 
        Launched map tasks=2
        Launched reduce tasks=1
        Data-local map tasks=2
        Total time spent by all maps in occupied slots (ms)=5043
        Total time spent by all reduces in occupied slots (ms)=2761
        Total time spent by all map tasks (ms)=5043
        Total time spent by all reduce tasks (ms)=2761
        Total vcore-seconds taken by all map tasks=5043
        Total vcore-seconds taken by all reduce tasks=2761
        Total megabyte-seconds taken by all map tasks=5164032
        Total megabyte-seconds taken by all reduce tasks=2827264
    Map-Reduce Framework
        Map input records=2
        Map output records=4
        Map output bytes=36
        Map output materialized bytes=56
        Input split bytes=294
        Combine input records=0
        Combine output records=0
        Reduce input groups=2
        Reduce shuffle bytes=56
        Reduce input records=4
        Reduce output records=0
        Spilled Records=8
        Shuffled Maps =2
        Failed Shuffles=0
        Merged Map outputs=2
        GC time elapsed (ms)=72
        CPU time spent (ms)=1700
        Physical memory (bytes) snapshot=693141504
        Virtual memory (bytes) snapshot=3142955008
        Total committed heap usage (bytes)=524288000
    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=236
    File Output Format Counters 
        Bytes Written=97
Job Finished in 16.452 seconds
Estimated value of Pi is 3.60000000000000000000

碰到的hadoop报错

1.

$ hadoop jar $HADOOP_HOME/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.3.0.jar wordcount /input/words.txt /output
14/03/02 21:34:15 INFO client.RMProxy: Connecting to ResourceManager at /0.0.0.0:8032
14/03/02 21:34:15 WARN security.UserGroupInformation: PriviledgedActionException as:hduser (auth:SIMPLE) cause:org.apache.hadoop.mapred.FileAlreadyExistsException: Output directory hdfs://localhost:9000/output already exists
org.apache.hadoop.mapred.FileAlreadyExistsException: Output directory hdfs://localhost:9000/output already exists
	at org.apache.hadoop.mapreduce.lib.output.FileOutputFormat.checkOutputSpecs(FileOutputFormat.java:146)

说明指定的输出文件夹/output已经存在，hadoop默认是不会覆盖已有的文件的，所以要把文件夹/output删除或者换一个不存在的文件夹名字。

2.

往hdfs上copy数据的时候报错，说是没有datanode

DataStreamer Exception: org.apache.hadoop.ipc.RemoteException: java.io.IOException: File /tmp/hadoop-Ceylon/mapred/system/job_local_0001/job.jar could only be replicated to 0 nodes, instead of 1

我的做法是将hadoop关闭，然后将文件夹下/home/hduser/hadoop/hadoop-2.3.0/tmp/的内容全部删除，重新启动hadoop。