初学hadoop2.7.1(三)第一个hadoop应用开发

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操作系统:在windows7下使用ubuntu-14.04.3-desktop-amd64
hadoop版本:hadoop-2.7.1

jdk版本:jdk-7u79-linux-x64.tar.gz

eclipse版本:eclipse-jee-mars-R-win32

maven版本:  apache-maven-3.3.9

1.      Hadoop开发环境介绍:

如上图所示,我们可以选择在win中开发,也可以在linux中开发,本地启动Hadoop或者远程调用Hadoop,标配的工具都是Maven和Eclipse。

2.  用Maven构建Hadoop环境

1)     创建自己的workspace开发目录

2)     在workspace目录下用Maven创建一个标准化的Java项目

mvnarchetype:generate -DarchetypeGroupId=org.apache.maven.archetypes-DgroupId=com.myhadoop -DartifactId=myHadoop -DpackageName=org.myhadoop-Dversion=1.0-SNAPSHOT -DinteractiveMode=false

3)     进入项目myHadoop,执行mvn命令生成eclipse工程

mvn clean install

mvn eclipse:eclipse

4)     打开eclipse设置maven

设置installations

设置User Settings

5)     Hadoop工程导入到eclipse

6)     在pom.xml中添加hadoop依赖

注:

很多框架都会依赖jdk中的tools.jar,但是maven仓库中却没有.

如在eclipse+maven编写mapreduce代码,就会报Missing artifact jdk.toos:jdk.toos:jar:1.6

如何解决这个问题呢,只需要在项目的pom.xml 文件中加入以下配置,指定maven去本地寻找 tools.jar、

<dependency>

<groupId>jdk.tools</groupId>

<artifactId>jdk.tools</artifactId>

<version>1.8</version>

<scope>system</scope>

<systemPath>${JAVA_HOME}/lib/tools.jar</systemPath>

3.  开发应用程序

1)     开发HDFS测试程序

package com.myhadoop;import java.io.InputStream;import java.net.URI;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.FSDataOutputStream;import org.apache.hadoop.fs.FileStatus;import org.apache.hadoop.fs.FileSystem;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.IOUtils;publicclass HDFSTest {       publicstaticvoid main(String[] args) throws Exception {        String uri = "hdfs://192.168.248.128:9000/";         Configuration config = newConfiguration();         FileSystem fs = FileSystem.get(URI.create(uri), config);           // 列出hdfs上目录下的所有文件和目录         FileStatus[] statuses = fs.listStatus(new Path("dfs/data/test"));         for (FileStatus status : statuses) {             System.out.println(status);         }         // 在hdfs目录下创建一个文件,并写入一行文本         FSDataOutputStream os = fs.create(new Path("dfs/data/test/test.log"));         os.write("HelloWorld!".getBytes());         os.flush();         os.close();         // 显示在hdfs下指定文件的内容         InputStream is = fs.open(new Path("dfs/data/test/test.log"));         IOUtils.copyBytes(is, System.out, 1024, true);       }}

注:如果出现connect fail 错误,在core-site.xml里修改host为对外ip

<configuration>

  <property>

       <name>fs.defaultFS</name>

       <value>hdfs://192.168.248.128:9000</value>

   </property>

   <property>

       <name>hadoop.tmp.dir</name>

       <value>/home/tongwei/Work/Dev/Hadoop/hadoop-2.7.1/tmp</value>

       <description>A base of other temporarydirectories</description>

  </property>

</configuration>

2)     开发MapReduce测试程序

package com.myhadoop;import java.io.IOException;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.IntWritable;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Job;import org.apache.hadoop.mapreduce.Mapper;import org.apache.hadoop.mapreduce.Reducer;import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;import org.apache.hadoop.util.GenericOptionsParser;public class EventCount {    public static class MyMapper extends Mapper<Object, Text, Text, IntWritable>{          private final static IntWritable one = new IntWritable(1);          private Text event = new Text();             public void map(Object key, Text value, Context context) throws IOException, InterruptedException {              int idx = value.toString().indexOf(" ");              if (idx > 0) {                  String e = value.toString().substring(0, idx);                  event.set(e);                  context.write(event, one);              }          }      }         public static class MyReducer extends Reducer<Text,IntWritable,Text,IntWritable> {          private IntWritable result = new IntWritable();             public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {              int sum = 0;              for (IntWritable val : values) {                  sum += val.get();              }              result.set(sum);              context.write(key, result);          }      }         public static void main(String[] args) throws Exception {          Configuration conf = new Configuration();          String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();          if (otherArgs.length < 2) {              System.err.println("Usage: EventCount <in> <out>");              System.exit(2);          }          Job job = Job.getInstance(conf, "event count");          job.setJarByClass(EventCount.class);          job.setMapperClass(MyMapper.class);          job.setCombinerClass(MyReducer.class);          job.setReducerClass(MyReducer.class);          job.setOutputKeyClass(Text.class);          job.setOutputValueClass(IntWritable.class);          FileInputFormat.addInputPath(job, new Path(otherArgs[0]));          FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));          System.exit(job.waitForCompletion(true) ? 0 : 1);      }  }

运行“mvn package”命令产生jar包myHadoop-1.0-SNAPSHOT.jar,并将jar文件复制到hadoop安装目录下。这里假定我们需要分析几个日志文件中的Event信息来统计各种Event个数,所以创建一下目录和文件。

创建input文件夹

$ mkdir input

在input文件夹里创建我们需要分析的日志文件,

$ sudo vim./input/event.log.1

编辑文件内容:

JOB_NEW ... 

JOB_NEW ... 

JOB_FINISH ... 

JOB_NEW ... 

JOB_FINISH ...

以此类推分别创建event.log.2, event.log.3日志文件,

$ cp ./input/event.log.1 ./input/event.log.2

$ cp ./input/event.log.1 ./input/event.log.3

在dfs/data下创建input文件夹,

$ bin/hadoop fs -mkdir -p ./dfs/data/input

然后把这些文件复制到HDFS上,

$ bin/hdfs dfs -put./input ./dfs/data

$ bin/hadoop fs –put ./input./dfs/data

运行mapreduce作业,

1$ bin/hadoopjar myHadoop-1.0-SNAPSHOT.jar com.myhadoop.EventCount dfs/data/input dfs/data/output

查看执行结果,

$ bin/hadoopfs -cat dfs/data/output/part-r-00000

 

附录:

在eclispse中设置input和output作为传入参数

String input ="hdfs://192.168.248.128:9000/user/tongwei/dfs/data/input";

Stringoutput = "hdfs://192.168.248.128:9000/user/tongwei/dfs/data/output";

运行改程序的时候可能会出现下面错误,

ERROR [org.apache.hadoop.util.Shell]Failed to locate the winutils binary in the hadoop binary path

java.io.IOException:Could not locate executable null\bin\winutils.exe in the Hadoop binaries.

究其原因为程序需要根据HADOOP_HOME找到winutils.exe,由于win机器并没有配置该环境变量,所以程序报null\bin\winutils.exe。

解决方案为:

1.      下载hadoop2.7.1版本的winutils的windows版本

http://download.csdn.net/detail/faq_tong/9413293

2.      Ecplise用64为JDK作为complier解决

NativeIO$Windows.createDirectoryWithMode0(Ljava/lang/String;I)S错误

3.     添加HADOOP_HOME环境变量或用下面代码设置系统属性

System.setProperty("hadoop.home.dir","C:/tongwei/works/myprojects/HadoopEx/tools/hadoop-common-bin-2.7.1");

4.      把hadoop.dll拷贝到windows/system32下解决org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z错误

一切OK,程序运行成功!



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