Hadoop实战:reduce端实现Join
项目描述
现在假设有两个数据集:气象站数据库和天气记录数据库,并考虑如何合二为一。一个典型的查询是:输出气象站的历史信息,同时各行记录也包含气象站的元数据信息。
气象站和天气记录合并之后的示意图如下所示。
测试数据
启动Hadoop集群,然后在hdfs中创建join文件夹用于存放测试数据station.txt和records.txt,他们分别代表气象站数据库和天气记录数据库。
项目代码
JoinStationMapper.java
package com.hadoop.Join; import java.io.IOException; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Mapper; /** * @author Zimo * */ public class JoinStationMapper extends Mapper<LongWritable,Text,TextPair,Text> { protected void map(LongWritable key,Text value,Context context) throws IOException,InterruptedException { String line = value.toString(); String[] arr = line.split("\\s+");//解析气象站数据 int length = arr.length; if(length==2) {//满足这种数据格式 //key=气象站id value=气象站名称 System.out.println("station="+arr[0]+"0"); context.write(new TextPair(arr[0],"0"),new Text(arr[1])); } } }
JoinRecordMapper.java
package com.hadoop.Join; import java.io.IOException; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Mapper; /** * @author Zimo * */ public class JoinRecordMapper extends Mapper<LongWritable,Text,TextPair,Text> { protected void map(LongWritable key,Text value,Context context) throws IOException,InterruptedException { String line = value.toString(); String[] arr = line.split("\\s+",2);//解析天气记录数据 int length = arr.length; if(length==2){ //key=气象站id value=天气记录数据 context.write(new TextPair(arr[0],"1"),new Text(arr[1])); } } }
TextPair.java
package com.hadoop.Join; import java.io.*; import org.apache.hadoop.io.Text; import org.apache.hadoop.io.WritableComparable; /** * @author Zimo * */ public class TextPair implements WritableComparable<TextPair> { private Text first; //Text 类型的实例变量first private Text second;//Text 类型的实例变量second public TextPair() //无参构造方法 { set(new Text(),new Text()); } public TextPair(String first,String second) // Sting类型参数的构造方法 { set(new Text(first),new Text(second)); } public TextPair(Text first,Text second) // Text类型参数的构造方法 { set(first,second); } public void set(Text first,Text second) //set方法 { this.first=first; this.second=second; } public Text getFirst() //getFirst方法 { return first; } public Text getSecond() //getSecond方法 { return second; } //将对象转换为字节流并写入到输出流out中 @Override //------------ 序列化 public void write(DataOutput out) throws IOException //write方法 { first.write(out); second.write(out); } //从输入流in中读取字节流反序列化为对象 @Override //------------反 序列化 public void readFields(DataInput in) throws IOException //readFields方法 { first.readFields(in); second.readFields(in); } @Override public int hashCode() //在mapreduce中,通过hashCode来选择reduce分区 { return first.hashCode() *163+second.hashCode(); } @Override public boolean equals(Object o) //equals方法,这里是两个对象的内容之间比较 { if (o instanceof TextPair) { TextPair tp=(TextPair) o; return first.equals(tp.first) && second.equals(tp.second); } return false; } @Override public String toString() //toString方法 { return first +"\t"+ second; } @Override public int compareTo(TextPair o) { // TODO Auto-generated method stub if(!first.equals(o.first)) { return first.compareTo(o.first); } else if(!second.equals(o.second)) { return second.compareTo(o.second); } return 0; } }
JoinReducer.java
package com.hadoop.Join; import java.io.IOException; import java.util.Iterator; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Reducer; /** * @author Zimo * */ public class JoinReducer extends Reducer< TextPair,Text,Text,Text> { protected void reduce(TextPair key, Iterable< Text> values,Context context) throws IOException,InterruptedException { Iterator< Text> iter = values.iterator(); Text stationName = new Text(iter.next());//气象站名称 while(iter.hasNext()){ Text record = iter.next();//天气记录的每条数据 Text outValue = new Text(stationName.toString()+"\t"+record.toString()); context.write(key.getFirst(),outValue); } } }
JoinRecordWithStationName.java
package com.hadoop.Join; import java.io.InputStream; import org.apache.hadoop.util.Tool; import java.io.OutputStream; import java.util.Set; import javax.lang.model.SourceVersion; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.conf.Configured; import org.apache.hadoop.fs.FileSystem; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.Text; import org.apache.hadoop.io.WritableComparable; import org.apache.hadoop.io.WritableComparator; import org.apache.hadoop.mapreduce.Job; import org.apache.hadoop.mapreduce.Partitioner; import org.apache.hadoop.mapreduce.lib.input.MultipleInputs; import org.apache.hadoop.mapreduce.lib.input.TextInputFormat; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import org.apache.hadoop.util.ToolRunner; /** * @author Zimo * */ public class JoinRecordWithStationName extends Configured implements Tool { public static class KeyPartitioner extends Partitioner< TextPair,Text> { public int getPartition(TextPair key,Text value,int numPartitions) { return (key.getFirst().hashCode()&Integer.MAX_VALUE) % numPartitions; } } public static class GroupingComparator extends WritableComparator { protected GroupingComparator() { super(TextPair.class,true); } @Override public int compare(WritableComparable w1,WritableComparable w2) { TextPair ip1=(TextPair) w1; TextPair ip2=(TextPair) w2; Text l=ip1.getFirst(); Text r=ip2.getFirst(); return l.compareTo(r); } } public int run(String[] args) throws Exception { Configuration conf = new Configuration();// 读取配置文件 Path mypath=new Path(args[2]); FileSystem hdfs=mypath.getFileSystem(conf); if (hdfs.isDirectory(mypath)) { hdfs.delete(mypath,true); } Job job = Job.getInstance(conf,"join");// 新建一个任务 job.setJarByClass(JoinRecordWithStationName.class);// 主类 Path recordInputPath = new Path(args[0]);//天气记录数据源,这里是牵扯到多路径输入和多路径输出的问题。默认是从args[0]开始 Path stationInputPath = new Path(args[1]);//气象站数据源 Path outputPath = new Path(args[2]);//输出路径 //若只有一个输入和一个输出,则输入是args[0],输出是args[1]。 //若有两个输入和一个输出,则输入是args[0]和args[1],输出是args[2] MultipleInputs.addInputPath(job,recordInputPath,TextInputFormat.class,JoinRecordMapper.class);//读取天气记录Mapper MultipleInputs.addInputPath(job,stationInputPath,TextInputFormat.class,JoinStationMapper.class);//读取气象站Mapper FileOutputFormat.setOutputPath(job,outputPath); job.setReducerClass(JoinReducer.class);// Reducer job.setNumReduceTasks(2); job.setPartitionerClass(KeyPartitioner.class);//自定义分区 job.setGroupingComparatorClass(GroupingComparator.class);//自定义分组 job.setMapOutputKeyClass(TextPair.class); job.setMapOutputValueClass(Text.class); job.setOutputKeyClass(Text.class); job.setOutputValueClass(Text.class); return job.waitForCompletion(true)?0:1; } public static void main(String[] args) throws Exception { String[] args0={"hdfs://centpy:9000/join/records.txt" ,"hdfs://centpy:9000/join/station.txt" ,"hdfs://centpy:9000/join/out" }; int exitCode=ToolRunner.run( new JoinRecordWithStationName(), args0); System.exit(exitCode); } }
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