hbase与hdfs之间的数据转换

最新推荐文章于 2025-06-30 17:43:35 发布

搬运工的IT

最新推荐文章于 2025-06-30 17:43:35 发布

阅读量894

点赞数

CC 4.0 BY-SA版权

本文链接：https://blog.youkuaiyun.com/qq_42851004/article/details/82251848

本文围绕MapReduce功能实现展开，涵盖Hbase和Hdfs间数据转换、排序、Top N、去重计数等多种功能。还介绍了从Hbase表读取数据，将统计结果存到另一Hbase表或Hdfs中的操作，包含建表的Java代码及Linux执行方式。

摘要生成于 C知道，由 DeepSeek-R1 满血版支持，前往体验 >

MapReduce功能实现系列：

MapReduce功能实现一---Hbase和Hdfs之间数据相互转换

MapReduce功能实现二---排序

MapReduce功能实现三---Top N

MapReduce功能实现四---小综合(从hbase中读取数据统计并在hdfs中降序输出Top 3)

MapReduce功能实现五---去重(Distinct)、计数(Count)

MapReduce功能实现六---最大值(Max)、求和(Sum)、平均值(Avg)

MapReduce功能实现七---小综合(多个job串行处理计算平均值)

MapReduce功能实现八---分区(Partition)

MapReduce功能实现九---Pv、Uv

MapReduce功能实现十---倒排索引(Inverted Index)

MapReduce功能实现十一---join

一、从Hbase表1中读取数据再把统计结果存到表2

在Hbase中建立相应的表1：

create 'hello','cf'
put 'hello','1','cf:hui','hello world'
put 'hello','2','cf:hui','hello hadoop'
put 'hello','3','cf:hui','hello hive'
put 'hello','4','cf:hui','hello hadoop'
put 'hello','5','cf:hui','hello world'
put 'hello','6','cf:hui','hello world'

java代码：

import java.io.IOException;
import java.util.Iterator;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.HColumnDescriptor;
import org.apache.hadoop.hbase.HTableDescriptor;
import org.apache.hadoop.hbase.client.HBaseAdmin;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.client.Result;
import org.apache.hadoop.hbase.client.Scan;
import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
import org.apache.hadoop.hbase.mapreduce.TableMapper;
import org.apache.hadoop.hbase.mapreduce.TableReducer;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
public class HBaseToHbase {
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
String hbaseTableName1 = "hello";
String hbaseTableName2 = "mytb2";
prepareTB2(hbaseTableName2);
Configuration conf = new Configuration();
Job job = Job.getInstance(conf);
job.setJarByClass(HBaseToHbase.class);
job.setJobName("mrreadwritehbase");
Scan scan = new Scan();
scan.setCaching(500);
scan.setCacheBlocks(false);
TableMapReduceUtil.initTableMapperJob(hbaseTableName1, scan, doMapper.class, Text.class, IntWritable.class, job);
TableMapReduceUtil.initTableReducerJob(hbaseTableName2, doReducer.class, job);
System.exit(job.waitForCompletion(true) ? 1 : 0);
}
public static class doMapper extends TableMapper<Text, IntWritable>{
private final static IntWritable one = new IntWritable(1);
@Override
protected void map(ImmutableBytesWritable key, Result value, Context context) throws IOException, InterruptedException {
String rowValue = Bytes.toString(value.list().get(0).getValue());
context.write(new Text(rowValue), one);
}
}
public static class doReducer extends TableReducer<Text, IntWritable, NullWritable>{
@Override
protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
System.out.println(key.toString());
int sum = 0;
Iterator<IntWritable> haha = values.iterator();
while (haha.hasNext()) {
sum += haha.next().get();
}
Put put = new Put(Bytes.toBytes(key.toString()));
put.add(Bytes.toBytes("mycolumnfamily"), Bytes.toBytes("count"), Bytes.toBytes(String.valueOf(sum)));
context.write(NullWritable.get(), put);
}
}
public static void prepareTB2(String hbaseTableName) throws IOException{
HTableDescriptor tableDesc = new HTableDescriptor(hbaseTableName);
HColumnDescriptor columnDesc = new HColumnDescriptor("mycolumnfamily");
tableDesc.addFamily(columnDesc);
Configuration cfg = HBaseConfiguration.create();
HBaseAdmin admin = new HBaseAdmin(cfg);
if (admin.tableExists(hbaseTableName)) {
System.out.println("Table exists,trying drop and create!");
admin.disableTable(hbaseTableName);
admin.deleteTable(hbaseTableName);
admin.createTable(tableDesc);
} else {
System.out.println("create table: "+ hbaseTableName);
admin.createTable(tableDesc);
}
}
}

在Linux中执行该代码：

[hadoop@h71 q1]$ /usr/jdk1.7.0_25/bin/javac HBaseToHbase.java
[hadoop@h71 q1]$ /usr/jdk1.7.0_25/bin/jar cvf xx.jar HBaseToHbase*class
[hadoop@h71 q1]$ hadoop jar xx.jar HBaseToHbase