本篇先介绍HBase在伪分布式环境下的安装方式,然后将MapReduce编程和HBase结合起来使用,完成WordCount这个例子。
- HBase在伪分布环境下安装
一、 前提条件
已经成功地安装了jdk1.6和hadoop1.2.1。
Jdk1.6+Hadoop1.2.1在伪分布环境下具体的安装方法见:Hadoop1.2.1安装——单节点方式和单机伪分布方式
二、 环境
- VMware® Workstation 10.04
- Ubuntu14.04 32位
- Java JDK 1.6.0
- hadoop1.2.1
- hbase0.94.26
三、 HBase0.94伪分布式下的安装步骤
(1)下载hbase0.94.26的tar包并解压
tar -zxvf hbase-0.94.26.tar.g
(2)去{hbase}/conf目录修改hbase-site.xml
<configuration>
<property>
<name>hbase.rootdir</name>
<value>hdfs://localhost:9000/hbase</value>
<!-- 端口号和ip地址要与hadoop配置参数fs.default.name一致 -->
</property> <property>
<name>hbase.cluster.distributed</name>
<value>true</value>
</property>
<property>
<name>dfs.replication</name>
<value>1</value> (伪分布设置为1)
</property>
</configuration>
(3)去{hbase}/conf目录修改hbase-env.sh文件
export JAVA_HOME=/usr/lib/jvm/{jdk} #jdk安装路径 export HBASE_CLASSPATH=/etc/hadoop export HBASE_MANAGES_ZK=true
(4)让hbase0.94.26支持hadoop1.2.1
hbase0.94.26默认支持的是hadoop1.0.4,我们可以用替换hadoop-core的方式让其支持hadoop1.2.1.
a. 将hadoop主目录下的hadoop-core-1.2.1.jar文件复制到hbase/lib目录下去,将hbase/lib 目录下自带的 hadoop-core-1.0.4.jar文件删除,
b. 再将hadoop/lib目录下的commons-collections-3.2.1.jar和commons-configuration-1.6.jar文件复制到 hbase/lib目录下去
rm /home/u14/hbase-0.94.26/lib/hadoop-core-1.0.4.jar
cp /home/u14/hadoop/hadoop-core-1.2.1.jar /home/u14/hbase-0.94.26/lib
cp /home/u14/hadoop/lib/commons-collections-3.2.1.jar /home/u14/hbase-0.94.26/lib
cp /home/u14/hadoop/lib/commons-configuration-1.6.jar /home/u14/hbase-0.94.26/lib
(5)启动HBase
a. 先启动hadoop
b. 启动Hbase
进入hbase的解压目录下的bin文件夹,执行start-hbase.sh脚本
bin/start-hbase.sh
用jps命令查看相关进程:
SecondaryNameNode
DataNode
HQuorumPeer
TaskTracker
JobTracker
Jps
HRegionServer
HMaster
NameNode
c. 进入shell模式,操作hbase
bin/hbase shell
d. 停止hbase:先停止hbase,再停止hadoop
stop-hbase.sh
stop-all.sh
- 使用Eclipse开发HBase应用程序
a. 在eclipse里新建一个java项目HBase,然后选择项目属性,在Libraries->Add External JARs...,然后选择{hbase}/lib下相关的JAR包,如果只是测试用的话,就简单一点,将所有的JAR选上
b. 在项目HBase下增加一个文件夹conf,将Hbase集群的配置文件hbase-site.xml复制到该目录,然后选择项目属性在Libraries->Add Class Folder,将刚刚增加的conf目录选上。 - 将MapReduce与HBase结合起来完成wordCount例子
在这个例子中,输入文件为:
user/u14/hbasetest/file01: hello world bye world
user/u14/hbasetest/file02: hello hadoop bye hadoop
程序思想:程序首先从文件中收集数据,在shuffle完成之后进行统计并计算,最后将计算结果存储到hbase中。
import java.io.IOException; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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.mapreduce.TableOutputFormat;
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.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat; public class WordCountHBase {
public static class Map extends Mapper<LongWritable,Text, Text, IntWritable>{
private IntWritable i = new IntWritable(1);
public void map(LongWritable key, Text value, Context context)
throws IOException, InterruptedException{
String s[] = value.toString().trim().split(" ");
for(String m: s){
context.write(new Text(m), i);
}
}
} public static class Reduce extends TableReducer<Text, IntWritable, NullWritable>{
public void reduce(Text key, Iterable<IntWritable> values, Context context)
throws IOException, InterruptedException{
int sum = 0;
for(IntWritable i: values){
sum += i.get();
}
Put put = new Put(Bytes.toBytes(key.toString())); //put实例化,每一个词存一行
put.add(Bytes.toBytes("content"),Bytes.toBytes("count"),
Bytes.toBytes(String.valueOf(sum))); //列族为content,列修饰符为count,列值为数值
context.write(NullWritable.get(), put);
}
} public static void createHBaseTable(String tableName) throws IOException{
HTableDescriptor htd = new HTableDescriptor(tableName);
HColumnDescriptor col = new HColumnDescriptor("content");
htd.addFamily(col);
HBaseConfiguration config = new HBaseConfiguration();
HBaseAdmin admin = new HBaseAdmin(config);
if(admin.tableExists(tableName)){
System.out.println("table exists, trying recreate table!");
admin.disableTable(tableName);
admin.deleteTable(tableName);
}
System.out.println("create new table: "+ tableName);
admin.createTable(htd);
} public static void main(String args[]) throws Exception{
String tableName = "wordcountH";
Configuration conf = new Configuration();
conf.set(TableOutputFormat.OUTPUT_TABLE, tableName);
createHBaseTable(tableName);
Job job = new Job(conf, "WordCountHbase");
job.setJarByClass(WordCountHBase.class);
job.setNumReduceTasks(3);
job.setMapperClass(Map.class);
job.setReducerClass(Reduce.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
job.setInputFormatClass(TextInputFormat.class);
job.setOutputFormatClass(TableOutputFormat.class);
FileInputFormat.addInputPath(job, new Path(args[0]));
System.exit(job.waitForCompletion(true)?0:1);
}
}
程序成功运行后,通过Hbase Shell检查输出结果:
aaarticlea/png;base64,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" 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