hbase和mapreduce开发 WordCount
代码:
/**
* hello world by world 测试数据
* @author a
*
*/
public class DefinedMapper extends Mapper<LongWritable, Text, Text, LongWritable>{
@Override
protected void map(LongWritable key, Text value, Mapper<LongWritable, Text, Text, LongWritable>.Context context)
throws IOException, InterruptedException {
long num=1L;
if(null!=value){
String strValue=value.toString();
String arrValue[]=strValue.split(" ");
if(arrValue.length==4){
for(int i=0;i<arrValue.length;i++){
context.write(new Text(arrValue[i].toString()), new LongWritable(num));
}
}
}
}
}
public class DefinedReduce extends TableReducer{
@Override
protected void reduce(Object arg0, Iterable values, Context arg2) throws IOException, InterruptedException {
if(null!=values){
long num=0l;
Iterator<LongWritable> it=values.iterator();
while(it.hasNext()){
LongWritable count=it.next();
num+=Long.valueOf(count.toString());
}
Put put=new Put(String.valueOf(arg0).getBytes());//设置行键
put.add("context".getBytes(), "count".getBytes(), String.valueOf(num).getBytes());
arg2.write(arg0, put);
}
}
}
package com.zhang.hbaseandmapreduce; 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.mapreduce.TableOutputFormat;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; public class HBaseAndMapReduce {
public static void createTable(String tableName){
Configuration conf=HBaseConfiguration.create();
HTableDescriptor htable=new HTableDescriptor(tableName);
HColumnDescriptor hcol=new HColumnDescriptor("context");
try {
HBaseAdmin admin=new HBaseAdmin(conf);
if(admin.tableExists(tableName)){
System.out.println(tableName+" 已经存在");
return;
}
htable.addFamily(hcol);
admin.createTable(htable);
System.out.println(tableName+" 创建成功");
} catch (IOException e) {
e.printStackTrace();
} }
public static void main(String[] args) {
String tableName="workCount";
Configuration conf=new Configuration();
conf.set(TableOutputFormat.OUTPUT_TABLE, tableName);
conf.set("hbase.zookeeper.quorum", "192.168.177.124:2181");
createTable(tableName);
try {
Job job=new Job(conf);
job.setJobName("hbaseAndMapReduce");
job.setJarByClass(HBaseAndMapReduce.class);//jar的运行主类
job.setOutputKeyClass(Text.class);//mapper key的输出类型
job.setOutputValueClass(LongWritable.class);//mapper value的输出类型
job.setMapperClass(DefinedMapper.class);
job.setReducerClass(DefinedReduce.class);
job.setInputFormatClass(org.apache.hadoop.mapreduce.lib.input.TextInputFormat.class);
job.setOutputFormatClass(TableOutputFormat.class);
FileInputFormat.addInputPath(job, new Path("/tmp/dataTest/data.text"));
System.exit(job.waitForCompletion(true) ? 0:1);
} catch (Exception e) {
e.printStackTrace();
} } }
[root@node4 Desktop]# hadoop jar hbaseAndMapR.jar com.zhang.hbaseandmapreduce.HBaseAndMapReduce
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(LongWritable.class);
(1)2017-01-07 06:53:33,493 INFO org.apache.hadoop.yarn.server.nodemanager.containermanager.monitor.ContainersMonitorImpl: Memory usage of ProcessTree 14615 for container-id container_1483797859000_0001_01_000001: 80.9 MB of 2 GB physical memory used; 1.7 GB of 4.2 GB virtual memory used
(2)Detected pause in JVM or host machine (eg GC): pause of approximately 3999ms
(3)AttemptID:attempt_1462439785370_0055_m_000001_0 Timed out after 600 secs
MB of 1 GB physical memory used; 812.3 MB of 2.1 GB virtual memory used
<property>
<name>mapred.task.timeout</name>
<value>180000</value>
</property>
# The maximum amount of heap to use. Default is left to JVM default.
export HBASE_HEAPSIZE=2G
# Uncomment below if you intend to use off heap cache. For example, to allocate 8G of
# offheap, set the value to "8G".
export HBASE_OFFHEAPSIZE=2G


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