Hadoop自定义类型处理手机上网日志
package mapreduce;import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.Writable;
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.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.mapreduce.lib.partition.HashPartitioner;
public>
static final String INPUT_PATH = "hdfs://chaoren:9000/wlan";//wlan是个文件夹，日志文件放在/wlan目录下
static final String OUT_PATH = "hdfs://chaoren:9000/out";
public static void main(String[] args) throws Exception {
final Job job = new Job(new Configuration(),
KpiApp.class.getSimpleName());
// 1.1 指定输入文件路径
FileInputFormat.setInputPaths(job, INPUT_PATH);
// 指定哪个类用来格式化输入文件
job.setInputFormatClass(TextInputFormat.class);
// 1.2指定自定义的Mapper类
job.setMapperClass(MyMapper.class);
// 指定输出<k2,v2>的类型
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(KpiWritable.class);
// 1.3 指定分区类
job.setPartitionerClass(HashPartitioner.class);
job.setNumReduceTasks(1);
// 1.4 TODO 排序、分区
// 1.5 TODO （可选）归约
// 2.2 指定自定义的reduce类
job.setReducerClass(MyReducer.class);
// 指定输出<k3,v3>的类型
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(KpiWritable.class);
// 2.3 指定输出到哪里
FileOutputFormat.setOutputPath(job, new Path(OUT_PATH));
// 设定输出文件的格式化类
job.setOutputFormatClass(TextOutputFormat.class);
// 把代码提交给JobTracker执行
job.waitForCompletion(true);
}
static>
protected void map(
LongWritable key,
Text value,
org.apache.hadoop.mapreduce.Mapper<LongWritable, Text, Text, KpiWritable>.Context context)
throws IOException, InterruptedException {
final String[] splited = value.toString().split("\t");
final String msisdn = splited;
final Text k2 = new Text(msisdn);
final KpiWritable v2 = new KpiWritable(splited, splited,
splited, splited);
context.write(k2, v2);
};
}
static>
Reducer<Text, KpiWritable, Text, KpiWritable> {
/**
* @param k2
* 表示整个文件中不同的手机号码
* @param v2s
* 表示该手机号在不同时段的流量的集合
*/
protected void reduce(
Text k2,
java.lang.Iterable<KpiWritable> v2s,
org.apache.hadoop.mapreduce.Reducer<Text, KpiWritable, Text, KpiWritable>.Context context)
throws IOException, InterruptedException {
long upPackNum = 0L;
long downPackNum = 0L;
long upPayLoad = 0L;
long downPayLoad = 0L;
for (KpiWritable kpiWritable : v2s) {
upPackNum += kpiWritable.upPackNum;
downPackNum += kpiWritable.downPackNum;
upPayLoad += kpiWritable.upPayLoad;
downPayLoad += kpiWritable.downPayLoad;
}
final KpiWritable v3 = new KpiWritable(upPackNum + "", downPackNum
+ "", upPayLoad + "", downPayLoad + "");
context.write(k2, v3);
};
}
}
>
long upPackNum;
long downPackNum;
long upPayLoad;
long downPayLoad;
public KpiWritable() {
}
public KpiWritable(String upPackNum, String downPackNum, String upPayLoad,
String downPayLoad) {
this.upPackNum = Long.parseLong(upPackNum);
this.downPackNum = Long.parseLong(downPackNum);
this.upPayLoad = Long.parseLong(upPayLoad);
this.downPayLoad = Long.parseLong(downPayLoad);
}
public void readFields(DataInput in) throws IOException {
this.upPackNum = in.readLong();
this.downPackNum = in.readLong();
this.upPayLoad = in.readLong();
this.downPayLoad = in.readLong();
}
public void write(DataOutput out) throws IOException {
out.writeLong(upPackNum);
out.writeLong(downPackNum);
out.writeLong(upPayLoad);
out.writeLong(downPayLoad);
}
@Override
public String toString() {
return upPackNum + "\t" + downPackNum + "\t" + upPayLoad + "\t"
+ downPayLoad;
}
}
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