Hadoop案例（五）过滤日志及自定义日志输出路径（自定义OutputFormat)

时间：2023-01-17 14:19:08

过滤日志及自定义日志输出路径（自定义OutputFormat）

1.需求分析

过滤输入的log日志中是否包含xyg

（1）包含xyg的网站输出到e:/xyg.log

（2）不包含xyg的网站输出到e:/other.log

2.数据准备

http://www.baidu.com

http://www.google.com

http://cn.bing.com

http://www.xyg.com

http://www.sohu.com

http://www.sina.com

http://www.sin2a.com

http://www.sin2desa.com

http://www.sindsafa.com

log.txt

输出预期：

http://www.xyg.com

xyg.txt

http://cn.bing.com

http://www.baidu.com

http://www.google.com

http://www.sin2a.com

http://www.sin2desa.com

http://www.sina.com

http://www.sindsafa.com

http://www.sohu.com

other.txt

3.代码实现

（1）自定义一个outputformat

package com.xyg.mapreduce.outputformat;

import java.io.IOException;

import org.apache.hadoop.io.NullWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.mapreduce.RecordWriter;

import org.apache.hadoop.mapreduce.TaskAttemptContext;

import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

public class FilterOutputFormat extends FileOutputFormat<Text, NullWritable>{

    @Override

    public RecordWriter<Text, NullWritable> getRecordWriter(TaskAttemptContext job) throws IOException, InterruptedException {

        // 创建一个RecordWriter

        return new FilterRecordWriter(job);

    }

}

（2）具体的写数据RecordWriter

package com.xyg.mapreduce.outputformat;

import java.io.IOException;

import org.apache.hadoop.fs.FSDataOutputStream;

import org.apache.hadoop.fs.FileSystem;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.NullWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.mapreduce.RecordWriter;

import org.apache.hadoop.mapreduce.TaskAttemptContext;

public class FilterRecordWriter extends RecordWriter<Text, NullWritable> {

    FSDataOutputStream atguiguOut = null;

    FSDataOutputStream otherOut = null;

    public FilterRecordWriter(TaskAttemptContext job) {

        // 1 获取文件系统

        FileSystem fs;

        try {

            fs = FileSystem.get(job.getConfiguration());

            // 2 创建输出文件路径

            Path atguiguPath = new Path("e:/xyg.log");

            Path otherPath = new Path("e:/other.log");

            // 3 创建输出流

            atguiguOut = fs.create(atguiguPath);

            otherOut = fs.create(otherPath);

        } catch (IOException e) {

            e.printStackTrace();

        }

    }

    @Override

    public void write(Text key, NullWritable value) throws IOException, InterruptedException {

        // 判断是否包含“xyg”输出到不同文件

        if (key.toString().contains("xyg")) {

            atguiguOut.write(key.toString().getBytes());

        } else {

            otherOut.write(key.toString().getBytes());

        }

    }

    @Override

    public void close(TaskAttemptContext context) throws IOException, InterruptedException {

        // 关闭资源

        if (atguiguOut != null) {

            atguiguOut.close();

        }

        if (otherOut != null) {

            otherOut.close();

        }

    }

}

（3）编写FilterMapper

package com.xyg.mapreduce.outputformat;

import java.io.IOException;

import org.apache.hadoop.io.LongWritable;

import org.apache.hadoop.io.NullWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.mapreduce.Mapper;

public class FilterMapper extends Mapper<LongWritable, Text, Text, NullWritable>{

    Text k = new Text();

    @Override

    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {

        // 1 获取一行

        String line = value.toString();

        k.set(line);

        // 3 写出

        context.write(k, NullWritable.get());

    }

}

（4）编写FilterReducer

package com.xyg.mapreduce.outputformat;

import java.io.IOException;

import org.apache.hadoop.io.NullWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.mapreduce.Reducer;

public class FilterReducer extends Reducer<Text, NullWritable, Text, NullWritable> {

    @Override

    protected void reduce(Text key, Iterable<NullWritable> values, Context context) throws IOException, InterruptedException {

        String k = key.toString();

        k = k + "\r\n";

        context.write(new Text(k), NullWritable.get());

    }

}

（5）编写FilterDriver

package com.xyg.mapreduce.outputformat;

import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.NullWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.mapreduce.Job;

import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;

import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

public class FilterDriver {

    public static void main(String[] args) throws Exception {

        args = new String[] { "e:/inputoutputformat", "e:/output2" };

        Configuration conf = new Configuration();

        Job job = Job.getInstance(conf);

        job.setJarByClass(FilterDriver.class);

        job.setMapperClass(FilterMapper.class);

        job.setReducerClass(FilterReducer.class);

        job.setMapOutputKeyClass(Text.class);

        job.setMapOutputValueClass(NullWritable.class);

        job.setOutputKeyClass(Text.class);

        job.setOutputValueClass(NullWritable.class);

        // 要将自定义的输出格式组件设置到job中

        job.setOutputFormatClass(FilterOutputFormat.class);

        FileInputFormat.setInputPaths(job, new Path(args[]));

        // 虽然我们自定义了outputformat，但是因为我们的outputformat继承自fileoutputformat

        // 而fileoutputformat要输出一个_SUCCESS文件，所以，在这还得指定一个输出目录

        FileOutputFormat.setOutputPath(job, new Path(args[]));

        boolean result = job.waitForCompletion(true);

        System.exit(result ?  : );

    }

}

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