HDFS小文件处理——Mapper处理

处理小文件的时候，可以通过org.apache.hadoop.io.SequenceFile.Writer类将所有文件写出到一个seq文件中。

大致流程如下：

实现代码：

package study.smallfile.sequence_one;

import java.io.IOException;



import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FileStatus;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.BytesWritable;
import org.apache.hadoop.io.IOUtils;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.SequenceFile;
import org.apache.hadoop.io.SequenceFile.CompressionType;
import org.apache.hadoop.io.SequenceFile.Writer;
import org.apache.hadoop.io.SequenceFile.Writer.Option;
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.output.FileOutputFormat;

public class MapperDemo {

    private static final String INPUT_PATH = "hdfs://cluster1/smallfile/blankfile";
    private static final String OUT_PATH = "hdfs://cluster1/smallfile/combined/map";
    static FileSystem fileSystem;

    public void CombinedFile() throws Exception {
        Job job = Job.getInstance();

        job.setJarByClass(MapperDemo.class);
        job.setJobName(MapperDemo.class.getSimpleName());

        // 设置map类
        job.setMapperClass(MapperDemo.CombinedMapper.class);
        // 设置输出
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(BytesWritable.class);
        // 设置reduce任务数量
        job.setNumReduceTasks(0);
        // 设置输入路径
        FileInputFormat.setInputPaths(job, new Path(INPUT_PATH));
        // 检查输出路径
        Path outdir = new Path(OUT_PATH);
        fileSystem = FileSystem.get(job.getConfiguration());
        if (fileSystem.exists(outdir)) {// 如果已经存在删除
            fileSystem.delete(outdir, true);
        }

        // 设置输出路径
        FileOutputFormat.setOutputPath(job, outdir);

        job.waitForCompletion(true);

    }

    static class CombinedMapper extends
            Mapper<LongWritable, Text, Text, BytesWritable> {
        Writer writer = null;
        FileStatus[] files;

        Text outKey = new Text();
        BytesWritable outValue = new BytesWritable();

        FSDataInputStream in;
        byte[] buffer = null;

        @Override
        protected void map(LongWritable key, Text value,
                Mapper<LongWritable, Text, Text, BytesWritable>.Context context)
                throws IOException, InterruptedException {
//            for (FileStatus file : files) {
//                outKey.set(file.getPath().toString());
//
//                in = fileSystem.open(file.getPath());
//                buffer = new byte[(int) file.getLen()];
//                IOUtils.read(in, buffer, 0, buffer.length);
//                outValue.set(new BytesWritable(buffer));
//                writer.append(outKey, outValue);
//            }

        }

        @Override
        protected void cleanup(
                Mapper<LongWritable, Text, Text, BytesWritable>.Context context)
                throws IOException, InterruptedException {
            for (FileStatus file : files) {
                outKey.set(file.getPath().toString());

                in = fileSystem.open(file.getPath());
                buffer = new byte[(int) file.getLen()];
                IOUtils.readFully(in, buffer, 0, buffer.length);
                outValue.set(new BytesWritable(buffer));
                writer.append(outKey, outValue);
            }
            IOUtils.closeStream(writer);
        }

        @Override
        protected void setup(
                Mapper<LongWritable, Text, Text, BytesWritable>.Context context)
                throws IOException, InterruptedException {
            // 输出文件项
            Option fileOption = SequenceFile.Writer.file(new Path(OUT_PATH
                    + "/mapper.seq"));
            // 压缩选项
            Option compressionOption = SequenceFile.Writer
                    .compression(CompressionType.BLOCK);
            // SequeneFile key类型设置
            Option keyClassOption = SequenceFile.Writer.keyClass(Text.class);
            // SequeneFile value类型设置
            Option valueClassOption = SequenceFile.Writer
                    .valueClass(BytesWritable.class);
            // 构建输出流文件
            Configuration conf = new Configuration();
            writer = SequenceFile.createWriter(conf, fileOption,
                    compressionOption, keyClassOption, valueClassOption);
            if (fileSystem == null) {
                fileSystem = FileSystem.get(conf);
            }
            files = fileSystem.listStatus(new Path("hdfs://cluster1/smallfile/logs"));
            
        }
    }
}

注意事项：

　　我原本的逻辑是放到map函数中，将所有文件通过Writer写到HDFS中，但是map在整个mr的执行中被调用的次数是根据输入文件情况确定的，通过控制输入文件的情况，可以通过map函数实现

发现问题：

原本在实现之前，定义了一个FileSystem类型的静态字段，在提交job前已经赋值了，但是，在mapper类中访问到的fileSystem字段，是空值，有知道的大虾，多多指导小弟

SequenceFile介绍：

http://wiki.apache.org/hadoop/SequenceFile

http://www.cnblogs.com/zhenjing/archive/2012/11/02/File-Format.html