RCFile读写操作

http://smallboby.iteye.com/blog/1592531

读取RCfile

Job job = new Job();  
    job.setJarByClass(类.class);  
    //设定输入文件为RcFile格式  
    job.setInputFormatClass(RCFileInputFormat.class);    
     //普通输出  
    job.setOutputFormatClass(TextOutputFormat.class);  
     //设置输入路径  
    RCFileInputFormat.addInputPath(job, new Path(srcpath));  
    //MultipleInputs.addInputPath(job, new Path(srcpath), RCFileInputFormat.class);  
     // 输出  
    TextOutputFormat.setOutputPath(job, new Path(respath));  
    // 输出key格式  
    job.setOutputKeyClass(Text.class);    
    //输出value格式  
    job.setOutputValueClass(NullWritable.class);    
    //设置mapper类  
     job.setMapperClass(ReadTestMapper.class);  
            //这里没设置reduce，reduce的操作就是读Text类型文件，因为mapper已经给转换了。                
                code = (job.waitForCompletion(true)) ? 0 : 1;    
      
    // mapper 类        
    pulic class ReadTestMapper extends 
                Mapper {  
              
            @Override  
            protected void map(LongWritable key, BytesRefArrayWritable value, Context context) 
                    throws IOException, InterruptedException {  
                // TODO Auto-generated method stub  
                Text txt = new Text();   
            //因为RcFile行存储和列存储，所以每次进来的一行数据，Value是个列簇，遍历，输出。  
                StringBuffer sb = new StringBuffer();  
                for (int i = 0; i < value.size(); i++) {  
                    BytesRefWritable v = value.get(i);  
                    txt.set(v.getData(), v.getStart(), v.getLength());  
                    if(i==value.size()-1){  
                        sb.append(txt.toString());  
                    }else{  
                        sb.append(txt.toString()+"\t");  
                    }  
                }  
                context.write(new Text(sb.toString()),NullWritable.get());  
            }  
     }

写RCFile

Job job = new Job();  
    Configuration conf = job.getConfiguration();  
//设置每行的列簇数  
    RCFileOutputFormat.setColumnNumber(conf, 4);  
    job.setJarByClass(类.class);  

    FileInputFormat.setInputPaths(job, new Path(srcpath));  
    RCFileOutputFormat.setOutputPath(job, new Path(respath));  

    job.setInputFormatClass(TextInputFormat.class);  
    job.setOutputFormatClass(RCFileOutputFormat.class);  

    job.setMapOutputKeyClass(LongWritable.class);  
    job.setMapOutputValueClass(BytesRefArrayWritable.class);  

    job.setMapperClass(OutPutTestMapper.class);  

    conf.set("date", line.getOptionValue(DATE));  
//设置压缩参数  
    conf.setBoolean("mapred.output.compress", true);  
    conf.set("mapred.output.compression.codec", "org.apache.hadoop.io.compress.GzipCodec");  

    code = (job.waitForCompletion(true)) ? 0 : 1;  

public class OutPutTestMapper 
             extends Mapper {  
@Override  
public void map(LongWritable key, Text value, Context context) 
       throws IOException, InterruptedException {  
    String line = value.toString();  
    String day = context.getConfiguration().get("date");  
    if (!line.equals("")) {  
        String[] lines = line.split(" ", -1);  
        if (lines.length > 3) {  
            String time_temp = lines[1];  
            String times = timeStampDate(time_temp);  
            String d = times.substring(0, 10);  
            if (day.equals(d)) {  
                byte[][] record = {lines[0].getBytes("UTF-8"), 
                                   lines[1].getBytes("UTF-8"),lines[2].getBytes("UTF-8"), 
                                   lines[3].getBytes("UTF-8")};  
                }

                BytesRefArrayWritable bytes = new BytesRefArrayWritable(record.length);  

                for (int i = 0; i < record.length; i++) {  
                    BytesRefWritable cu = new BytesRefWritable(record[i], 0, record[i].length);  
                    bytes.set(i, cu);  
                }  
                context.write(key, bytes);  
            }  
        }  
    }  
}