具有混合数据源的MapReduce作业:HBase表和HDFS文件

Question

我需要实现一个MR作业,它可以访问HBase表和HDFS文件中的数据.例如,映射器从HBase表和HDFS文件中读取数据,这些数据共享相同的主键但具有不同的模式.然后,reducer将所有列(来自HBase表和HDFS文件)连接在一起.

我尝试在线查找,无法找到使用此类混合数据源运行MR作业的方法.MultipleInputs似乎只适用于多个HDFS数据源.如果您有任何想法,请告诉我.示例代码会很棒.

Answer 1

经过几天的调查(并从HBase用户邮件列表中获得帮助),我终于想出了如何做到这一点.这是源代码:

public class MixMR {

public static class Map extends Mapper<Object, Text, Text, Text> {

    public void map(Object key, Text value, Context context) throws IOException,   InterruptedException {
        String s = value.toString();
        String[] sa = s.split(",");
        if (sa.length == 2) {
            context.write(new Text(sa[0]), new Text(sa[1]));
        }

    }

}

public static class TableMap extends TableMapper<Text, Text>  {
    public static final byte[] CF = "cf".getBytes();
    public static final byte[] ATTR1 = "c1".getBytes();

    public void map(ImmutableBytesWritable row, Result value, Context context) throws IOException, InterruptedException {

        String key = Bytes.toString(row.get());
        String val = new String(value.getValue(CF, ATTR1));

        context.write(new Text(key), new Text(val));
    }
}


public static class Reduce extends Reducer  <Object, Text, Object, Text> {
    public void reduce(Object key, Iterable<Text> values, Context context)
            throws IOException, InterruptedException {
        String ks = key.toString();
        for (Text val : values){
            context.write(new Text(ks), val);
        }

    }
}

public static void main(String[] args) throws Exception {
Path inputPath1 = new Path(args[0]);
    Path inputPath2 = new Path(args[1]);
    Path outputPath = new Path(args[2]);

    String tableName = "test";

    Configuration config = HBaseConfiguration.create();
    Job job = new Job(config, "ExampleRead");
    job.setJarByClass(MixMR.class);     // class that contains mapper

    Scan scan = new Scan();
    scan.setCaching(500);        // 1 is the default in Scan, which will be bad for MapReduce jobs
    scan.setCacheBlocks(false);  // don't set to true for MR jobs
    scan.addFamily(Bytes.toBytes("cf"));

    TableMapReduceUtil.initTableMapperJob(
            tableName,        // input HBase table name
              scan,             // Scan instance to control CF and attribute selection
              TableMap.class,   // mapper
              Text.class,             // mapper output key
              Text.class,             // mapper output value
              job);


    job.setReducerClass(Reduce.class);    // reducer class
    job.setOutputFormatClass(TextOutputFormat.class);   


    // inputPath1 here has no effect for HBase table
    MultipleInputs.addInputPath(job, inputPath1, TextInputFormat.class, Map.class);
    MultipleInputs.addInputPath(job, inputPath2,  TableInputFormat.class, TableMap.class);

    FileOutputFormat.setOutputPath(job, outputPath); 

    job.waitForCompletion(true);
}

}