Question

我需要在HBase表上运行MapReduce以求和Double个值。我按照HBase documentation。

中的示例进行了操作

最初通过将字符串转换为字节数组（使用HBase的Bytes.toBytes(value)）来存储属性，但现在我需要将它们作为Double来对它们的值求和。对于仅具有正值的列，它给出了正确的总和，但是我的列也有一些负值（在下面的代码中称为diferenca）。

当我运行这个工作时，它给了我一个错误的答案，我注意到它就像Reduce任务正在获取数字的模块，或类似的东西。但是当我调试时，我发现解析的Double对象valor是正确的否定。我不知道造成这种情况的原因......

工作设置：

 job = new Job(hTable.getConfiguration(), "All");
            job.setJarByClass(HBaseQuery.class);
            scan.setCaching(500);
            scan.setCacheBlocks(false);
            TableMapReduceUtil.initTableMapperJob(
                    tabela,        // input table
                    scan,               
                    CalculoTotaisMapper.class,     // mapper class
                    Text.class,         // mapper output key
                    DoubleWritable.class,  // mapper output value
                    job);
            TableMapReduceUtil.initTableReducerJob(
                    tabela,        // output table
                    CalculoTotaisReducer.class,    // reducer class
                    job);
            job.setNumReduceTasks(1);   // at least one, adjust as required

            boolean b = job.waitForCompletion(true);

我的映射器：

public class CalculoTotaisMapper extends TableMapper<Text, DoubleWritable> {

    public static final String[] ATTRS = 
      new String[]{"valortotalprestador", "valortotalconvenio", "diferenca"};


    private Text text = new Text();
    private Logger logger = LoggerFactory.getLogger(CalculoTotaisMapper.class);

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

        Double val = 0.0;
        for (String attr : ATTRS) {
            byte[] valueBytes = value.getValue("hc".getBytes(), attr.getBytes());
            String valueString = Bytes.toString(valueBytes);

            val = Double.parseDouble(valueString);

            text.set(attr);

            context.write(text, new DoubleWritable(val));


        }

    }
}

我的减速机：

public class CalculoTotaisReducer extends TableReducer <Text, DoubleWritable,
                                                   ImmutableBytesWritable> {

    public static final byte[] CF = "qu".getBytes();

    public void reduce(Text key, Iterable<DoubleWritable> values,
       Context context) throws IOException, InterruptedException {
        double i = 0.0;
        for (DoubleWritable val : values) {
            double valor =  val.get();
           i += valor;
        }

        Put put = new Put(Bytes.toBytes("all"));
        put.add(CF, key.getBytes(), Bytes.toBytes(i));

        context.write(null, put);
    }

}

Hbase + Hadoop的MapReduce给出了负值的错误总和

0 个答案: