自定义分区

通过简单例子了解partition分区类的重写方法

分区是在MR的过程中进行的,属于Shuffle阶段

但是在Job端不要忘记进行调用:job.setPartitionerClass(xxx.class)

按照年龄分区:

class AgePartitioner extends Partitioner {

    @Override
    public int getPartition(MyComparable key, NullWritable value, int numPartitions) {
        int partition = 0;
        switch (key.age) {
            case 22:
                partition = 1;
                break;
            case 23:
                partition = 2;
                break;
            case 24:
                partition = 3;
                break;
        }
        return partition;
    }
}

按照数据倾斜分区:

// 自定义分区:在Map阶段给key加上随机后缀,基于后缀返回不同的分区编号
class SkewPartitioner extends Partitioner {

    @Override
    public int getPartition(Text text, IntWritable intWritable, int numPartitions) {
        String key = text.toString();
        int partitions = 0;
        // 只对数据倾斜的key做特殊处理
        if ("hadoop".equals(key.split("_")[0])) {
            switch (key) {
//                case "hadoop_0":
//                    partitions = 0;
//                    break;
                case "hadoop_1":
                    partitions = 1;
                    break;
                case "hadoop_2":
                    partitions = 2;
                    break;
            }
        } else {
            // 正常的key还是按照默认的Hash取余进行分区
            partitions = (key.hashCode() & Integer.MAX_VALUE) % numPartitions;
        }
        return partitions;
    }
}

你可能感兴趣的:(Hadoop,hdfs,hadoop,大数据)