hive--UDF、UDAF

1、UDF

package com.example.hive.udf;

import org.apache.hadoop.hive.ql.exec.UDF;
import org.apache.hadoop.io.Text;

public final class Lower extends UDF {
  public Text evaluate(final Text s) {
    if (s == null) { return null; }
    return new Text(s.toString().toLowerCase());
  }
}

add jar my_jar.jar;

create temporary function my_lower as 'com.example.hive.udf.Lower';

主要描述了实现一个udf的过程，首先自然是实现一个UDF函数，然后编译为jar并加入到hive的classpath中，最后创建一个临时变量名字让hive中调用。

2、UDAF

package org.apache.hadoop.hive.contrib.udaf.example;

import org.apache.hadoop.hive.ql.exec.UDAF;
import org.apache.hadoop.hive.ql.exec.UDAFEvaluator;

/**
 * This is a simple UDAF that calculates average.
 *
 * It should be very easy to follow and can be used as an example for writing
 * new UDAFs.
 *
 * Note that Hive internally uses a different mechanism (called GenericUDAF) to
 * implement built-in aggregation functions, which are harder to program but
 * more efficient.
 *
 */
public final class UDAFExampleAvg extends UDAF {

  /**
   * The internal state of an aggregation for average.
   *
   * Note that this is only needed if the internal state cannot be represented
   * by a primitive.
   *
   * The internal state can also contains fields with types like
   * ArrayList<String> and HashMap<String,Double> if needed.
   */
  public static class UDAFAvgState {
    private long mCount;
    private double mSum;
  }

  /**
   * The actual class for doing the aggregation. Hive will automatically look
   * for all internal classes of the UDAF that implements UDAFEvaluator.
   */
  public static class UDAFExampleAvgEvaluator implements UDAFEvaluator {

    UDAFAvgState state;

    public UDAFExampleAvgEvaluator() {
      super();
      state = new UDAFAvgState();
      init();
    }

    /**
     * Reset the state of the aggregation.
     */
    public void init() {
      state.mSum = 0;
      state.mCount = 0;
    }

    /**
     * Iterate through one row of original data.
     *
     * The number and type of arguments need to the same as we call this UDAF
     * from Hive command line.
     *
     * This function should always return true.
     */
    public boolean iterate(Double o) {
      if (o != null) {
        state.mSum += o;
        state.mCount++;
      }
      return true;
    }

    /**
     * Terminate a partial aggregation and return the state. If the state is a
     * primitive, just return primitive Java classes like Integer or String.
     */
    public UDAFAvgState terminatePartial() {
      // This is SQL standard - average of zero items should be null.
      return state.mCount == 0 ? null : state;
    }

    /**
     * Merge with a partial aggregation.
     *
     * This function should always have a single argument which has the same
     * type as the return value of terminatePartial().
     */
    public boolean merge(UDAFAvgState o) {
      if (o != null) {
        state.mSum += o.mSum;
        state.mCount += o.mCount;
      }
      return true;
    }

    /**
     * Terminates the aggregation and return the final result.
     */
    public Double terminate() {
      // This is SQL standard - average of zero items should be null.
      return state.mCount == 0 ? null : Double.valueOf(state.mSum
          / state.mCount);
    }
  }

  private UDAFExampleAvg() {
    // prevent instantiation
  }

}

关于UDAF开发注意点：

1.需要import org.apache.hadoop.hive.ql.exec.UDAF以及org.apache.hadoop.hive.ql.exec.UDAFEvaluator,这两个包都是必须的

2.函数类需要继承UDAF类，内部类Evaluator实现UDAFEvaluator接口

3.Evaluator需要实现 init、iterate、terminatePartial、merge、terminate这几个函数

1）init函数类似于构造函数，用于UDAF的初始化

2）iterate接收传入的参数，并进行内部的轮转。其返回类型为boolean

3）terminatePartial无参数，其为iterate函数轮转结束后，返回乱转数据，iterate和terminatePartial类似于hadoop的Combiner

4）merge接收terminatePartial的返回结果，进行数据merge操作，其返回类型为boolean

5）terminate返回最终的聚集函数结果