Spark：高级排序（二次排序）
为了多维的排序，需要考虑多个条件，这要求我们自定义key
1 23
3 22
3 31
1 12
2 11
4 45二、使用java实现
2.1、自定义key
使用scala.math.Ordered接口,实现Serializable接口
package com.chb.sparkDemo.secondarySort;
import java.io.Serializable;
import scala.math.Ordered;
/**
* Spark 二次排序自定义key
* 使用scala.math.Ordered接口
* @author 12285
*/
public class MyKey implements Ordered, Serializable{
private int firstKey;
private int secondKey;
public MyKey(int firstKey, int secondKey) {
super();
this.firstKey = firstKey;
this.secondKey = secondKey;
}
public int getFirstKey() {
return firstKey;
}
public int getSecondKey() {
return secondKey;
}
public void setFirstKey(int firstKey) {
this.firstKey = firstKey;
}
public void setSecondKey(int secondKey) {
this.secondKey = secondKey;
}
public boolean $greater(MyKey other) {
if (this.getFirstKey() > other.getFirstKey()) {
return true;
}else if(this.getFirstKey() == other.getFirstKey() && this.getSecondKey() > other.getSecondKey()){
return true;
}else {
return false;
}
}
public boolean $greater$eq(MyKey other) {
if ($greater(other) || this.getFirstKey()==other.getFirstKey() && this.getSecondKey() == other.getSecondKey()) {
return true;
}
return false;
}
public boolean $less(MyKey other) {
if (this.getFirstKey() < other.getFirstKey()) {
return true;
}else if(this.getFirstKey() == other.getFirstKey() && this.getSecondKey() < other.getSecondKey()){
return true;
}else {
return false;
}
}
public boolean $less$eq(MyKey other) {
if ($less(other) || this.getFirstKey()==other.getFirstKey() && this.getSecondKey() == other.getSecondKey()) {
return true;
}
return false;
}
public int compare(MyKey other) {
if (this.getFirstKey() != other.getFirstKey()) {
return this.getFirstKey()-other.getFirstKey();
}else {
return this.getSecondKey() - other.getSecondKey();
}
}
public int compareTo(MyKey other) {
if (this.getFirstKey() != other.getFirstKey()) {
return this.getFirstKey()-other.getFirstKey();
}else {
return this.getSecondKey() - other.getSecondKey();
}
}
@Override
public int hashCode() {
final int prime = 31;
int result = 1;
result = prime * result + firstKey;
result = prime * result + secondKey;
return result;
}
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (getClass() != obj.getClass())
return false;
MyKey other = (MyKey) obj;
if (firstKey != other.firstKey)
return false;
if (secondKey != other.secondKey)
return false;
return true;
}
}
2.2、具体实现步骤
第一步: 自定义key 实现scala.math.Ordered接口，和Serializeable接口
第二步：将要进行二次排序的数据加载，按照
第三步：使用sortByKey 基于自定义的key进行二次排序
第四步：去掉排序的key,只保留排序的结果
2.2.1、 第一步: 自定义key 实现scala.math.Ordered接口，和Serializeable接口
JavaPairRDD mykeyPairs = lines.mapToPair(new PairFunction() {
private static final long serialVersionUID = 1L;
public Tuple2 call(String line) throws Exception {
int firstKey = Integer.valueOf(line.split(" ")[0]);
int secondKey = Integer.valueOf(line.split(" ")[1]);
MyKey mykey = new MyKey(firstKey, secondKey);
return new Tuple2(mykey, line);
}
}); 2.2.2、第三步：使用sortByKey 基于自定义的key进行二次排序
JavaPairRDD sortPairs = mykeyPairs.sortByKey();
2.2.3、第四步：去掉排序的key,只保留排序的结果
JavaRDD result = sortPairs.map(new Function, String>() {
private static final long serialVersionUID = 1L;
public String call(Tuple2 tuple) throws Exception {
return tuple._2;//line
}
});
//打印排序好的结果
result.foreach(new VoidFunction() {
private static final long serialVersionUID = 1L;
public void call(String line) throws Exception {
System.out.println(line);
}
}); 三、完整代码
package com.chb.sparkDemo.secondarySort;
import io.netty.handler.codec.http.HttpContentEncoder.Result;
import java.awt.image.RescaleOp;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.Function;
import org.apache.spark.api.java.function.PairFunction;
import org.apache.spark.api.java.function.VoidFunction;
import scala.Tuple2;
/**
* Spark二次排序的具体实现步骤：
* 第一步: 自定义key 实现scala.math.Ordered接口，和Serializeable接口
* 第二步：将要进行二次排序的数据加载，按照格式的RDD
* 第三步：使用sortByKey 基于自定义的key进行二次排序
* 第四步：去掉排序的key,只保留排序的结果
* @author 12285
*
*/
public class SecordSortTest {
public static void main(String[] args) {
SparkConf conf = new SparkConf().setMaster("local").setAppName("WordCount");
//内部实际调用的SparkContext
JavaSparkContext jsc = new JavaSparkContext(conf);
//读取文件，将每行数据转换为
JavaRDD lines = jsc.textFile("C:\\Users\\12285\\Desktop\\test");//hadoopRDD
//第二步：将要进行二次排序的数据加载，按照格式的RDD
JavaPairRDD mykeyPairs = lines.mapToPair(new PairFunction() {
private static final long serialVersionUID = 1L;
public Tuple2 call(String line) throws Exception {
int firstKey = Integer.valueOf(line.split(" ")[0]);
int secondKey = Integer.valueOf(line.split(" ")[1]);
MyKey mykey = new MyKey(firstKey, secondKey);
return new Tuple2(mykey, line);
}
});
//第三步：使用sortByKey 基于自定义的key进行二次排序
JavaPairRDD sortPairs = mykeyPairs.sortByKey();
//第四步：去掉排序的key,只保留排序的结果
JavaRDD result = sortPairs.map(new Function, String>() {
private static final long serialVersionUID = 1L;
public String call(Tuple2 tuple) throws Exception {
return tuple._2;//line
}
});
//打印排序好的结果
result.foreach(new VoidFunction() {
private static final long serialVersionUID = 1L;
public void call(String line) throws Exception {
System.out.println(line);
}
});
}
}
结果：
1 12
1 23
2 11
3 22
3 31
4 45 四、使用scala实现
4.1、自定义key
class SecordSortKey(val firstKey: Int, val secondKey: Int)extends Ordered[SecordSortKey] with Serializable{
override def compare(that: SecordSortKey):Int = {
if(this.firstKey != that.firstKey) {
this.firstKey - that.firstKey
}else {
this.secondKey - that.secondKey
}
}
}4.2、具体实现
import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
object SecordSortTest {
def main(args: Array[String]): Unit = {
val conf = new SparkConf().setMaster("local[2]").setAppName("SecordSort")
val sc = new SparkContext(conf);
val lines = sc.textFile("C:\\Users\\12285\\Desktop\\test");
//第二步：将要进行二次排序的数据加载，按照格式的RDD
val pairSortKey = lines.map { line => (
new SecordSortKey(line.split(" ")(0).toInt, line.split(" ")(1).toInt),
line
) };
//第三步：使用sortByKey 基于自定义的key进行二次排序
val sortPair = pairSortKey.sortByKey(false);
val sortResult = sortPair.map(line=>line._2);
sortResult.collect().foreach { x => print(x) };
}
} 原文参考：https://blog.csdn.net/sundujing/article/details/51399606