取最大的前三个数字
top.txt
1、SortByKey
1)基于java
package cn.spark.study.core;
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 scala.Tuple2;
import java.util.List;
public class Top3 {
public static void main(String[] args) {
SparkConf conf = new SparkConf()
.setMaster("local")
.setAppName("Top3");
JavaSparkContext sc = new JavaSparkContext(conf);
JavaRDD<String> lines = sc.textFile("E:\\ziliao\\Spark\\node\\shuju\\top.txt");
JavaPairRDD<Integer, Integer> numbers = lines.mapToPair(new PairFunction<String, Integer, Integer>() {
@Override
public Tuple2<Integer, Integer> call(String s) throws Exception {
return new Tuple2<Integer, Integer>(Integer.parseInt(s), 1);
}
});
JavaPairRDD<Integer, Integer> sorted = numbers.sortByKey(false);
JavaRDD<Integer> map = sorted.map(new Function<Tuple2<Integer, Integer>, Integer>() {
@Override
public Integer call(Tuple2<Integer, Integer> Tuple2) throws Exception {
return Tuple2._1;
}
});
List<Integer> take = map.take(3);
for (Integer e: take){
System.out.println(e);
}
}
}
1)基于scala
package cn.spark.study.core
import org.apache.spark.rdd.RDD
import org.apache.spark.{SparkConf, SparkContext}
object Top3 {
def main(args: Array[String]): Unit = {
val conf: SparkConf = new SparkConf()
.setMaster("local")
.setAppName("Top3")
val sc= new SparkContext(conf)
val lines: RDD[String] = sc.textFile("E:\\ziliao\\Spark\\node\\shuju\\top.txt")
//注意numPartitions的设置,注意是全局排序还是每个分区排序
val numTake3: Array[String] = lines.map((_,1)).sortByKey(false,1).map(_._1).take(3)
for (e <- numTake3){
println(e)
}
}
}
2、SortBy
1)基于java
package cn.spark.study.core;
import org.apache.spark.SparkConf;
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.VoidFunction;
public class Top3_SortBy {
public static void main(String[] args) {
SparkConf conf = new SparkConf()
.setMaster("local")
.setAppName("Top3_SortBy");
JavaSparkContext sc = new JavaSparkContext(conf);
JavaRDD<String> lines = sc.textFile("E:\\ziliao\\Spark\\node\\shuju\\top.txt");
JavaRDD<Integer> number = lines.map(new Function<String, Integer>() {
@Override
public Integer call(String s) throws Exception {
return Integer.parseInt(s);
}
});
JavaRDD<Integer> sortBy = number.sortBy(new Function<Integer, Integer>() {
@Override
public Integer call(Integer integer) throws Exception {
return integer;
}
}, false, 1);
List<Integer> take = sortBy.take(3);
for (Integer e: take){
System.out.println(e);
}
}
}
1)基于scala
package cn.spark.study.core
import org.apache.spark.rdd.RDD
import org.apache.spark.{SparkConf, SparkContext}
object Top3_SortBy {
def main(args: Array[String]): Unit = {
val conf: SparkConf = new SparkConf()
.setMaster("local")
.setAppName("Top3_SortBy")
val sc = new SparkContext(conf)
val lines: RDD[String] = sc.textFile("E:\\ziliao\\Spark\\node\\shuju\\top.txt")
val sortByTake3: Array[Int] = lines.map(Integer.parseInt(_)).sortBy((t:Int) => t, false, 1).take(3)
for (e <- sortByTake3){
println(e)
}
}
}