框架搭建
使用IDEA搭建同时可以写Scala语言和Java语言的Maven项目，步骤：
new--->project
选择Maven项目，不要勾选任何选项，一直next到finish；
pom.xml如下：
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.tao</groupId>
<artifactId>spark</artifactId>
<version>1.0-SNAPSHOT</version>
<properties>
<spark.version>2.1.0</spark.version>
<scala.version>2.11.8</scala.version>
</properties>
<dependencies>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
<version>${scala.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.11</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>2.6.5</version>
</dependency>
</dependencies>
<!--打包插件-->
<build>
<sourceDirectory>src/main/scala</sourceDirectory>
<testSourceDirectory>src/test/scala</testSourceDirectory>
<pluginManagement>
<plugins>
<plugin>
<groupId>net.alchim31.maven</groupId>
<artifactId>scala-maven-plugin</artifactId>
<version>3.2.2</version>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.7.0</version>
</plugin>
</plugins>
</pluginManagement>
<plugins>
<plugin>
<groupId>net.alchim31.maven</groupId>
<artifactId>scala-maven-plugin</artifactId>
<executions>
<execution>
<id>scala-compile-first</id>
<phase>process-resources</phase>
<goals>
<goal>add-source</goal>
<goal>compile</goal>
</goals>
</execution>
<execution>
<id>scala-test-compile</id>
<phase>process-test-resources</phase>
<goals>
<goal>testCompile</goal>
</goals>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<version>2.4.3</version>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<filters>
<filter>
<artifact>*:*</artifact>
<excludes>
<exclude>META-INF/*.SF</exclude>
<exclude>META-INF/*.DSA</exclude>
<exclude>META-INF/*.RSA</exclude>
</excludes>
</filter>
</filters>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
</project>
使用该pom文件，直接下载即可；
Scala写WordCount
代码如下：
/**
* Taoyongpan
* Created in 12:47 2018/5/24
*/
object WordCount {
def main(args: Array[String]): Unit = {
val conf = new SparkConf().setAppName("ScalaWorkContext").setMaster("local")
//sc是Spark Context,是Spark程序的入口
val sc = new SparkContext(conf)
//编写Spark程序
//sc.textFile(args(0)).flatMap(_.split(" ")).map((_,1)).reduceByKey(_+_).saveAsTextFile(args(1))
//指定从哪里读取数据，并生成RDD
val lines : RDD[String] = sc.textFile(args(0))
//将一行内容进行切分压平
val words : RDD[String] = lines.flatMap(_.split(" "))
//将单词和1放到一个元组中
val wordAndOne : RDD[(String,Int)] = words.map((_,1))
//继续聚合
val reduced : RDD[(String,Int)] = wordAndOne.reduceByKey(_+_)
//从小到大排序
val sorted : RDD[(String,Int)] = reduced.sortBy(_._2)
//逆序排序
// val sorted : RDD[(String,Int)] = reduced.sortBy(_._2,false)
//存储到指定位置
sorted.saveAsTextFile(args(1))
sc.stop()
}
}
Java写 WordCount
代码如下：
/**
* Author: Taoyongpan
* Date: Created in 13:16 2018/5/24
*/
public class WordCount {
public static void main(String[] args) {
//
SparkConf conf = new SparkConf();
conf.setAppName("WordCount").setMaster("local");
//创建程序执行的入口
JavaSparkContext jsc = new JavaSparkContext(conf);
//Spark程序
//指定从哪里读取数据
final JavaRDD<String> lines = jsc.textFile(args[0]);
//切分压平
JavaRDD<String> words = lines.flatMap(new FlatMapFunction<String, String>() {
public Iterator<String> call(String line) throws Exception {
String[] words = line.split(" ");
return Arrays.asList(words).iterator();
}
});
//将单词和1放在一起
JavaPairRDD<String, Integer> wordAndOne = words.mapToPair(new PairFunction<String, String, Integer>() {
public Tuple2<String, Integer> call(String word) throws Exception {
return new Tuple2<String, Integer>(word, 1);
}
});
//聚合
JavaPairRDD<String, Integer> reduced = wordAndOne.reduceByKey(new Function2<Integer, Integer, Integer>() {
public Integer call(Integer v1, Integer v2) throws Exception {
return v1 + v2;
}
});
//排序,Java的RDD只支持SortByKey,调换单词和次数的顺序
JavaPairRDD<Integer, String> swaped = reduced.mapToPair(new PairFunction<Tuple2<String, Integer>, Integer, String>() {
public Tuple2<Integer, String> call(Tuple2<String, Integer> tp) throws Exception {
return tp.swap();
}
});
//排序
JavaPairRDD<Integer, String> sorted = swaped.sortByKey();
//再调换顺序
JavaPairRDD<String, Integer> res = sorted.mapToPair(new PairFunction<Tuple2<Integer, String>, String, Integer>() {
public Tuple2<String, Integer> call(Tuple2<Integer, String> tp) throws Exception {
return tp.swap();
}
});
//保存
res.saveAsTextFile(args[1]);
//释放资源
jsc.stop();
}
}
未完待续。。。
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