我们在工作中最长见的问题就是词频统计了,下面给大家一个模板,希望可以帮到大家,scala版本为2.11
pom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.wy</groupId>
<artifactId>sparkt</artifactId>
<version>1.0-SNAPSHOT</version>
<dependencies>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
<version>2.11.8</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.11</artifactId>
<version>2.0.2</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.11</artifactId>
<version>2.0.2</version>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>5.1.6</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-hive_2.11</artifactId>
<version>2.0.2</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_2.11</artifactId>
<version>2.0.2</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-kafka-0-10_2.11</artifactId>
<version>2.0.2</version>
</dependency>
</dependencies>
<build>
<pluginManagement>
<plugins>
<!-- 编译scala的插件 -->
<plugin>
<groupId>net.alchim31.maven</groupId>
<artifactId>scala-maven-plugin</artifactId>
<version>3.2.2</version>
</plugin>
<!-- 编译java的插件 -->
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.5.1</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-compiler-plugin</artifactId>
<executions>
<execution>
<phase>compile</phase>
<goals>
<goal>compile</goal>
</goals>
</execution>
</executions>
</plugin>
<!-- 打jar插件 -->
<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>
代码如下
package com.wy.sparkcore
import org.apache.spark.rdd.RDD
import org.apache.spark.{
SparkConf, SparkContext}
object WordCount {
def main(args: Array[String]): Unit = {
//Spark的容器SparkConext
val conf: SparkConf = new SparkConf().setMaster("local").setAppName("WordCount")
val sc = new SparkContext(conf)
//读取文件创建RDD:(弹性分布式数据集)
//拿到文件的行集(行的RDD)
val dataRDD: RDD[String] = sc.textFile("a.txt")
//对每行进行切分:按照空格切分 => 切分之后的字符串RDD
val wordRDD: RDD[String] = dataRDD.flatMap(_.split(" "))
//对上面处理的字符串RDD做转换:每个字符串记1 ("hello",1) ("hello",1)
val wordnumRDD: RDD[(String, Int)] = wordRDD.map((_,1))
//对上面的到的元组按照key进行reduce
//val resultRDD: RDD[(String, Int)] = wordnumRDD.reduceByKey(_+_)
val resultRDD: RDD[(String, Int)] = wordnumRDD.reduceByKey((num1:Int,num2:Int)=>num1+num2)
//触发任务提交执行,打印输出结果
resultRDD.foreach(println(_))
//sc.textFile("a.txt").flatMap(_.split(" ")).map((_,1)).reduceByKey(_+_).foreach(println(_))
}
}