Spark2.x SparkCore WordCount Demo
作者：互联网
版本
scala : 2.11 spark : 2.20
1、pom.xml
<?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>org.exercise</groupId>
<artifactId>scala</artifactId>
<version>1.0-SNAPSHOT</version>
<properties>
<maven.compiler.source>1.8</maven.compiler.source>
<maven.compiler.target>1.8</maven.compiler.target>
<scala.version>2.11.8</scala.version>
<spark.version>2.2.0</spark.version>
<hadoop.version>2.7.3</hadoop.version>
<encoding>UTF-8</encoding>
<akka.version>2.4.17</akka.version>
<scala.compat.version>2.11</scala.compat.version>
<lucene.version>6.5.1</lucene.version>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.httpcomponents</groupId>
<artifactId>httpclient</artifactId>
<version>4.5.2</version>
</dependency>
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-api</artifactId>
<version>2.3</version>
</dependency>
<dependency>
<groupId>commons-logging</groupId>
<artifactId>commons-logging</artifactId>
<version>1.2</version>
</dependency>
<!-- <dependency>-->
<!-- <groupId>org.slf4j</groupId>-->
<!-- <artifactId>slf4j-log4j12</artifactId>-->
<!-- <version>1.7.25</version>-->
<!-- <scope>test</scope>-->
<!-- </dependency>-->
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-nop</artifactId>
<version>1.7.2</version>
</dependency>
<!-- lucene的核心 -->
<dependency>
<groupId>org.apache.lucene</groupId>
<artifactId>lucene-core</artifactId>
<version>${lucene.version}</version>
</dependency>
<!-- lucene的分词器，有标准的英文相关的分词器，没有中文的 -->
<dependency>
<groupId>org.apache.lucene</groupId>
<artifactId>lucene-analyzers-common</artifactId>
<version>${lucene.version}</version>
</dependency>
<!-- 查询解析器 -->
<dependency>
<groupId>org.apache.lucene</groupId>
<artifactId>lucene-queryparser</artifactId>
<version>${lucene.version}</version>
</dependency>
<!-- 各种查询方式 -->
<dependency>
<groupId>org.apache.lucene</groupId>
<artifactId>lucene-queries</artifactId>
<version>${lucene.version}</version>
</dependency>
<!-- 关键字高亮 -->
<dependency>
<groupId>org.apache.lucene</groupId>
<artifactId>lucene-highlighter</artifactId>
<version>${lucene.version}</version>
</dependency>
<dependency>
<groupId>org.apache.lucene</groupId>
<artifactId>lucene-demo</artifactId>
<version>${lucene.version}</version>
</dependency>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>4.12</version>
</dependency>
<dependency>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
<version>1.2.17</version>
</dependency>
<!-- <dependency>-->
<!-- <groupId>org.slf4j</groupId>-->
<!-- <artifactId>slf4j-api</artifactId>-->
<!-- <version>1.7.22</version>-->
<!-- </dependency>-->
<!--######################################################-->
<!-- es的客户端-->
<dependency>
<groupId>org.elasticsearch.client</groupId>
<artifactId>transport</artifactId>
<version>5.4.3</version>
</dependency>
<!-- 依赖2.x的log4j -->
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-api</artifactId>
<version>2.8.2</version>
</dependency>
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-core</artifactId>
<version>2.8.2</version>
</dependency>
<!-- 单元测试 -->
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>4.12</version>
</dependency>
<!--###########################################################-->
<dependency>
<groupId>com.github.scopt</groupId>
<artifactId>scopt_2.10</artifactId>
<version>3.2.0</version>
</dependency>
<!-- 添加akka的actor依赖 -->
<dependency>
<groupId>com.typesafe.akka</groupId>
<artifactId>akka-actor_${scala.compat.version}</artifactId>
<version>${akka.version}</version>
</dependency>
<!-- 多进程之间的Actor通信 -->
<dependency>
<groupId>com.typesafe.akka</groupId>
<artifactId>akka-remote_${scala.compat.version}</artifactId>
<version>${akka.version}</version>
</dependency>
<!-- 导入scala的依赖 -->
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
<version>${scala.version}</version>
</dependency>
<!-- 导入spark的依赖 -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.11</artifactId>
<version>${spark.version}</version>
</dependency>
<!-- 指定hadoop-client API的版本 -->
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>${hadoop.version}</version>
</dependency>
<!-- 导入spark sql的依赖 -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.11</artifactId>
<version>${spark.version}</version>
</dependency>
<!-- spark如果想整合Hive，必须加入hive的支持 -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-hive_2.11</artifactId>
<version>2.2.0</version>
</dependency>
<!-- spark steaming的依赖 -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_2.11</artifactId>
<version>2.2.0</version>
</dependency>
<!-- spark-mllib的依赖 -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-mllib_2.11</artifactId>
<version>2.2.0</version>
</dependency>
<!-- sparkSteaming跟Kafka整合的依赖 -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-kafka-0-8_2.11</artifactId>
<version>${spark.version}</version>
</dependency>
<!-- mysql的连接驱动依赖 -->
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>8.0.16</version>
</dependency>
<dependency>
<groupId>redis.clients</groupId>
<artifactId>jedis</artifactId>
<version>2.9.0</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>
View Code
2、FavTeacher.scala
import java.net.URL
import org.apache.spark.rdd.RDD
import org.apache.spark.{SparkConf, SparkContext}
object FavTeacher {
def main(args: Array[String]): Unit = {
val conf = new SparkConf().setAppName("FavTeacher").setMaster("local[4]")
val sc = new SparkContext(conf)
//指定以后从哪里读取数据
val lines: RDD[String] = sc.textFile("F:\\Java\\scala\\src\\main\\resources\\spart_data\\topN\\input\\teacher.log")
//整理数据
val teacherAndOne = lines.map(line => {
val index = line.lastIndexOf("/")
val teacher = line.substring(index + 1)
//val httpHost = line.substring(0, index)
//val subject = new URL(httpHost).getHost.split("[.]")(0)
(teacher, 1)
})
//聚合
val reduced: RDD[(String, Int)] = teacherAndOne.reduceByKey(_+_)
//排序
val sorted: RDD[(String, Int)] = reduced.sortBy(_._2, false)
//触发Action执行计算
val reslut: Array[(String, Int)] = sorted.collect()
//打印
println(reslut.toBuffer)
sc.stop()
}
}
标签：scala,Spark2,SparkCore,WordCount,lucene,version,apache,org,spark 来源： https://www.cnblogs.com/ywjfx/p/14827302.html