spark 單詞統計

maven 項目 前提是裝好hadoop集羣和spark集羣 並上傳好文件到hdfs 

pom.xml 如下

<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>test</groupId>
  <artifactId>spark</artifactId>
  <version>0.0.1-SNAPSHOT</version>
  <packaging>jar</packaging>

  <name>spark</name>
  <url>http://maven.apache.org</url>

  <properties>
    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
  </properties>

  <dependencies>
    <dependency>
      <groupId>junit</groupId>
      <artifactId>junit</artifactId>
      <version>3.8.1</version>
      <scope>test</scope>
    </dependency>
    
    <dependency>
    <groupId>org.apache.spark</groupId>
    <artifactId>spark-core_2.10</artifactId>
    <version>2.2.0</version>
</dependency>
    
  </dependencies>
  
  
  <build>
		<plugins>
			<plugin>
				<groupId>org.apache.maven.plugins</groupId>
				<artifactId>maven-compiler-plugin</artifactId>
				<configuration>
					<source>1.8</source>
					<target>1.8</target>
					<encoding>UTF-8</encoding>
				</configuration>
			</plugin>
			<plugin>
				<groupId>org.springframework.boot</groupId>
				<artifactId>spring-boot-maven-plugin</artifactId>
			</plugin>
		</plugins>
	</build>
</project>

java 代碼

package test.spark;

import java.util.Arrays;
import java.util.List;

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 scala.Tuple2;

public class CountWord {

	@SuppressWarnings("resource")
	public static void main(String[] args) {
		// 創建一個java版本的Spark Context
		SparkConf conf = new SparkConf().setMaster("spark://192.168.7.202:7077").setAppName("My App");
		JavaSparkContext sc = new JavaSparkContext(conf);
		// 從hadoop中hdfs讀取輸入數據
		JavaRDD<String> input = sc.textFile("hdfs://192.168.7.202:900/test/sql.txt");
		// 根據空格切分成單詞
		JavaRDD<String> words = input.flatMap((String x) -> {
			List<String> list = Arrays.asList(x.split(" "));
			return list.iterator();
		});
		// 轉換成鍵值對並計數
		JavaPairRDD<String, Integer> count = words.mapToPair((String x) -> {
			return new Tuple2<String, Integer>(x, 1);
		}).reduceByKey((Integer v1, Integer v2) -> {
			return v1 + v2;
		});
		// 將統計出來的單詞存入一個文本文件
		count.saveAsTextFile("hdfs://192.168.7.202:900/test/sql-spark2");
		
	}

}

最後打包

上傳jar包到主節點

執行命令

 /data1/hadoop/spark-2.2.0-bin-hadoop2.7/bin/spark-submit --master spark://192.168.7.202:7077 --class test.spark.CountWord  /data1/hadoop/spark-2.2.0-bin-hadoop2.7/shell/spark-0.0.1-SNAPSHOT.jar

查看結果

hadoop fs -cat /test/sql-spark2/part-00001

代碼量是不是比用hadoop 體系裏面mapreduce少很多