一、Pi估值算法

通过在圆上“投掷飞镖”来估计π。我们在单位平方（（0，0）到（1，1））中随机选取点，看看有多少点落在单位圆内。分数应该是π/4，所以我们用这个来得到我们的估计值。

 

二、项目maven依赖

<?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.mk</groupId><artifactId>spark-test</artifactId><version>1.0</version><name>spark-test</name><url>http://spark.mk.com</url><properties><project.build.sourceEncoding>UTF-8</project.build.sourceEncoding><maven.compiler.source>1.8</maven.compiler.source><maven.compiler.target>1.8</maven.compiler.target><scala.version>2.11.1</scala.version><spark.version>2.4.4</spark.version><hadoop.version>2.6.0</hadoop.version></properties><dependencies><!-- scala依赖--><dependency><groupId>org.scala-lang</groupId><artifactId>scala-library</artifactId><version>${scala.version}</version></dependency><!-- spark依赖--><dependency><groupId>org.apache.spark</groupId><artifactId>spark-core_2.11</artifactId><version>${spark.version}</version></dependency><dependency><groupId>org.apache.spark</groupId><artifactId>spark-sql_2.11</artifactId><version>${spark.version}</version></dependency><dependency><groupId>junit</groupId><artifactId>junit</artifactId><version>4.11</version><scope>test</scope></dependency></dependencies><build><pluginManagement><plugins><plugin><artifactId>maven-clean-plugin</artifactId><version>3.1.0</version></plugin><plugin><artifactId>maven-resources-plugin</artifactId><version>3.0.2</version></plugin><plugin><artifactId>maven-compiler-plugin</artifactId><version>3.8.0</version></plugin><plugin><artifactId>maven-surefire-plugin</artifactId><version>2.22.1</version></plugin><plugin><artifactId>maven-jar-plugin</artifactId><version>3.0.2</version></plugin></plugins></pluginManagement></build>
</project>

 

三、编程代码

public class PiApp implements SparkConfInfo {public static void main(String[] args) {SparkSession sparkSession = new PiApp().getSparkConf("Pi");int slices = 2;int n = (int) Math.min(100_000L * slices, Integer.MAX_VALUE);JavaSparkContext sparkContext = new JavaSparkContext(sparkSession.sparkContext());List<Integer> list = new ArrayList<>(n);for (int i = 0; i < n; i++)list.add(i + 1);int count = sparkContext.parallelize(list, slices).map(v -> {double x = Math.random() * 2 - 1;double y = Math.random() * 2 - 1;if (x * x + y * y < 1)return 1;return 0;}).reduce((Integer a, Integer b) -> a + b);System.out.println("PI:" + 4.0 * count / n);sparkSession.stop();}
}public interface SparkConfInfo {default SparkSession getSparkConf(String appName){SparkConf sparkConf = new SparkConf();if(System.getProperty("os.name").toLowerCase().contains("win")) {sparkConf.setMaster("local[4]");System.out.println("使用本地模拟是spark");}else{sparkConf.setMaster("spark://hadoop01:7077,hadoop02:7077,hadoop03:7077");sparkConf.set("spark.driver.host","192.168.150.1");//本地ip，必须与spark集群能够相互访问，如：同一个局域网sparkConf.setJars(new String[] {".\\out\\artifacts\\spark_test\\spark-test.jar"});//项目构建生成的路径}SparkSession session = SparkSession.builder().appName(appName).config(sparkConf).config(sparkConf).getOrCreate();return session;}
}

输出

PI:3.14296