标签:pil 操作 memory private 消息 生成 mem void long
tar -zxvf spark-2.4.0-bin-hadoop2.7.tgz
rm spark-2.4.0-bin-hadoop2.7.tgz
mv spark-2.4.0-bin-hadoop2.7 spark
sudo vim /etc/profile
export SPARK_HOME=/usr/local/storm
export PATH=$PATH:$SPARK_HOME/bin
source /etc/profile
准备 master worker1 worker2 worker3 这四台机器
首先确保你的Hadoop集群能够正常运行worker1 worker2 worker3为DataNode, master为NameNode
具体配置参照我的博客https://www.cnblogs.com/ye-hcj/p/10192857.html
spark-env.sh
进入spark的conf目录下,cp spark-env.sh.template spark-env.sh
sudo vim spark-env.sh
输入如下配置
export JAVA_HOME=/usr/local/jdk/jdk-11.0.1
export SCALA_HOME=/usr/local/scala/scala
export HADOOP_HOME=/usr/local/hadoop/hadoop-3.1.1
export SPARK_HOME=/usr/local/spark/spark
export HADOOP_CONF_DIR=/usr/local/hadoop/hadoop-3.1.1/etc/hadoop
export SPARK_MASTER_HOST=master
export SPARK_WORKER_MEMORY=1g
export SPARK_WORKER_CORES=1
slaves
进入spark的conf目录下,cp slaves.template slaves
sudo vim slaves
输入如下配置
master
worker1
worker2
worker3
启动
在master中运行 sbin/start-all.sh 即可
访问http://master:8080/即可看到spark的ui
写个小demo,用来分析10万个数据中男女人数
模拟数据的java代码
// 模拟数据
// 10万个人当中,统计青年男性和青年女性的比例,看看男女比例是否均衡
FileOutputStream f = null;
ThreadLocalRandom random = ThreadLocalRandom.current();
String str = "";
int count = 0;
try {
f = new FileOutputStream("C:\\Users\\26401\\Desktop\\data.txt", true);
for(;count<100000;count++) {
str = count + " " + random.nextInt(18, 28) + " " + (random.nextBoolean()?‘M‘:‘F‘);
f.write((str + "\r\n").getBytes());
}
} catch (Exception e) {
e.printStackTrace();
} finally {
try {
if(f != null) f.close();
} catch (IOException e) {
e.printStackTrace();
}
}
依赖
<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>test</artifactId>
<version>1.0.0</version>
<name>test</name>
<description>Test project for spring boot mybatis</description>
<packaging>jar</packaging>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<maven.compiler.encoding>UTF-8</maven.compiler.encoding>
<java.version>1.8</java.version>
<maven.compiler.source>1.8</maven.compiler.source>
<maven.compiler.target>1.8</maven.compiler.target>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.12</artifactId>
<version>2.4.0</version>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
<version>1.7.25</version>
</dependency>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>3.8.1</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-jar-plugin</artifactId>
<configuration>
<archive>
<manifest>
<addClasspath>true</addClasspath>
<useUniqueVersions>false</useUniqueVersions>
<classpathPrefix>lib/</classpathPrefix>
</manifest>
</archive>
</configuration>
</plugin>
</plugins>
</build>
</project>
java代码
package test;
import java.io.Serializable;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.Function;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
public class App implements Serializable
{
private static final long serialVersionUID = -7114915627898482737L;
public static void main(String[] args) throws Exception {
Logger logger=LoggerFactory.getLogger(App.class);
SparkConf sparkConf = new SparkConf();
sparkConf.setMaster("spark://master:7077");
sparkConf.set("spark.submit.deployMode", "cluster");
sparkConf.setAppName("FirstTest");
JavaSparkContext sc = new JavaSparkContext(sparkConf);
JavaRDD<String> file = sc.textFile("hdfs://master:9000/data.txt");
JavaRDD<String> male = file.filter(new Function<String, Boolean>() {
private static final long serialVersionUID = 1L;
@Override
public Boolean call(String s) throws Exception {
logger.info(s);
return s.contains("M");
}
});
logger.info("**************************************");
logger.info(male.count()+""); // 49991
logger.info("**************************************");
sc.close();
// 其他的api请自行查阅,很简单,不想看,可以自己瞎点
}
}
运行
1. 将生成的测试数据data.txt上传至hdfs
2. 将打包的jar上传到master机器
3. 运行 bin/spark-submit --master spark://master:7077 --class test.App test-1.0.0.jar
4. 进入spark的ui界面可以清楚的看到打印的消息
标签:pil 操作 memory private 消息 生成 mem void long
原文地址:https://www.cnblogs.com/ye-hcj/p/10280114.html