spark初识(一):
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1、官网的spark包中pre-build with user provider与pre-build for Apache hadoop3.2什么区别?
2、spark是否使用是否必须安装hadoop?
3、第一个wordcount例子提交集群
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开始解惑(单纯个人理解):
1、spark的下载包区别,spark是否使用是否必须安装hadoop?
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我的理解是两个包(with user provider与没有)区别不是太大,假如
使用搭建spark集群的话都能使用,注意版本是否与hadoop版本一致,
为了防止其他意外发生还是版本一致即可。
注意:spark安装不需安装hadoop环境,只是两者经常配合使用,比如用到hadoop中的hdfs
**
2、wordcount提交集群例子?
scala代码
object WordCount {
def main(args: Array[String]): Unit = {
val sparConf = new SparkConf().setAppName("WordCount")
val sc = new SparkContext(sparConf)
var filepath = "data"+ File.separator +"*.txt"
if(args.length>0){
filepath = args(0)
}
val lines:RDD[String]= sc.textFile(filepath,2)
val words:RDD[String]= lines flatMap (_.split(" "))
val wordGroup:RDD[(String, Iterable[String])] = words.groupBy(word=>word)
val word2count = wordGroup.map {
case (word, list) => {
(word, list.size)
}
}
word2count.saveAsTextFile("out")
// val array = word2count.collect()
// val unit = array.foreach(println)
sc.stop()
}
}
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.example</groupId>
<artifactId>spark-demo</artifactId>
<version>1.0-SNAPSHOT</version>
<build>
<plugins>
<plugin>
<groupId>net.alchim31.maven</groupId>
<artifactId>scala-maven-plugin</artifactId>
<version>3.4.6</version>
<executions>
<execution>
<goals>
<goal>compile</goal>
<goal>testCompile</goal>
</goals>
</execution>
</executions>
</plugin>
</plugins>
</build>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.12</artifactId>
<version>3.1.1</version>
</dependency>
</dependencies>
</project>
提交集群
spark-submit
--master spark://spark:7077
--class WordCount
wc.jar
spark-3.1.2-bin-hadoop3.2/input/*
spark web界面显示如下
学习总结:
例如:
1、 spark集群部署只是第一步,能简单搭建个即可,不用死钻进去,毕竟开发时不是总用搭建的
2、动手试试效果最好,加深理解