189 8069 5689

Spark的安装和基础编程

Linux系统:Ubuntu 16.04

十年的大厂网站建设经验,针对设计、前端、开发、售后、文案、推广等六对一服务,响应快,48小时及时工作处理。成都营销网站建设的优势是能够根据用户设备显示端的尺寸不同,自动调整大厂建站的显示方式,使网站能够适用不同显示终端,在浏览器中调整网站的宽度,无论在任何一种浏览器上浏览网站,都能展现优雅布局与设计,从而大程度地提升浏览体验。创新互联从事“大厂网站设计”,“大厂网站推广”以来,每个客户项目都认真落实执行。

Hadoop: 2.7.1

JDK: 1.8

Spark: 2.4.3

一.下载安装文件

http://spark.apache.org/downloads.html

https://archive.apache.org/dist/spark/

hadoop@dblab:/usr/local$ sudo wgethttp://mirror.bit.edu.cn/apache/spark/spark-2.4.3/spark-2.4.3-bin-hadoop2.7.tgz

hadoop@dblab:/usr/local$ sudo tar -zxf spark-2.4.3-bin-hadoop2.7.tgz -C spark

hadoop@dblab:/usr/local$ sudo chown -R hadoop:hadoop spark/

二.配置相关文件

hadoop@dblab:/usr/local/spark$ ./conf/spark-env.sh.template  ./conf/spark-env.sh

export SPARK_DIST_CLASSPATH=$(/usr/local/hadoop/bin/hadoop classpath)

#验证Spark是否安装成功

hadoop@dblab:/usr/local/spark$ bin/run-example SparkPi

Pi is roughly 3.139035695178476   

三.启动Spark Shell

hadoop@dblab:/usr/local/spark$ ./bin/spark-shell     

Welcome to

      ____              __

     / __/__  ___ _____/ /__

    _\ \/ _ \/ _ `/ __/  '_/

   /___/ .__/\_,_/_/ /_/\_\   version 2.1.0

      /_/

Using Scala version 2.11.8 (OpenJDK 64-Bit Server VM, Java 1.8.0_212)

Type in expressions to have them evaluated.

Type :help for more information.

scala> 

scala> 8*2+5

res0: Int = 21

四.读取文件

1.读取本地文件

hadoop@dblab:/usr/local/hadoop$ ./sbin/start-dfs.sh                             

scala> val textFile=sc.textFile("file:///usr/local/spark/README.md")

textFile: org.apache.spark.rdd.RDD[String] = file:///usr/local/spark/README.md MapPartitionsRDD[1] at textFile at :24

scala> textFile.first()

res0: String = # Apache Spark

2.读取HDFS文件

hadoop@dblab:/usr/local/hadoop$ ./bin/hdfs dfs -put /usr/local/spark/README.md .

hadoop@dblab:/usr/local/hadoop$ ./bin/hdfs dfs -cat README.md

scala> val textFile=sc.textFile("hdfs://localhost:9000/user/hadoop/README.md")

textFile: org.apache.spark.rdd.RDD[String] = hdfs://localhost:9000/user/hadoop/README.md MapPartitionsRDD[3] at textFile at :24

scala> textFile.first()

res1: String = # Apache Spark

scala> :quit


当前标题:Spark的安装和基础编程
本文路径:http://cdxtjz.cn/article/gseggd.html

其他资讯