部署单机环境下的Spark

在官网下载Spark安装包

# 官网地址
https://www.apache.org/dyn/closer.lua/spark/spark-2.4.7/spark-2.4.7-bin-hadoop2.7.tgz
# 下载链接
https://mirrors.tuna.tsinghua.edu.cn/apache/spark/spark-2.4.7/spark-2.4.7-bin-hadoop2.7.tgz

解压缩

1	$ tar -zxvf spark-2.4.7-bin-hadoop2.7.tgz

安装Java

1	$ sudo apt install openjdk-8-jdk -y

启动Spark Shell

$ cd spark-2.4.7-bin-hadoop2.7
$ bin/spark-shell
20/12/23 18:19:08 WARN Utils: Your hostname, Mi-Lv resolves to a loopback address: 127.0.1.1; using 192.168.52.1 instead (on interface eth1)
20/12/23 18:19:08 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
20/12/23 18:19:08 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Spark context Web UI available at http://192.168.52.1:4040
Spark context available as 'sc' (master = local[*], app id = local-1608718759318).
Spark session available as 'spark'.
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 2.4.7
      /_/
         
Using Scala version 2.11.12 (OpenJDK 64-Bit Server VM, Java 1.8.0_275)
Type in expressions to have them evaluated.
Type :help for more information.

scala>

word count程序

1 2	scala> sc.textFile("/home/pancras/input.txt").flatMap(_.split(" ")).map((_,1)).reduceByKey(_+_).collect res1: Array[(String, Int)] = Array((hello,2), (morning,1), (world,2), (good,1))

Tags: all spark

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部署Spark

部署单机环境下的Spark