Mac部署spark2.4.4

环境信息

1. 操作系统：macOS Mojave 10.14.6
2. JDK：1.8.0_211 (安装位置：/Library/Java/JavaVirtualMachines/jdk1.8.0_211.jdk/Contents/Home)

前提条件

请参考《Mac部署hadoop3(伪分布式)》一文，在Mac上事先部署好hadoop3

部署步骤

1. 安装scala：

brew install scala

2. 配置scala的环境变量，打开文件~/.bash_profile，增加以下配置内容：

export SCALA_HOME=/usr/local/Cellar/scala/2.13.0
export PATH=$PATH:$SCALA_HOME/bin

3. 执行命令source ~/.bash_profile，再验证scala：

base) zhaoqindeMBP:~ zhaoqin$ scala -version
Scala code runner version 2.13.0 -- Copyright 2002-2019, LAMP/EPFL and Lightbend, Inc.

4. 下载spark，地址是：http://spark.apache.org/downloads.html ，如下图红框：
   
5. 将下载的文件在/usr/local/目录下解压，并将文件夹名字从spark-2.4.4-bin-hadoop2.7改为spark
6. 配置spark的环境变量，打开文件~/.bash_profile，增加以下配置内容：

export SPARK_HOME=/usr/local/spark
export PATH=$PATH:$SPARK_HOME/bin

7. 执行命令source ~/.bash_profile使配置生效；
8. 打开文件spark/conf/spark-env.sh，在尾部增加以下三行：

export SCALA_HOME=/usr/local/Cellar/scala/2.13.0
export SPARK_MASTER_IP=localhost
export SPARK_WORKER_MEMORY=2G

9. 确保hdfs和yarn已经启动，然后执行命令spark-shell，即可启动spark服务：

To update your account to use zsh, please run `chsh -s /bin/zsh`.
For more details, please visit https://support.apple.com/kb/HT208050.
(base) zhaoqindeMBP:~ zhaoqin$ spark-shell
19/10/27 13:33:51 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://zhaoqindembp:4040
Spark context available as 'sc' (master = local[*], app id = local-1572154437623).
Spark session available as 'spark'.
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 2.4.4
      /_/

Using Scala version 2.11.12 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_211)
Type in expressions to have them evaluated.
Type :help for more information.

scala>

至此，Mac机器上的hadoop和spark都运行起来了，希望本文能给您带来一些参考。