一、安装JDK

首先检查是否安装jdk,以及版本是否符合要求

java -version

1. 官网下载JDK安装包

http://www.oracle.com/technetwork/java/javase/downloads/index.html
这里下载的是：jdk-8u144-linux-x64.tar.gz

2. 将安装包上传到服务器上

3. 解压JDK

创建要安装Scala的目录

sudo mkdir /usr/lib/java

解压Scala到该目录中

sudo mv jdk-8u144-linux-x64.tar.gz /usr/lib/java/
cd /usr/lib/java/
sudo tar -zxvf jdk-8u144-linux-x64.tar.gz

4. 添加环境变量

vim ~/.bashrc

在最后添加这两行内容

export JAVA_HOME=/usr/lib/java/jdk1.8.0_144
export PATH=$PATH:${JAVA_HOME}/bin

使文件生效

source ~/.bashrc

查看系统环境变量

echo $PATH

5.测试jdk 是是否安装成功

java -version
javac -version

二、安装Scala

1. 官网下载Scala安装包

http://www.scala-lang.org/download/2.11.11.html
这里下载的是：scala-2.11.11.tgz

2. 将安装包上传到服务器上

3. 解压Scala

创建要安装Scala的目录

sudo mkdir /usr/lib/scala

解压Scala到该目录中

sudo mv scala-2.11.11.tgz /usr/lib/scala/
cd /usr/lib/scala/
sudo tar -zxvf scala-2.11.11.tgz

4. 添加环境变量

vim ~/.bashrc

在最后添加这两行内容

export SCALA_HOME=/usr/lib/scala/scala-2.11.11
export PATH=$PATH:${SCALA_HOME}/bin

# 使文件生效
source ~/.bashrc
# 查看系统环境变量
echo $PATH
# 查看是否安装成功
scala -version

三、安装Spark

1.下载Spark

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

Package type
- Source code: Spark 源码，需要编译才能使用，另外 Scala 2.11 需要使用源码编译才可使用
- Pre-build with user-provided Hadoop: “Hadoop free” 版，可应用到任意 Hadoop 版本
- Pre-build for Hadoop 2.7 and later: 基于 Hadoop 2.7 的预先编译版，需要与本机安装的 Hadoop 版本对应。
选择完毕，点击>Download Spark<

2. 将安装包上传到服务器上

3. 解压Spark

创建要安装Spark的目录

sudo mkdir /usr/lib/spark

解压Spark到该目录中

sudo mv scala-2.11.11.tgz /usr/lib/scala/
cd /usr/lib/scala/
sudo tar -zxvf spark-2.2.0-bin-hadoop2.7.tgz

4. 添加环境变量

vim ~/.bashrc

在最后添加这两行内容

export SPARK_HOME=/usr/lib/scala/spark-2.2.0-bin-hadoop2.7
export PATH=$PATH:${SPARK_HOME}/bin

使文件生效

source ~/.bashrc

查看系统环境变量

echo $PATH

5. 测试是否安装成功

输入：spark-shell

Spark context Web UI available at http://10.65.157.216:4040
Spark context available as 'sc' (master = local[*],app id = local-1507699389775).
Spark session available as 'spark'.
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 2.2.0
      /_/

Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM,Java 1.8.0_144)
Type in expressions to have them evaluated.
Type :help for more information.

scala>

测试代码：

scala> val textFile = sc.textFile("file:///usr/lib/spark/spark-2.2.0-bin-hadoop2.7/README.md")
scala> textFile.count()
scala> textFile.first()
scala> val wordCounts = textFile.flatMap(line => line.split(" ")).map(word => (word,1)).reduceByKey((a,b) => a + b)
scala> wordCounts.collect()

测试Spark，输入: pyspark

Python 2.7.6 (default,Oct 26 2016,20:30:19)
[GCC 4.8.4] on linux2
Type "help","copyright","credits" or "license" for more information.
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).
17/10/11 00:19:39 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
17/10/11 00:19:45 WARN ObjectStore: Failed to get database global_temp,returning NoSuchObjectException
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /__ / .__/\_,_/_/ /_/\_\   version 2.2.0
      /_/

Using Python version 2.7.6 (default,Oct 26 2016 20:30:19)
SparkSession available as 'spark'.
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