搭建spark本地环境
- 搭建Java环境
(1)到官网下载JDK
下载地址:点击这里
(2)解压缩到指定的目录
>sudo tar -zxvf jdk-8u91-linux-x64.tar.gz -C /usr/lib/jdk //版本号视自己安装的而定
(3)设置路径和环境变量
>sudo vim /etc/profile
在文件的最后加上
export JAVA_HOME=/usr/lib/jdk/jdk1.8.0_91
export JRE_HOME=${JAVA_HOME}/jre
export CLASSPATH=.:${JAVA_HOME}/lib:${JRE_HOME}/lib
export PATH=${JAVA_HOME}/bin:$PATH
(4)让配置生效
source /etc/profile
(5)验证安装是否成功
~$ java -version
java version "1.8.0_181"
Java(TM) SE Runtime Environment (build 1.8.0_181-b13)
Java HotSpot(TM) 64-Bit Server VM (build 25.181-b13, mixed mode)
- 安装Scala
(1)到官网下载安装包
点击这里
(2)解压缩到指定目录
sudo tar -zxvf scala-2.11.8.tgz -C /usr/lib/scala //版本号视自己安装的而定
(3)设置路径和环境变量
>sudo vim /etc/profile
在文件最后加上
export SCALA_HOME=/usr/lib/scala/scala-2.11.8 //版本号视自己安装的而定
export PATH=${SCALA_HOME}/bin:$PATH
(4)让配制生效
source /etc/profile
(5)验证安装是否成功
:~$ scala
Welcome to Scala 2.12.6 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_181).
Type in expressions for evaluation. Or try :help.
scala>
- 安装Spark
(1)到官网下载安装包
下载地址:点击这里
(2)解压缩到指定目录
sudo tar -zxvf spark-1.6.1-bin-hadoop2.6.tgz -C /usr/lib/spark //版本号视自己安装的而定
(3)设置路径和环境变量
>sudo vim /etc/profile
在文件最后加上
export SPARK_HOME=/usr/lib/spark/spark-1.6.1-bin-hadoop2.6
export PATH=${SPARK_HOME}/bin:$PATH
(4)让配置生效
source /etc/profile
(5)验证安装是否成功
:~$ cd spark-1.6.1-bin-hadoop2.6
:~/spark-1.6.1-bin-hadoop2.6$ ./bin/spark-shell
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).
18/09/30 20:59:31 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
18/09/30 20:59:32 WARN Utils: Your hostname, pxh resolves to a loopback address: 127.0.1.1; using 10.22.48.4 instead (on interface wlan0)
18/09/30 20:59:32 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
18/09/30 20:59:45 WARN ObjectStore: Failed to get database global_temp, returning NoSuchObjectException
Spark context Web UI available at http://10.22.48.4:4040
Spark context available as 'sc' (master = local[*], app id = local-1538312374870).
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_181)
Type in expressions to have them evaluated.
Type :help for more information.
- 安装sbt
(1)到官网下载安装包
下载地址:点击这里
(2)解压缩到指定目录
tar -zxvf sbt-0.13.9.tgz -C /usr/local/sbt
(3)在/usr/local/sbt 创建sbt脚本并添加以下内容
$ cd /usr/local/sbt
$ vim sbt
# 在sbt文本文件中添加如下信息:
BT_OPTS="-Xms512M -Xmx1536M -Xss1M -XX:+CMSClassUnloadingEnabled -XX:MaxPermSize=256M"
java $SBT_OPTS -jar /usr/local/sbt/bin/sbt-launch.jar "$@"
(4)保存后,为sbt脚本增加执行权限
$ chmod u+x sbt
(5)设置路径和环境变量
>sudo vim /etc/profile
在文件最后加上
export PATH=/usr/local/sbt/:$PATH
(6)让配置生效
source /etc/profile
(7)验证安装是否成功
$ sbt sbt-version
//如果这条命令运行不成功请改为以下这条 >sbt sbtVersion
$ sbt sbtVersion
Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=256M; support was removed in 8.0
[info] Loading project definition from /home/pxh/project
[info] Set current project to pxh (in build file:/home/pxh/)
[info] 1.2.1
编写Scala应用程序
(1)在终端创建一个文件夹sparkapp作为应用程序根目录
cd ~
mkdir ./sparkapp
mkdir -p ./sparkapp/src/main/scala #创建所需的文件夹结构
(2)./sparkapp/src/main/scala在建立一个SimpleApp.scala的文件并添加以下代码
import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._
import org.apache.spark.SparkConf
object SimpleApp {
def main(args:Array[String]){
val logFile = "file:///home/pxh/hello.ts"
val conf = new SparkConf().setAppName("Simple Application")
val sc = new SparkContext(conf)
val logData = sc.textFile(logFile,2).cache()
val numAs = logData.filter(line => line.contains("a")).count()
println("Lines with a: %s".format(numAs))
}
}
(3)添加该独立应用程序的信息以及与Spark的依赖关系
vim ./sparkapp/simple.sbt
在文件中添加如下内容
name:= "Simple Project"
version:= "1.0"
scalaVersion :="2.11.8"
libraryDependencies += "org.apache.spark"%% "spark-core" % "2.2.0"
(4)检查整个应用程序的文件结构
cd ~/sparkapp
find .
文件结构如下
.
./simple.sbt
./src
./src/main
./src/main/scala
./src/main/scala/SimpleApp.scala
(5)将整个应用程序打包成JAR(首次运行的话会花费较长时间下载依赖包,请耐心等待)
sparkapp$ /usr/local/sbt/sbt package
Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=256M; support was removed in 8.0
[info] Loading project definition from /home/pxh/sparkapp/project
[info] Loading settings for project sparkapp from simple.sbt ...
[info] Set current project to Simple Project (in build file:/home/pxh/sparkapp/)
[success] Total time: 2 s, completed 2018-10-1 0:04:59
(6)将生成的jar包通过spark-submit提交到Spark中运行
:~$ /home/pxh/spark-2.2.0-bin-hadoop2.7/bin/spark-submit --class "SimpleApp" /home/pxh/sparkapp/target/scala-2.11/simple-project_2.11-1.0.jar 2>&1 | grep "Lines with a:"
Lines with a: 3
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