Spark:一个独立应用

关于构建

Java和Scala

在Java和Scala中,只需要给你的应用添加一个对于spark-core的Maven依赖.

Python

在Python中,可以把应用写成脚本,然后使用Spark自带的bin/spark-submit脚本来运行.spark-submit会引入Python程序的Spark依赖.使用方式如下所示.
/PATH_TO_SPARK/bin/spark-submit my_python_script.py

初始化SparkContext

• 先创建一个SparkConf对象来配置应用
• 基于SparkConf创建一个SparkContext对象

Python示例

代码

from pyspark import SparkConf, SparkContextconf = SparkConf().setMaster("local").setAppName("My App")
sc = SparkContext(conf = conf)

运行

spark-submit spark-app.py

Scala示例

import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._val conf = new SparkConf().setMaster("local").setAppName("My App")
val sc = new SparkContext(conf)

Java示例

import org.apache.spark.SparkConf
import org.apache.spark.api.java.JavaSparkContextSparkConf conf = new SparkConf().setMaster("local").setAppName("My App");
JavaSparkContext sc = new JavaSparkContext(conf);

说明

上述例子是创建SparkContext的最基本的方法,你只需传递两个参数:

• 集群URL(上述是local),告诉Spark如何运行连接到集群上
• 应用名可以用来在集群管理器的用户界面找到该应用

独立应用示例

创建空白目录,在新建目录下,新建文件simpleApp.Scala,添加如下代码.

Scala代码

import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._
import org.apache.spark.SparkConfobject SimpleApp {def main(args: Array[String]) {val logFile = "README.md"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()val numBs = logData.filter(line => line.contains("b")).count()println("Lines with a: %s, lines with b: %s".format(numAs, numBs))}
}

构建文件

在新建目录下,新建文件simple.sbt,复制如下代码.

name := "Simple Application"
version := "1.0"
scalaVersion := "2.11.8"
libraryDependencies += "org.apache.spark" %% "spark-core" % "2.0.0"

• 使用scala -version命令查看scala版本,使用spark-shell可以查看spark版本及scala版本,使用:quit命令退出spark-shell

说明

• 程序构建需要安装sbt
• 程序用来统计README.md文件中包含a和b的行数
• 需要将README.md放到Spark使用的文件系统的相应位置.比如,如果使用的是HDFS,README.md应该放在/user/YOUR_USER_NAME/目录下, 或者将val logFile = "README.md"中的文件路径改为绝对路径,例如:val logFile = "/user/mint/README.md".

构建

新建文件夹下包含的文件

$ ls
simpleApp.scala  simple.sbt

执行构建

$ sbt package
[info] Set current project to Simple Project (in build file:/home/public/program/scala/self-cont-app/)
[info] Updating {file:/home/public/program/scala/self-cont-app/}self-cont-app...
[info] Resolving jline#jline;2.12.1 ...
[info] Done updating.
[info] Compiling 1 Scala source to /home/public/program/scala/self-cont-app/target/scala-2.11/classes...
[info] Packaging /home/public/program/scala/self-cont-app/target/scala-2.11/simple-project_2.11-1.0.jar ...
[info] Done packaging.
[success] Total time: 11 s, completed Sep 8, 2016 3:12:31 PM

运行构建的程序

$ spark-submit --class "SimpleApp" --master local[4] ./target/scala-2.11/simple-project_2.11-1.0.jar
SLF4J: Class path contains multiple SLF4J bindings.
...
Lines with a: 61, lines with b: 27