林子雨编著《大数据基础编程、实验和案例教程》(教材官网)教材中的代码，在纸质教材中的印刷效果不是很好，可能会影响读者对代码的理解，为了方便读者正确理解代码或者直接拷贝代码用于上机实验，这里提供全书配套的所有代码。
查看教材所有章节的代码
第9章 Spark的安装和基础编程
教材第170页
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sudo tar -zxf ~/下载/spark-1.6.2-bin-without-hadoop.tgz -C /usr/local/
cd /usr/local
sudo mv ./spark-1.6.2-bin-without-hadoop/ ./spark
sudo chown -R hadoop:hadoop ./spark # hadoop是当前登录Linux系统的用户名
cd /usr/local/spark
cp ./conf/spark-env.sh.template ./conf/spark-env.sh
教材第171页
export SPARK_DIST_CLASSPATH=$(/usr/local/hadoop/bin/hadoop classpath)
cd /usr/local/spark
bin/run-example SparkPi
bin/run-example SparkPi 2>&1 | grep "Pi is roughly"
教材第172页
cd /usr/local/spark
./bin/spark-shell
scala> 8*2+5
res0: Int = 21
scala>:quit
cd /usr/local/spark
./bin/spark-shell
scala> val textFile = sc.textFile("file:///usr/local/spark/README.md")
scala> textFile.first()
教材第173页
cd /usr/local/hadoop
./sbin/start-dfs.sh
cd /usr/local/hadoop
./bin/hdfs dfs –put /usr/local/spark/README.md .
./bin/hdfs dfs –cat README.md
scala> val textFile = sc.textFile("hdfs://localhost:9000/user/hadoop/README.md")
scala> textFile.first()
scala> val textFile = sc.textFile("hdfs://localhost:9000/user/hadoop/ README.md ")
scala> val textFile = sc.textFile("/user/hadoop/ README.md ")
scala> val textFile = sc.textFile("README.md ")
教材第174页
scala> val textFile = sc.textFile("file:///usr/local/spark/ README.md ")
scala> val wordCount = textFile.flatMap(line => line.split(" ")).map(word => (word, 1)).reduceByKey((a, b) => a + b)
scala> wordCount.collect()
教材第175页
https://repo.typesafe.com/typesafe/ivy-releases/org.scala-sbt/sbt-launch/0.13.11/sbt-launch.jar
sudo mkdir /usr/local/sbt
sudo chown -R hadoop /usr/local/sbt # 此处的hadoop是Linux系统当前登录用户名
cd /usr/local/sbt
cp ~/下载/sbt-launch.jar .
vim ./sbt
#!/bin/bash
SBT_OPTS="-Xms512M -Xmx1536M -Xss1M -XX:+CMSClassUnloadingEnabled -XX:MaxPermSize=256M"
java $SBT_OPTS -jar `dirname $0`/sbt-launch.jar "$@"
chmod u+x ./sbt
./sbt sbt-version
教材第176页
cd ~ # 进入用户主文件夹
mkdir ./sparkapp # 创建应用程序根目录
mkdir -p ./sparkapp/src/main/scala # 创建所需的文件夹结构
cd ~
vim ./sparkapp/src/main/scala/SimpleApp.scala
/* SimpleApp.scala */
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:///usr/local/spark/README.md" // Should be some file on your system
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))
}
}
教材第177页
cd ~
vim ./sparkapp/simple.sbt
name := "Simple Project"
version := "1.0"
scalaVersion := "2.10.5"
libraryDependencies += "org.apache.spark" %% "spark-core" % "1.6.2"
cd ~/sparkapp
find .
cd ~/sparkapp #一定把这个目录设置为当前目录
/usr/local/sbt/sbt package
教材第178页
/usr/local/spark/bin/spark-submit --class "SimpleApp" ~/sparkapp/target/scala-2.10/simple-project_2.10-1.0.jar
/usr/local/spark/bin/spark-submit --class "SimpleApp" ~/sparkapp/target/scala-2.10/simple-project_2.10-1.0.jar 2>&1 | grep "Lines with a:"
教材第179页
http://apache.fayea.com/maven/maven-3/3.3.9/binaries/apache-maven-3.3.9-bin.zip
sudo unzip ~/下载/apache-maven-3.3.9-bin.zip -d /usr/local
cd /usr/local
sudo mv apache-maven-3.3.9/ ./maven
sudo chown -R hadoop ./maven
cd ~ #进入用户主文件夹
mkdir -p ./sparkapp2/src/main/java
vim ./sparkapp2/src/main/java/SimpleApp.java
/*** SimpleApp.java ***/
import org.apache.spark.api.java.*;
import org.apache.spark.api.java.function.Function;
public class SimpleApp {
public static void main(String[] args) {
String logFile = "file:///usr/local/spark/README.md"; // Should be some file on your system
JavaSparkContext sc = new JavaSparkContext("local", "Simple App",
"file:///usr/local/spark/", new String[]{"target/simple-project-1.0.jar"});
JavaRDD<String> logData = sc.textFile(logFile).cache();
long numAs = logData.filter(new Function<String, Boolean>() {
public Boolean call(String s) { return s.contains("a"); }
}).count();
long numBs = logData.filter(new Function<String, Boolean>() {
public Boolean call(String s) { return s.contains("b"); }
}).count();
System.out.println("Lines with a: " + numAs + ", lines with b: " + numBs);
}
}
教材第180页
cd ~
vim ./sparkapp2/pom.xml
<project>
<groupId>edu.berkeley</groupId>
<artifactId>simple-project</artifactId>
<modelVersion>4.0.0</modelVersion>
<name>Simple Project</name>
<packaging>jar</packaging>
<version>1.0</version>
<repositories>
<repository>
<id>Akka repository</id>
<url>http://repo.akka.io/releases</url>
</repository>
</repositories>
<dependencies>
<dependency> <!-- Spark dependency -->
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.10</artifactId>
<version>1.6.2</version>
</dependency>
</dependencies>
</project>
教材第181页
cd ~/sparkapp2
find .
cd ~/sparkapp2 #一定把这个目录设置为当前目录
/usr/local/maven/bin/mvn package
/usr/local/spark/bin/spark-submit --class "SimpleApp" ~/sparkapp2/target/simple-project-1.0.jar
/usr/local/spark/bin/spark-submit --class "SimpleApp" ~/sparkapp2/target/simple-project-1.0.jar 2>&1 | grep "Lines with a"