feat:ChatGPT第 1 课：Spark 是什么，以及第一个 Spark 程序

src/main/scala/org/exercises/demo/Demo2CreateRDD.scala

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+package org.exercises.demo
+
+import org.apache.spark.{SparkConf, SparkContext}
+
+object Demo2CreateRDD {
+  def main(args: Array[String]): Unit = {
+    val sc = new SparkContext(new SparkConf().setAppName("CreateRDD").setMaster("local"))
+    val nums = Seq(1, 2, 3, 4, 5)
+    val rdd = sc.parallelize(nums)
+    rdd.foreach(println)
+  }
+}

src/main/scala/org/exercises/demo/Demo3RddMap.scala

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+package org.exercises.demo
+
+import org.apache.spark.{SparkConf, SparkContext}
+
+object Demo3RddMap {
+  def main(args: Array[String]): Unit = {
+    val sc = new SparkContext(new SparkConf().setAppName("RddMap").setMaster("local"))
+    val rdd = sc.parallelize(List(1, 2, 3))
+    val result = rdd.map(_ + 1)
+    result.foreach(println)
+    println(result.collect().toList)
+  }
+}

src/main/scala/org/exercises/demo/DemoS1tart.scala

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+package org.exercises.demo
+
+import org.apache.spark.{SparkConf, SparkContext}
+
+import java.lang.Thread.sleep
+
+/*
+* 第 1 课：Spark 是什么，以及第一个 Spark 程序*/
+object DemoS1tart {
+  def main(args: Array[String]): Unit = {
+    val conf = new SparkConf()
+      .setMaster("local")
+      .setAppName("Spark01_Hello")
+    val sc = new SparkContext(conf)
+
+    println("Spark启动成功")
+    //    sleep(100000)
+    sc.stop()
+  }
+}

src/main/scala/org/exercises/exercises/Exercises1.scala

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+package org.exercises.exercises
+
+/*
+* 练习 1：创建 SparkContext
+要求：
+master = local
+appName = SparkExercise01
+创建：
+SparkContext*/
+
+import org.apache.spark.{SparkConf, SparkContext}
+
+object Exercises1 {
+  def main(args: Array[String]): Unit = {
+    val sc = new SparkContext(new SparkConf().setAppName("SparkExercise01").setMaster("local"))
+    sc.stop()
+  }
+}

src/main/scala/org/exercises/exercises/Exercises2.scala

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+package org.exercises.exercises
+
+/*
+* 练习 2：创建 RDD
+创建：
+1, 2, 3, 4, 5, 6
+的 RDD。*/
+
+import org.apache.spark.{SparkConf, SparkContext}
+
+object Exercises2 {
+  def main(args: Array[String]): Unit = {
+    val sc = new SparkContext(new SparkConf().setAppName("Exercises2").setMaster("local"))
+    val list = List(1, 2, 3, 4, 5, 6)
+    val rdd = sc.parallelize(list)
+    sc.stop()
+  }
+}

src/main/scala/org/exercises/exercises/Exercises3.scala

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+package org.exercises.exercises
+
+/*
+* 练习 3：filter
+筛选出偶数：
+2, 4, 6*/
+
+import org.apache.spark.{SparkConf, SparkContext}
+
+object Exercises3 {
+  def main(args: Array[String]): Unit = {
+    val sc = new SparkContext(new SparkConf().setAppName("Exercises3").setMaster("local"))
+    val list = List(1, 2, 3, 4, 5, 6)
+    val rdd = sc.parallelize(list)
+    val result = rdd.filter(_ % 2 == 0)
+    sc.stop()
+  }
+}

src/main/scala/org/exercises/exercises/Exercises4.scala

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+package org.exercises.exercises
+
+/*
+* 练习 4：map
+把偶数全部乘以 10：
+20, 40, 60*/
+
+import org.apache.spark.{SparkConf, SparkContext}
+
+object Exercises4 {
+  def main(args: Array[String]): Unit = {
+    val sc = new SparkContext(new SparkConf().setAppName("Exercises4").setMaster("local"))
+    val list = List(1, 2, 3, 4, 5, 6)
+    val rdd = sc.parallelize(list)
+    val result = rdd
+      .filter(_ % 2 == 0)
+      .map(_ * 10)
+    sc.stop()
+  }
+}

src/main/scala/org/exercises/exercises/Exercises5.scala

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+package org.exercises.exercises
+
+import org.apache.spark.{SparkConf, SparkContext}
+
+/*
+* 练习 5：Action
+使用：
+collect()
+把最终结果打印出来。
+最后应该得到：
+List(20, 40, 60)*/
+object Exercises5 {
+  def main(args: Array[String]): Unit = {
+    val sc = new SparkContext(new SparkConf().setAppName("Exercises5").setMaster("local"))
+    val list = List(1, 2, 3, 4, 5, 6)
+    val rdd = sc.parallelize(list)
+    val result = rdd.filter(_ % 2 == 0).map(_ * 10)
+    println(result.collect().toList)
+    sc.stop()
+  }
+}