Question

我花了好几个小时通过You Tube vids和教程试图了解我如何在Scala中运行Spark运行字数统计程序，并将其转换为jar文件。我现在变得非常困惑。

我运行了Hello World，并且我已经了解了要在Apache.spark.spark-core中添加库，但现在我已经

了

Error: Could not find or load main class WordCount

更进一步，我完全不知道为什么这两个我认为我们教导相同的教程看起来差异很大：tutorial1 tutorial2

第二个似乎是第一个的两倍，它抛出了第一个没有提及的东西。我是否应该依赖其中任何一个来帮助我获得一个简单的字数统计程序并运行并运行？

聚苯乙烯。我的代码目前看起来像这样。我从某个地方复制了它：

import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._
import org.apache.spark._

object WordCount {
  def main(args: Array[String]) {

    val sc = new SparkContext( "local", "Word Count", "/usr/local/spark", Nil, Map(), Map())
    val input = sc.textFile("../Data/input.txt")
    val count = input.flatMap(line ⇒ line.split(" "))
      .map(word ⇒ (word, 1))
      .reduceByKey(_ + _)
    count.saveAsTextFile("outfile")
    System.out.println("OK");
  }
}

Answer 1

在IntelliJ Idea do File中 - ＆gt;新 - ＆gt;项目 - ＆gt; Scala - ＆gt; SBT - ＆gt; （选择项目的位置和名称） - ＆gt;完成。

写在build.sbt

scalaVersion := "2.11.11"
libraryDependencies += "org.apache.spark" % "spark-core_2.11" % "2.2.0"

在命令行中执行sbt update（在主项目文件夹中）或在IntelliJ Idea中的SBT工具窗口中按刷新按钮。

在src/main/scala/WordCount.scala

中编写代码

import org.apache.spark.{SparkConf, SparkContext}

object WordCount {
  def main(args: Array[String]) {
    val conf = new SparkConf()
      .setMaster("local")
      .setAppName("Word Count")
      .setSparkHome("src/main/resources")
    val sc = new SparkContext(conf)
    val input = sc.textFile("src/main/resources/input.txt")
    val count = input.flatMap(line ⇒ line.split(" "))
      .map(word ⇒ (word, 1))
      .reduceByKey(_ + _)
    count.saveAsTextFile("src/main/resources/outfile")
    println("OK")
  }
}

将您的文件设为src/main/resources/input.txt

运行您的代码：Ctrl + Shift + F10或sbt run

在文件夹src/main/resources中，应该会显示包含多个文件的新子文件夹outfile。

控制台输出：

Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
17/09/02 14:57:08 INFO SparkContext: Running Spark version 2.2.0
17/09/02 14:57:09 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
17/09/02 14:57:09 WARN Utils: Your hostname, dmitin-HP-Pavilion-Notebook resolves to a loopback address: 127.0.1.1; using 192.168.1.104 instead (on interface wlan0)
17/09/02 14:57:09 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
17/09/02 14:57:09 INFO SparkContext: Submitted application: Word Count
17/09/02 14:57:09 INFO SecurityManager: Changing view acls to: dmitin
17/09/02 14:57:09 INFO SecurityManager: Changing modify acls to: dmitin
17/09/02 14:57:09 INFO SecurityManager: Changing view acls groups to: 
17/09/02 14:57:09 INFO SecurityManager: Changing modify acls groups to: 
17/09/02 14:57:09 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(dmitin); groups with view permissions: Set(); users  with modify permissions: Set(dmitin); groups with modify permissions: Set()
17/09/02 14:57:10 INFO Utils: Successfully started service 'sparkDriver' on port 38186.
17/09/02 14:57:10 INFO SparkEnv: Registering MapOutputTracker
17/09/02 14:57:10 INFO SparkEnv: Registering BlockManagerMaster
17/09/02 14:57:10 INFO BlockManagerMasterEndpoint: Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
17/09/02 14:57:10 INFO BlockManagerMasterEndpoint: BlockManagerMasterEndpoint up
17/09/02 14:57:10 INFO DiskBlockManager: Created local directory at /tmp/blockmgr-d90a4735-6a2b-42b2-85ea-55b0ed9b1dfd
17/09/02 14:57:10 INFO MemoryStore: MemoryStore started with capacity 1950.3 MB
17/09/02 14:57:10 INFO SparkEnv: Registering OutputCommitCoordinator
17/09/02 14:57:10 INFO Utils: Successfully started service 'SparkUI' on port 4040.
17/09/02 14:57:11 INFO SparkUI: Bound SparkUI to 0.0.0.0, and started at http://192.168.1.104:4040
17/09/02 14:57:11 INFO Executor: Starting executor ID driver on host localhost
17/09/02 14:57:11 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 46432.
17/09/02 14:57:11 INFO NettyBlockTransferService: Server created on 192.168.1.104:46432
17/09/02 14:57:11 INFO BlockManager: Using org.apache.spark.storage.RandomBlockReplicationPolicy for block replication policy
17/09/02 14:57:11 INFO BlockManagerMaster: Registering BlockManager BlockManagerId(driver, 192.168.1.104, 46432, None)
17/09/02 14:57:11 INFO BlockManagerMasterEndpoint: Registering block manager 192.168.1.104:46432 with 1950.3 MB RAM, BlockManagerId(driver, 192.168.1.104, 46432, None)
17/09/02 14:57:11 INFO BlockManagerMaster: Registered BlockManager BlockManagerId(driver, 192.168.1.104, 46432, None)
17/09/02 14:57:11 INFO BlockManager: Initialized BlockManager: BlockManagerId(driver, 192.168.1.104, 46432, None)
17/09/02 14:57:12 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 214.5 KB, free 1950.1 MB)
17/09/02 14:57:12 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 20.4 KB, free 1950.1 MB)
17/09/02 14:57:12 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on 192.168.1.104:46432 (size: 20.4 KB, free: 1950.3 MB)
17/09/02 14:57:12 INFO SparkContext: Created broadcast 0 from textFile at WordCount.scala:16
17/09/02 14:57:12 INFO FileInputFormat: Total input paths to process : 1
17/09/02 14:57:12 INFO SparkContext: Starting job: saveAsTextFile at WordCount.scala:20
17/09/02 14:57:12 INFO DAGScheduler: Registering RDD 3 (map at WordCount.scala:18)
17/09/02 14:57:12 INFO DAGScheduler: Got job 0 (saveAsTextFile at WordCount.scala:20) with 1 output partitions
17/09/02 14:57:12 INFO DAGScheduler: Final stage: ResultStage 1 (saveAsTextFile at WordCount.scala:20)
17/09/02 14:57:12 INFO DAGScheduler: Parents of final stage: List(ShuffleMapStage 0)
17/09/02 14:57:12 INFO DAGScheduler: Missing parents: List(ShuffleMapStage 0)
17/09/02 14:57:12 INFO DAGScheduler: Submitting ShuffleMapStage 0 (MapPartitionsRDD[3] at map at WordCount.scala:18), which has no missing parents
17/09/02 14:57:13 INFO MemoryStore: Block broadcast_1 stored as values in memory (estimated size 4.7 KB, free 1950.1 MB)
17/09/02 14:57:13 INFO MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 2.7 KB, free 1950.1 MB)
17/09/02 14:57:13 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on 192.168.1.104:46432 (size: 2.7 KB, free: 1950.3 MB)
17/09/02 14:57:13 INFO SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:1006
17/09/02 14:57:13 INFO DAGScheduler: Submitting 1 missing tasks from ShuffleMapStage 0 (MapPartitionsRDD[3] at map at WordCount.scala:18) (first 15 tasks are for partitions Vector(0))
17/09/02 14:57:13 INFO TaskSchedulerImpl: Adding task set 0.0 with 1 tasks
17/09/02 14:57:13 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, localhost, executor driver, partition 0, PROCESS_LOCAL, 4873 bytes)
17/09/02 14:57:13 INFO Executor: Running task 0.0 in stage 0.0 (TID 0)
17/09/02 14:57:13 INFO HadoopRDD: Input split: file:/home/dmitin/Projects/sparkdemo/src/main/resources/input.txt:0+11
17/09/02 14:57:13 INFO Executor: Finished task 0.0 in stage 0.0 (TID 0). 1154 bytes result sent to driver
17/09/02 14:57:13 INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 289 ms on localhost (executor driver) (1/1)
17/09/02 14:57:13 INFO DAGScheduler: ShuffleMapStage 0 (map at WordCount.scala:18) finished in 0,321 s
17/09/02 14:57:13 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool 
17/09/02 14:57:13 INFO DAGScheduler: looking for newly runnable stages
17/09/02 14:57:13 INFO DAGScheduler: running: Set()
17/09/02 14:57:13 INFO DAGScheduler: waiting: Set(ResultStage 1)
17/09/02 14:57:13 INFO DAGScheduler: failed: Set()
17/09/02 14:57:13 INFO DAGScheduler: Submitting ResultStage 1 (MapPartitionsRDD[5] at saveAsTextFile at WordCount.scala:20), which has no missing parents
17/09/02 14:57:13 INFO MemoryStore: Block broadcast_2 stored as values in memory (estimated size 65.3 KB, free 1950.0 MB)
17/09/02 14:57:13 INFO MemoryStore: Block broadcast_2_piece0 stored as bytes in memory (estimated size 23.3 KB, free 1950.0 MB)
17/09/02 14:57:13 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on 192.168.1.104:46432 (size: 23.3 KB, free: 1950.3 MB)
17/09/02 14:57:13 INFO SparkContext: Created broadcast 2 from broadcast at DAGScheduler.scala:1006
17/09/02 14:57:13 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 1 (MapPartitionsRDD[5] at saveAsTextFile at WordCount.scala:20) (first 15 tasks are for partitions Vector(0))
17/09/02 14:57:13 INFO TaskSchedulerImpl: Adding task set 1.0 with 1 tasks
17/09/02 14:57:13 INFO TaskSetManager: Starting task 0.0 in stage 1.0 (TID 1, localhost, executor driver, partition 0, ANY, 4621 bytes)
17/09/02 14:57:13 INFO Executor: Running task 0.0 in stage 1.0 (TID 1)
17/09/02 14:57:13 INFO ShuffleBlockFetcherIterator: Getting 1 non-empty blocks out of 1 blocks
17/09/02 14:57:13 INFO ShuffleBlockFetcherIterator: Started 0 remote fetches in 10 ms
17/09/02 14:57:13 INFO FileOutputCommitter: Saved output of task 'attempt_20170902145712_0001_m_000000_1' to file:/home/dmitin/Projects/sparkdemo/src/main/resources/outfile/_temporary/0/task_20170902145712_0001_m_000000
17/09/02 14:57:13 INFO SparkHadoopMapRedUtil: attempt_20170902145712_0001_m_000000_1: Committed
17/09/02 14:57:13 INFO Executor: Finished task 0.0 in stage 1.0 (TID 1). 1224 bytes result sent to driver
17/09/02 14:57:13 INFO TaskSetManager: Finished task 0.0 in stage 1.0 (TID 1) in 221 ms on localhost (executor driver) (1/1)
17/09/02 14:57:13 INFO TaskSchedulerImpl: Removed TaskSet 1.0, whose tasks have all completed, from pool 
17/09/02 14:57:13 INFO DAGScheduler: ResultStage 1 (saveAsTextFile at WordCount.scala:20) finished in 0,223 s
17/09/02 14:57:13 INFO DAGScheduler: Job 0 finished: saveAsTextFile at WordCount.scala:20, took 1,222133 s
OK
17/09/02 14:57:13 INFO SparkContext: Invoking stop() from shutdown hook
17/09/02 14:57:13 INFO SparkUI: Stopped Spark web UI at http://192.168.1.104:4040
17/09/02 14:57:13 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
17/09/02 14:57:13 INFO MemoryStore: MemoryStore cleared
17/09/02 14:57:13 INFO BlockManager: BlockManager stopped
17/09/02 14:57:13 INFO BlockManagerMaster: BlockManagerMaster stopped
17/09/02 14:57:13 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
17/09/02 14:57:13 INFO SparkContext: Successfully stopped SparkContext
17/09/02 14:57:13 INFO ShutdownHookManager: Shutdown hook called
17/09/02 14:57:13 INFO ShutdownHookManager: Deleting directory /tmp/spark-663047b2-415a-45b5-bcad-20bd18270baa

Process finished with exit code 0

Answer 2

你总是可以做WordCount扩展App，这应该工作。我相信你的项目结构方式。

在此处详细了解应用特征。

http://www.scala-lang.org/api/2.12.1/scala/App.html

在任何情况下，请确保您的目录布局如下所示。

./ build.sbt
./src
./src/main
./src/main/scala
./src/main/scala/WordCount.scala

Answer 3

检查下面显示的示例代码

package com.spark.app

import org.scalatra._
import org.apache.spark.{ SparkContext, SparkConf }

class MySparkAppServlet extends MySparkAppStack {

  get("/wc") {
        val inputFile = "/home/limitless/Documents/projects/test/my-spark-app/README.md"
        val outputFile = "/home/limitless/Documents/projects/test/my-spark-app/README.txt"
        val conf = new SparkConf().setAppName("wordCount").setMaster("local[*]")
        val sc = new SparkContext(conf)
        val input =  sc.textFile(inputFile)
        val words = input.flatMap(line => line.split(" "))
        val counts = words.map(word => (word, 1)).reduceByKey{case (x, y) => x + y}
        counts.saveAsTextFile(outputFile)
    }

}

Answer 4

package com.application.spark

import org.apache.spark
import org.apache.spark.sql.SparkSession
import org.apache.spark.{SparkConf, SparkContext}

object WordCountDemo {
  def main(args: Array[String]): Unit = {
    //With using SparkContext
    val inputFile = "/Users/arupprasad/Desktop/MyFirstApplicationWithSpark1/src/main/resources/WordCountFile.txt"
    val outputFile = "/Users/arupprasad/Desktop/MyFirstApplicationWithSpark1/src/main/resources/WordCountOutput"
    val conf = new SparkConf().setAppName("wordCount").setMaster("local[*]")
    val sc = new SparkContext(conf)
    val input =  sc.textFile(inputFile)
    val words = input.flatMap(line => line.split(" "))
    val counts = words.map(word => (word, 1)).reduceByKey{case (x, y) => x + y}

    counts.saveAsTextFile(outputFile)

    //With using SparkSession
    val sparkSession = SparkSession.builder.master("local").appName("Scala Spark Example").getOrCreate()

    // import sparkSession.implicits._
    val sparkContext = sparkSession.sparkContext

    val inputFile = "/Users/arupprasad/Desktop/MyFirstApplicationWithSpark1/src/main/resources/WordCountFile.txt"
    val outputFile = "/Users/arupprasad/Desktop/MyFirstApplicationWithSpark1/src/main/resources/WordCountOutput"
    val input =  sparkContext.textFile(inputFile)
    val words = input.flatMap(line => line.split(" "))
    val counts = words.map(word => (word, 1)).reduceByKey{case (x, y) => x + y}

    counts.saveAsTextFile(outputFile)
  }
}

在IntelliJ中运行Spark字数

4 个答案: