IT俱乐部 Java Spark使用IDEA编写wordcount的示例演示

Spark使用IDEA编写wordcount的示例演示

发布: 2023年 7月 20日 148阅读

配置

Spark版本：3.2.0

Scala版本：2.12.12

JDK：1.8

Maven：3.6.3

pom文件

4.0.0com.zzjz.SparkSpark1.03.2.02.12org.apache.sparkspark-core_${scala.version}${spark.version}org.apache.sparkspark-streaming_${scala.version}${spark.version}org.apache.sparkspark-sql_${scala.version}${spark.version}org.apache.sparkspark-hive_${scala.version}${spark.version}org.apache.sparkspark-mllib_${scala.version}${spark.version}org.scala-toolsmaven-scala-plugin2.15.2compiletestCompilemaven-compiler-plugin3.6.01.81.8org.apache.maven.pluginsmaven-surefire-plugin2.19true

样例数据

9422850591,11603,39939,山西,邮件,人员
9422850591,116427,39911,山西,邮件,人员
9422850591,116437,39895,山西,邮件,人员

代码

import org.apache.spark.{SparkConf, SparkContext}  // 导入SparkConf和SparkContext类
object wcPerson {
  def main (args:Array[String]): Unit ={
    // 创建SparkConf对象，设置应用程序名称为"wcPerson"，运行模式为本地模式，使用一个CPU核心
    val conf = new SparkConf().setAppName("wcPerson").setMaster("local[1]")  
    // 创建SparkContext对象，与Spark集群进行通信
    val sc = new SparkContext(conf) 
    // 加载文件，将每一行作为一个字符串元素，返回一个RDD 
    val inputFile = sc.textFile("D:\workspace\spark\src\main\Data\person")  
    // 对RDD应用flatMap转换操作，将每一行按","分割成多个单词，并将所有单词扁平化为一个RDD
    val wc = inputFile.flatMap(line => line.split(","))  
    // 对RDD应用map转换操作，将每个单词映射为(key, value)的元组，其中key为单词本身，value为1
      .map(word => (word,1)) 
    // 对相同key的元组进行聚合操作，将相同key的value相加 
      .reduceByKey((a,b) => a + b) 
    // 打印输出聚合结果 
    wc.foreach(println)  
  }
}

运行结果

D:Javajdk1.8.0_131binjava.exe “-javaagent:D:ideaIntelliJ IDEA 2021.1.3libidea_rt.jar=52283:D:ideaIntelliJ IDEA 2021.1.3bin” -Dfile.encoding=UTF-8 -classpath “D:ideaIntelliJ IDEA 2021.1.3libidea_rt.jar” com.intellij.rt.execution.CommandLineWrapper C:UsersAdministratorAppDataLocalTempidea_classpath1156784809 wcPerson
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/D:/spark/spark-3.2.0-bin-hadoop2.7/jars/slf4j-log4j12-1.7.30.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/D:/Maven/Maven_repositories/org/slf4j/slf4j-log4j12/1.7.30/slf4j-log4j12-1.7.30.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
Using Spark’s default log4j profile: org/apache/spark/log4j-defaults.properties
23/07/11 10:00:01 INFO SparkContext: Running Spark version 3.2.0
23/07/11 10:00:01 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform… using builtin-java classes where applicable
23/07/11 10:00:02 INFO ResourceUtils: ==============================================================
23/07/11 10:00:02 INFO ResourceUtils: No custom resources configured for spark.driver.
23/07/11 10:00:02 INFO ResourceUtils: ==============================================================
23/07/11 10:00:02 INFO SparkContext: Submitted application: wcPerson
23/07/11 10:00:02 INFO ResourceProfile: Default ResourceProfile created, executor resources: Map(cores -> name: cores, amount: 1, script: , vendor: , memory -> name: memory, amount: 1024, script: , vendor: , offHeap -> name: offHeap, amount: 0, script: , vendor: ), task resources: Map(cpus -> name: cpus, amount: 1.0)
23/07/11 10:00:02 INFO ResourceProfile: Limiting resource is cpu
23/07/11 10:00:02 INFO ResourceProfileManager: Added ResourceProfile id: 0
23/07/11 10:00:02 INFO SecurityManager: Changing view acls to: Administrator
23/07/11 10:00:02 INFO SecurityManager: Changing modify acls to: Administrator
23/07/11 10:00:02 INFO SecurityManager: Changing view acls groups to: 
23/07/11 10:00:02 INFO SecurityManager: Changing modify acls groups to: 
23/07/11 10:00:02 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(Administrator); groups with view permissions: Set(); users  with modify permissions: Set(Administrator); groups with modify permissions: Set()
23/07/11 10:00:07 INFO Utils: Successfully started service ‘sparkDriver’ on port 52323.
23/07/11 10:00:07 INFO SparkEnv: Registering MapOutputTracker
23/07/11 10:00:07 INFO SparkEnv: Registering BlockManagerMaster
23/07/11 10:00:07 INFO BlockManagerMasterEndpoint: Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
23/07/11 10:00:07 INFO BlockManagerMasterEndpoint: BlockManagerMasterEndpoint up
23/07/11 10:00:07 INFO SparkEnv: Registering BlockManagerMasterHeartbeat
23/07/11 10:00:07 INFO DiskBlockManager: Created local directory at C:UsersAdministratorAppDataLocalTempblockmgr-0052575b-7c9f-457e-9ed5-fb50af59f965
23/07/11 10:00:07 INFO MemoryStore: MemoryStore started with capacity 623.4 MiB
23/07/11 10:00:07 INFO SparkEnv: Registering OutputCommitCoordinator
23/07/11 10:00:07 INFO Utils: Successfully started service ‘SparkUI’ on port 4040.
23/07/11 10:00:08 INFO SparkUI: Bound SparkUI to 0.0.0.0, and started at http://zzjz:4040
23/07/11 10:00:08 INFO Executor: Starting executor ID driver on host zzjz
23/07/11 10:00:08 INFO Utils: Successfully started service ‘org.apache.spark.network.netty.NettyBlockTransferService’ on port 52339.
23/07/11 10:00:08 INFO NettyBlockTransferService: Server created on zzjz:52339
23/07/11 10:00:08 INFO BlockManager: Using org.apache.spark.storage.RandomBlockReplicationPolicy for block replication policy
23/07/11 10:00:08 INFO BlockManagerMaster: Registering BlockManager BlockManagerId(driver, zzjz, 52339, None)
23/07/11 10:00:08 INFO BlockManagerMasterEndpoint: Registering block manager zzjz:52339 with 623.4 MiB RAM, BlockManagerId(driver, zzjz, 52339, None)
23/07/11 10:00:08 INFO BlockManagerMaster: Registered BlockManager BlockManagerId(driver, zzjz, 52339, None)
23/07/11 10:00:08 INFO BlockManager: Initialized BlockManager: BlockManagerId(driver, zzjz, 52339, None)
23/07/11 10:00:10 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 244.0 KiB, free 623.2 MiB)
23/07/11 10:00:10 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 23.4 KiB, free 623.1 MiB)
23/07/11 10:00:10 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on zzjz:52339 (size: 23.4 KiB, free: 623.4 MiB)
23/07/11 10:00:10 INFO SparkContext: Created broadcast 0 from textFile at wcPerson.scala:7
23/07/11 10:00:10 INFO FileInputFormat: Total input paths to process : 1
23/07/11 10:00:10 INFO SparkContext: Starting job: foreach at wcPerson.scala:10
23/07/11 10:00:11 INFO DAGScheduler: Registering RDD 3 (map at wcPerson.scala:9) as input to shuffle 0
23/07/11 10:00:11 INFO DAGScheduler: Got job 0 (foreach at wcPerson.scala:10) with 1 output partitions
23/07/11 10:00:11 INFO DAGScheduler: Final stage: ResultStage 1 (foreach at wcPerson.scala:10)
23/07/11 10:00:11 INFO DAGScheduler: Parents of final stage: List(ShuffleMapStage 0)
23/07/11 10:00:11 INFO DAGScheduler: Missing parents: List(ShuffleMapStage 0)
23/07/11 10:00:11 INFO DAGScheduler: Submitting ShuffleMapStage 0 (MapPartitionsRDD[3] at map at wcPerson.scala:9), which has no missing parents
23/07/11 10:00:11 INFO MemoryStore: Block broadcast_1 stored as values in memory (estimated size 6.9 KiB, free 623.1 MiB)
23/07/11 10:00:11 INFO MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 4.0 KiB, free 623.1 MiB)
23/07/11 10:00:11 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on zzjz:52339 (size: 4.0 KiB, free: 623.4 MiB)
23/07/11 10:00:11 INFO SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:1427
23/07/11 10:00:11 INFO DAGScheduler: Submitting 1 missing tasks from ShuffleMapStage 0 (MapPartitionsRDD[3] at map at wcPerson.scala:9) (first 15 tasks are for partitions Vector(0))
23/07/11 10:00:11 INFO TaskSchedulerImpl: Adding task set 0.0 with 1 tasks resource profile 0
23/07/11 10:00:11 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0) (zzjz, executor driver, partition 0, PROCESS_LOCAL, 4503 bytes) taskResourceAssignments Map()
23/07/11 10:00:11 INFO Executor: Running task 0.0 in stage 0.0 (TID 0)
23/07/11 10:00:12 INFO HadoopRDD: Input split: file:/D:/workspace/spark/src/main/Data/person:0+135
23/07/11 10:00:12 INFO Executor: Finished task 0.0 in stage 0.0 (TID 0). 1325 bytes result sent to driver
23/07/11 10:00:12 INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 1022 ms on zzjz (executor driver) (1/1)
23/07/11 10:00:12 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool 
23/07/11 10:00:12 INFO DAGScheduler: ShuffleMapStage 0 (map at wcPerson.scala:9) finished in 1.263 s
23/07/11 10:00:12 INFO DAGScheduler: looking for newly runnable stages
23/07/11 10:00:12 INFO DAGScheduler: running: Set()
23/07/11 10:00:12 INFO DAGScheduler: waiting: Set(ResultStage 1)
23/07/11 10:00:12 INFO DAGScheduler: failed: Set()
23/07/11 10:00:12 INFO DAGScheduler: Submitting ResultStage 1 (ShuffledRDD[4] at reduceByKey at wcPerson.scala:9), which has no missing parents
23/07/11 10:00:12 INFO MemoryStore: Block broadcast_2 stored as values in memory (estimated size 5.3 KiB, free 623.1 MiB)
23/07/11 10:00:12 INFO MemoryStore: Block broadcast_2_piece0 stored as bytes in memory (estimated size 3.1 KiB, free 623.1 MiB)
23/07/11 10:00:12 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on zzjz:52339 (size: 3.1 KiB, free: 623.4 MiB)
23/07/11 10:00:12 INFO SparkContext: Created broadcast 2 from broadcast at DAGScheduler.scala:1427
23/07/11 10:00:12 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 1 (ShuffledRDD[4] at reduceByKey at wcPerson.scala:9) (first 15 tasks are for partitions Vector(0))
23/07/11 10:00:12 INFO TaskSchedulerImpl: Adding task set 1.0 with 1 tasks resource profile 0
23/07/11 10:00:12 INFO TaskSetManager: Starting task 0.0 in stage 1.0 (TID 1) (zzjz, executor driver, partition 0, NODE_LOCAL, 4271 bytes) taskResourceAssignments Map()
23/07/11 10:00:12 INFO Executor: Running task 0.0 in stage 1.0 (TID 1)
23/07/11 10:00:12 INFO ShuffleBlockFetcherIterator: Getting 1 (142.0 B) non-empty blocks including 1 (142.0 B) local and 0 (0.0 B) host-local and 0 (0.0 B) push-merged-local and 0 (0.0 B) remote blocks
23/07/11 10:00:12 INFO ShuffleBlockFetcherIterator: Started 0 remote fetches in 20 ms
(116437,1)
(39911,1)
(116427,1)
(9422850591,3)
(39895,1)
(山西,3)
(11603,1)
(39939,1)
(人员,3)
(邮件,3)
23/07/11 10:00:12 INFO Executor: Finished task 0.0 in stage 1.0 (TID 1). 1224 bytes result sent to driver
23/07/11 10:00:12 INFO TaskSetManager: Finished task 0.0 in stage 1.0 (TID 1) in 123 ms on zzjz (executor driver) (1/1)
23/07/11 10:00:12 INFO TaskSchedulerImpl: Removed TaskSet 1.0, whose tasks have all completed, from pool 
23/07/11 10:00:12 INFO DAGScheduler: ResultStage 1 (foreach at wcPerson.scala:10) finished in 0.153 s
23/07/11 10:00:12 INFO DAGScheduler: Job 0 is finished. Cancelling potential speculative or zombie tasks for this job
23/07/11 10:00:12 INFO TaskSchedulerImpl: Killing all running tasks in stage 1: Stage finished
23/07/11 10:00:12 INFO DAGScheduler: Job 0 finished: foreach at wcPerson.scala:10, took 2.044775 s
23/07/11 10:00:12 INFO SparkContext: Invoking stop() from shutdown hook
23/07/11 10:00:12 INFO SparkUI: Stopped Spark web UI at http://zzjz:4040
23/07/11 10:00:12 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
23/07/11 10:00:12 INFO MemoryStore: MemoryStore cleared
23/07/11 10:00:12 INFO BlockManager: BlockManager stopped
23/07/11 10:00:12 INFO BlockManagerMaster: BlockManagerMaster stopped
23/07/11 10:00:12 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
23/07/11 10:00:12 INFO SparkContext: Successfully stopped SparkContext
23/07/11 10:00:12 INFO ShutdownHookManager: Shutdown hook called
23/07/11 10:00:12 INFO ShutdownHookManager: Deleting directory C:UsersAdministratorAppDataLocalTempspark-9f3eb32d-30f7-44d6-8751-f668b2710d89
Process finished with exit code 0

到此这篇关于Spark使用IDEA编写wordcount demo的文章就介绍到这了,更多相关idea编写wordcount内容请搜索IT俱乐部以前的文章或继续浏览下面的相关文章希望大家以后多多支持IT俱乐部！

本文收集自网络，不代表IT俱乐部立场，转载请注明出处。https://www.2it.club/code/java/8747.html
21赞
标签:
上一篇
下一篇

相关推荐

联系我们

联系我们

在线咨询: QQ交谈

邮箱: 1120393934@qq.com

工作时间：周一至周五，9:00-17:30，节假日休息

关注微信
微信扫一扫关注我们

微信扫一扫关注我们

返回顶部