配置
Spark版本：3.2.0
Scala版本：2.12.12
JDK：1.8
Maven：3.6.3
文章来源：https://www.toymoban.com/news/detail-550437.html
pom文件1
Spark版本：3.2.0
Scala版本：2.12.12
JDK：1.8
Maven：3.6.3
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.zzjz.Spark</groupId>
<artifactId>Spark</artifactId>
<version>1.0</version>
<properties>
<spark.version>3.2.0</spark.version>
<scala.version>2.12</scala.version>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_${scala.version}</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_${scala.version}</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_${scala.version}</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-hive_${scala.version}</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-mllib_${scala.version}</artifactId>
<version>${spark.version}</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.scala-tools</groupId>
<artifactId>maven-scala-plugin</artifactId>
<version>2.15.2</version>
<executions>
<execution>
<goals>
<goal>compile</goal>
<goal>testCompile</goal>
</goals>
</execution>
</executions>
</plugin>
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.6.0</version>
<configuration>
<source>1.8</source>
<target>1.8</target>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-surefire-plugin</artifactId>
<version>2.19</version>
<configuration>
<skip>true</skip>
</configuration>
</plugin>
</plugins>
</build>
</project>POM文件2
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>org.example</groupId>
<artifactId>sparklx</artifactId>
<version>1.0</version>
<name>sparklx</name>
<!-- FIXME change it to the project's website -->
<url>http://www.example.com</url>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<maven.compiler.source>1.8</maven.compiler.source>
<maven.compiler.target>1.8</maven.compiler.target>
<scala.version>2.12.12</scala.version> <!-- 将 Scala 版本更新为 2.12.12 -->
<spark.version>2.4.3</spark.version> <!-- 保持原始的 Spark 版本 -->
</properties>
<dependencies>
<!-- ... 其他依赖 ... -->
<!-- 导入 Scala 和 Spark 的依赖 -->
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
<version>${scala.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.12</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.12</artifactId>
<version>${spark.version}</version>
</dependency>
</dependencies>
<build>
<pluginManagement><!-- lock down plugins versions to avoid using Maven defaults (may be moved to parent pom) -->
<plugins>
<!-- clean lifecycle, see https://maven.apache.org/ref/current/maven-core/lifecycles.html#clean_Lifecycle -->
<plugin>
<artifactId>maven-clean-plugin</artifactId>
<version>3.1.0</version>
</plugin>
<!-- default lifecycle, jar packaging: see https://maven.apache.org/ref/current/maven-core/default-bindings.html#Plugin_bindings_for_jar_packaging -->
<plugin>
<artifactId>maven-resources-plugin</artifactId>
<version>3.0.2</version>
</plugin>
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.8.0</version>
</plugin>
<plugin>
<artifactId>maven-surefire-plugin</artifactId>
<version>2.22.1</version>
</plugin>
<plugin>
<artifactId>maven-jar-plugin</artifactId>
<version>3.0.2</version>
</plugin>
<plugin>
<artifactId>maven-install-plugin</artifactId>
<version>2.5.2</version>
</plugin>
<plugin>
<artifactId>maven-deploy-plugin</artifactId>
<version>2.8.2</version>
</plugin>
<!-- site lifecycle, see https://maven.apache.org/ref/current/maven-core/lifecycles.html#site_Lifecycle -->
<plugin>
<artifactId>maven-site-plugin</artifactId>
<version>3.7.1</version>
</plugin>
<plugin>
<artifactId>maven-project-info-reports-plugin</artifactId>
<version>3.0.0</version>
</plugin>
<!-- Scala compiler plugin -->
<plugin>
<groupId>net.alchim31.maven</groupId>
<artifactId>scala-maven-plugin</artifactId>
<version>4.4.0</version>
<executions>
<execution>
<goals>
<goal>compile</goal>
<goal>testCompile</goal>
</goals>
</execution>
</executions>
</plugin>
</plugins>
</pluginManagement>
</build>
</project>
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
文章来源地址https://www.toymoban.com/news/detail-550437.html
D:\Java\jdk1.8.0_131\bin\java.exe "-javaagent:D:\idea\IntelliJ IDEA 2021.1.3\lib\idea_rt.jar=52283:D:\idea\IntelliJ IDEA 2021.1.3\bin" -Dfile.encoding=UTF-8 -classpath "D:\idea\IntelliJ IDEA 2021.1.3\lib\idea_rt.jar" com.intellij.rt.execution.CommandLineWrapper C:\Users\Administrator\AppData\Local\Temp\idea_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:\Users\Administrator\AppData\Local\Temp\blockmgr-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:\Users\Administrator\AppData\Local\Temp\spark-9f3eb32d-30f7-44d6-8751-f668b2710d89
Process finished with exit code 0
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