Spark高效数据分析01、idea开发环境搭建
📋前言📋
💝博客：【红目香薰的博客_CSDN博客-计算机理论,2022年蓝桥杯,MySQL领域博主】💝
✍本文由在下【红目香薰】原创，首发于CSDN✍
🤗2022年最大愿望：【服务百万技术人次】🤗
💝Spark初始环境地址：【Spark高效数据分析01、idea开发环境搭建】💝
环境需求
环境：win10
开发工具：IntelliJ IDEA 2020.1.3 x64
maven版本：3.0.5
环境搭建
创建maven项目
起一个名字
只要是【3.0】以上的版本都可以正常使用
【settings.xml】这里使用的是阿里的镜像位置，默认库位置在【D:\maven\repository】
<?xml version="1.0" encoding="UTF-8"?>
<settings xmlns="http://maven.apache.org/SETTINGS/1.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/SETTINGS/1.0.0 http://maven.apache.org/xsd/settings-1.0.0.xsd">
<localRepository>D:\maven\repository</localRepository>
<pluginGroups>
</pluginGroups>
<proxies>
</proxies>
<servers>
</servers>
<mirrors>
<!-- 阿里云镜像 -->
<mirror>
<id>alimaven</id>
<name>aliyun maven</name>
<url>http://maven.aliyun.com/nexus/content/repositories/central/</url>
<mirrorOf>central</mirrorOf>
</mirror>
<!-- junit镜像地址 -->
<mirror>
<id>junit</id>
<name>junit Address/</name>
<url>http://jcenter.bintray.com/</url>
<mirrorOf>central</mirrorOf>
</mirror>
<mirror>
<id>alimaven</id>
<name>aliyun maven</name>
<url>http://maven.aliyun.com/nexus/content/groups/public/</url>
<mirrorOf>central</mirrorOf>
</mirror>
</mirrors>
<profiles>
</profiles>
</settings>
pom.xml需求
<dependencies>
<!-- https://mvnrepository.com/artifact/org.apache.spark/spark-core -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.13</artifactId>
<version>3.3.0</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.spark/spark-sql -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.13</artifactId>
<version>3.3.0</version>
<scope>provided</scope>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.spark/spark-streaming -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_2.13</artifactId>
<version>3.3.0</version>
<scope>provided</scope>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.spark/spark-mllib -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-mllib_2.13</artifactId>
<version>3.3.0</version>
<scope>provided</scope>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.spark/spark-hive -->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-hive_2.13</artifactId>
<version>3.3.0</version>
<scope>provided</scope>
</dependency>
</dependencies>
修改【maven】
未引入错误提示：
刷新【maven】配置文件
下载完成: 整个包内容大概【500M】，别用流量下载，很亏的。
下载【Scala】插件
在【Installed】中可以查看是否安装完毕。
创建【Scala】文件
**手动创建【scala】文件 **
点击设置Scala的SDK
我这里有【2.13.8】版本的，如果没有，点击【Create】去下载一个。
如果是下载的话得多等一会，挺慢的。
**可创建： **
Scala的类名需要首字母大写
创建成功
执行测试文件：
package com.item.action
import org.apache.spark.{SparkConf, SparkContext}
object Demo {
def main(args: Array[String]): Unit = {
// 创建 Spark 运行配置对象
val sparkConf = new SparkConf().setMaster("local[*]").setAppName("单词数量统计：")
// 创建 Spark 上下文环境对象（连接对象）
val sc = new SparkContext(sparkConf)
// 读取文件
var input=sc.textFile("src/main/java/test.txt");
// 分词
var lines=input.flatMap(line=>line.split(" "))
// 分组计数
var count=lines.map(word=>(word,1)).reduceByKey{(x,y)=>x+y}
// 打印结果
count.foreach(println)
//关闭 Spark 连接
sc.stop()
}
}
读取文件：
Love is like a butterfly. It goes where it pleases and it pleases where it goes.
**打印结果： **
C:\java\jdk\jdk1.8.0_152\bin\java.exe "-javaagent:C:\java\IDEA\IntelliJ IDEA 2020.1.3\lib\idea_rt.jar=57562:C:\java\IDEA\IntelliJ IDEA 2020.1.3\bin" -Dfile.encoding=UTF-8 -classpath 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nused-1.0.0.jar;D:\old\newPro\org\rocksdb\rocksdbjni\6.20.3\rocksdbjni-6.20.3.jar;D:\old\newPro\com\google\protobuf\protobuf-java\2.5.0\protobuf-java-2.5.0.jar;D:\old\newPro\com\google\guava\guava\14.0.1\guava-14.0.1.jar;D:\old\newPro\com\google\code\gson\gson\2.2.4\gson-2.2.4.jar;C:\Users\Administrator\.ivy2\cache\org.scala-lang\scala-library\jars\scala-library-2.13.8.jar;C:\Users\Administrator\.ivy2\cache\org.scala-lang\scala-reflect\jars\scala-reflect-2.13.8.jar;C:\Users\Administrator\.ivy2\cache\org.scala-lang\scala-library\srcs\scala-library-2.13.8-sources.jar com.item.action.Demo
Using Spark's default log4j profile: org/apache/spark/log4j2-defaults.properties
22/07/15 17:04:29 INFO SparkContext: Running Spark version 3.3.0
22/07/15 17:04:29 INFO ResourceUtils: ==============================================================
22/07/15 17:04:29 INFO ResourceUtils: No custom resources configured for spark.driver.
22/07/15 17:04:29 INFO ResourceUtils: ==============================================================
22/07/15 17:04:29 INFO SparkContext: Submitted application: 单词数量统计：
22/07/15 17:04:29 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)
22/07/15 17:04:29 INFO ResourceProfile: Limiting resource is cpu
22/07/15 17:04:29 INFO ResourceProfileManager: Added ResourceProfile id: 0
22/07/15 17:04:29 INFO SecurityManager: Changing view acls to: Administrator
22/07/15 17:04:29 INFO SecurityManager: Changing modify acls to: Administrator
22/07/15 17:04:29 INFO SecurityManager: Changing view acls groups to:
22/07/15 17:04:29 INFO SecurityManager: Changing modify acls groups to:
22/07/15 17:04:29 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()
22/07/15 17:04:30 INFO Utils: Successfully started service 'sparkDriver' on port 57604.
22/07/15 17:04:30 INFO SparkEnv: Registering MapOutputTracker
22/07/15 17:04:30 INFO SparkEnv: Registering BlockManagerMaster
22/07/15 17:04:30 INFO BlockManagerMasterEndpoint: Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
22/07/15 17:04:30 INFO BlockManagerMasterEndpoint: BlockManagerMasterEndpoint up
22/07/15 17:04:30 INFO SparkEnv: Registering BlockManagerMasterHeartbeat
22/07/15 17:04:30 INFO DiskBlockManager: Created local directory at C:\Users\Administrator\AppData\Local\Temp\blockmgr-f0d03bba-e54f-4c5a-81a6-edfdafbb455a
22/07/15 17:04:30 INFO MemoryStore: MemoryStore started with capacity 898.5 MiB
22/07/15 17:04:30 INFO SparkEnv: Registering OutputCommitCoordinator
22/07/15 17:04:30 INFO Utils: Successfully started service 'SparkUI' on port 4040.
22/07/15 17:04:30 INFO Executor: Starting executor ID driver on host 192.168.15.19
22/07/15 17:04:30 INFO Executor: Starting executor with user classpath (userClassPathFirst = false): ''
22/07/15 17:04:31 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 57647.
22/07/15 17:04:31 INFO NettyBlockTransferService: Server created on 192.168.15.19:57647
22/07/15 17:04:31 INFO BlockManager: Using org.apache.spark.storage.RandomBlockReplicationPolicy for block replication policy
22/07/15 17:04:31 INFO BlockManagerMaster: Registering BlockManager BlockManagerId(driver, 192.168.15.19, 57647, None)
22/07/15 17:04:31 INFO BlockManagerMasterEndpoint: Registering block manager 192.168.15.19:57647 with 898.5 MiB RAM, BlockManagerId(driver, 192.168.15.19, 57647, None)
22/07/15 17:04:31 INFO BlockManagerMaster: Registered BlockManager BlockManagerId(driver, 192.168.15.19, 57647, None)
22/07/15 17:04:31 INFO BlockManager: Initialized BlockManager: BlockManagerId(driver, 192.168.15.19, 57647, None)
22/07/15 17:04:31 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 358.0 KiB, free 898.2 MiB)
22/07/15 17:04:31 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 32.3 KiB, free 898.1 MiB)
22/07/15 17:04:31 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on 192.168.15.19:57647 (size: 32.3 KiB, free: 898.5 MiB)
22/07/15 17:04:31 INFO SparkContext: Created broadcast 0 from textFile at Demo.scala:12
22/07/15 17:04:31 INFO FileInputFormat: Total input files to process : 1
22/07/15 17:04:32 INFO SparkContext: Starting job: foreach at Demo.scala:18
22/07/15 17:04:32 INFO DAGScheduler: Registering RDD 3 (map at Demo.scala:16) as input to shuffle 0
22/07/15 17:04:32 INFO DAGScheduler: Got job 0 (foreach at Demo.scala:18) with 2 output partitions
22/07/15 17:04:32 INFO DAGScheduler: Final stage: ResultStage 1 (foreach at Demo.scala:18)
22/07/15 17:04:32 INFO DAGScheduler: Parents of final stage: List(ShuffleMapStage 0)
22/07/15 17:04:32 INFO DAGScheduler: Missing parents: List(ShuffleMapStage 0)
22/07/15 17:04:32 INFO DAGScheduler: Submitting ShuffleMapStage 0 (MapPartitionsRDD[3] at map at Demo.scala:16), which has no missing parents
22/07/15 17:04:32 INFO MemoryStore: Block broadcast_1 stored as values in memory (estimated size 7.0 KiB, free 898.1 MiB)
22/07/15 17:04:32 INFO MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 3.9 KiB, free 898.1 MiB)
22/07/15 17:04:32 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on 192.168.15.19:57647 (size: 3.9 KiB, free: 898.5 MiB)
22/07/15 17:04:32 INFO SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:1513
22/07/15 17:04:32 INFO DAGScheduler: Submitting 2 missing tasks from ShuffleMapStage 0 (MapPartitionsRDD[3] at map at Demo.scala:16) (first 15 tasks are for partitions Vector(0, 1))
22/07/15 17:04:32 INFO TaskSchedulerImpl: Adding task set 0.0 with 2 tasks resource profile 0
22/07/15 17:04:32 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0) (192.168.15.19, executor driver, partition 0, PROCESS_LOCAL, 7475 bytes) taskResourceAssignments Map()
22/07/15 17:04:32 INFO TaskSetManager: Starting task 1.0 in stage 0.0 (TID 1) (192.168.15.19, executor driver, partition 1, PROCESS_LOCAL, 7475 bytes) taskResourceAssignments Map()
22/07/15 17:04:32 INFO Executor: Running task 1.0 in stage 0.0 (TID 1)
22/07/15 17:04:32 INFO Executor: Running task 0.0 in stage 0.0 (TID 0)
22/07/15 17:04:32 INFO HadoopRDD: Input split: file:/C:/Users/Administrator/IdeaProjects/mytest/src/main/java/test.txt:40+40
22/07/15 17:04:32 INFO HadoopRDD: Input split: file:/C:/Users/Administrator/IdeaProjects/mytest/src/main/java/test.txt:0+40
22/07/15 17:04:33 INFO Executor: Finished task 0.0 in stage 0.0 (TID 0). 1432 bytes result sent to driver
22/07/15 17:04:33 INFO Executor: Finished task 1.0 in stage 0.0 (TID 1). 1303 bytes result sent to driver
22/07/15 17:04:33 INFO TaskSetManager: Finished task 1.0 in stage 0.0 (TID 1) in 672 ms on 192.168.15.19 (executor driver) (1/2)
22/07/15 17:04:33 INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 687 ms on 192.168.15.19 (executor driver) (2/2)
22/07/15 17:04:33 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool
22/07/15 17:04:33 INFO DAGScheduler: ShuffleMapStage 0 (map at Demo.scala:16) finished in 0.781 s
22/07/15 17:04:33 INFO DAGScheduler: looking for newly runnable stages
22/07/15 17:04:33 INFO DAGScheduler: running: HashSet()
22/07/15 17:04:33 INFO DAGScheduler: waiting: HashSet(ResultStage 1)
22/07/15 17:04:33 INFO DAGScheduler: failed: HashSet()
22/07/15 17:04:33 INFO DAGScheduler: Submitting ResultStage 1 (ShuffledRDD[4] at reduceByKey at Demo.scala:16), which has no missing parents
22/07/15 17:04:33 INFO MemoryStore: Block broadcast_2 stored as values in memory (estimated size 5.3 KiB, free 898.1 MiB)
22/07/15 17:04:33 INFO MemoryStore: Block broadcast_2_piece0 stored as bytes in memory (estimated size 3.0 KiB, free 898.1 MiB)
22/07/15 17:04:33 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on 192.168.15.19:57647 (size: 3.0 KiB, free: 898.5 MiB)
22/07/15 17:04:33 INFO SparkContext: Created broadcast 2 from broadcast at DAGScheduler.scala:1513
22/07/15 17:04:33 INFO DAGScheduler: Submitting 2 missing tasks from ResultStage 1 (ShuffledRDD[4] at reduceByKey at Demo.scala:16) (first 15 tasks are for partitions Vector(0, 1))
22/07/15 17:04:33 INFO TaskSchedulerImpl: Adding task set 1.0 with 2 tasks resource profile 0
22/07/15 17:04:33 INFO TaskSetManager: Starting task 0.0 in stage 1.0 (TID 2) (192.168.15.19, executor driver, partition 0, NODE_LOCAL, 7217 bytes) taskResourceAssignments Map()
22/07/15 17:04:33 INFO TaskSetManager: Starting task 1.0 in stage 1.0 (TID 3) (192.168.15.19, executor driver, partition 1, NODE_LOCAL, 7217 bytes) taskResourceAssignments Map()
22/07/15 17:04:33 INFO Executor: Running task 1.0 in stage 1.0 (TID 3)
22/07/15 17:04:33 INFO Executor: Running task 0.0 in stage 1.0 (TID 2)
22/07/15 17:04:33 INFO ShuffleBlockFetcherIterator: Getting 1 (72.0 B) non-empty blocks including 1 (72.0 B) local and 0 (0.0 B) host-local and 0 (0.0 B) push-merged-local and 0 (0.0 B) remote blocks
22/07/15 17:04:33 INFO ShuffleBlockFetcherIterator: Getting 1 (117.0 B) non-empty blocks including 1 (117.0 B) local and 0 (0.0 B) host-local and 0 (0.0 B) push-merged-local and 0 (0.0 B) remote blocks
22/07/15 17:04:33 INFO ShuffleBlockFetcherIterator: Started 0 remote fetches in 14 ms
22/07/15 17:04:33 INFO ShuffleBlockFetcherIterator: Started 0 remote fetches in 14 ms
(butterfly.,1)
(is,1)
(it,3)
(Love,1)
(a,1)
(goes.,1)
(like,1)
(goes,1)
(where,2)
(It,1)
(and,1)
(pleases,2)
22/07/15 17:04:33 INFO Executor: Finished task 0.0 in stage 1.0 (TID 2). 1321 bytes result sent to driver
22/07/15 17:04:33 INFO Executor: Finished task 1.0 in stage 1.0 (TID 3). 1321 bytes result sent to driver
22/07/15 17:04:33 INFO TaskSetManager: Finished task 0.0 in stage 1.0 (TID 2) in 78 ms on 192.168.15.19 (executor driver) (1/2)
22/07/15 17:04:33 INFO TaskSetManager: Finished task 1.0 in stage 1.0 (TID 3) in 62 ms on 192.168.15.19 (executor driver) (2/2)
22/07/15 17:04:33 INFO TaskSchedulerImpl: Removed TaskSet 1.0, whose tasks have all completed, from pool
22/07/15 17:04:33 INFO DAGScheduler: ResultStage 1 (foreach at Demo.scala:18) finished in 0.094 s
22/07/15 17:04:33 INFO DAGScheduler: Job 0 is finished. Cancelling potential speculative or zombie tasks for this job
22/07/15 17:04:33 INFO TaskSchedulerImpl: Killing all running tasks in stage 1: Stage finished
22/07/15 17:04:33 INFO DAGScheduler: Job 0 finished: foreach at Demo.scala:18, took 1.169723 s
22/07/15 17:04:33 INFO SparkUI: Stopped Spark web UI at http://192.168.15.19:4040
22/07/15 17:04:33 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
22/07/15 17:04:33 INFO MemoryStore: MemoryStore cleared
22/07/15 17:04:33 INFO BlockManager: BlockManager stopped
22/07/15 17:04:33 INFO BlockManagerMaster: BlockManagerMaster stopped
22/07/15 17:04:33 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
22/07/15 17:04:33 INFO SparkContext: Successfully stopped SparkContext
22/07/15 17:04:33 INFO ShutdownHookManager: Shutdown hook called
22/07/15 17:04:33 INFO ShutdownHookManager: Deleting directory C:\Users\Administrator\AppData\Local\Temp\spark-6624b247-1ac0-45f6-baa8-f271e26b2dc1
Process finished with exit code 0
打印结果中可以看到：
说明计算成功。
标签：
大数据
本文转载自: https://blog.csdn.net/feng8403000/article/details/125807380
版权归原作者 红目香薰 所有， 如有侵权，请联系我们删除。
版权归原作者 红目香薰 所有， 如有侵权，请联系我们删除。