[大数据]Windows平台搭建Spark开发环境（Intellij idea 2020.1社区版+Maven 3.6.3+Scala 2.11.8）

在开始之前，需要说明的是 要跑通基本的wordcount程序，是不需要在windows上安装 hadoop 和spark的，因为idea在跑程序的时候，会按照 pom.xml配置文件，从指定的 repository源，按照properties指定的版本，下载dependency中指定的依赖包 。?

如果需要在本地通过 spark-shell，或者 运行开发完的包，那么就需要完整的hadoop 和spark环境，就需要把这两个都安装好。

一、需要安装的软件版本 及 下载地址

jdk 1.8 ：https://www.oracle.com/java/technologies/javase/javase-jdk8-downloads.html
Scala 2.11.8? ：https://www.scala-lang.org/download/2.11.8.html
Intellij idea 2020.1社区版：?https://www.jetbrains.com/zh-cn/idea/download/other.html
Maven 3.6.3 ：http://maven.apache.org/docs/history.html
?

二、配置环境变量 及 验证

1、Java

新增系统环境变量：JAVA_HOME ?C:\Program Files\Java
PATH 中增加：C:\Program Files\Java\jdk1.8.0_91\bin 和 C:\Program Files\Java\jre1.8.0_91\bin
CLASSPATH 中要增加：.;%JAVA_HOME%\lib;%JAVA_HOME%\lib\tools.jar;

验证是否安装成功：

C:\Users\edz>java -version
java version "1.8.0_91"
Java(TM) SE Runtime Environment (build 1.8.0_91-b15)
Java HotSpot(TM) 64-Bit Server VM (build 25.91-b15, mixed mode)

C:\Users\edz>javac -version
javac 1.8.0_91

2、Scala

新增系统环境变量：SCALA_HOME C:\Program Files (x86)\scala
PATH 中增加：%SCALA_HOME%\bin

验证：

C:\Users\edz>scala
Welcome to Scala 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_91).
Type in expressions for evaluation. Or try :help.

scala> :quit

3、Maven

Maven下载后，解压到了D:\spark_study ，删除了 apache-maven-3.6.3-bin目录，路径为D:\spark_study\apache-maven-3.6.3

新增系统环境变量：MAVEN_HOME D:\spark_study\apache-maven-3.6.3
新增系统环境变量：MAVEN_OPTS -Xms128m -Xmx512m
CLASSPATH 中要增加：%MAVEN_HOME%\bin

设置 本地maven 仓库 的路径为：D:\spark_study\localWarehouse
打开 D:\spark_study\apache-maven-3.6.3\conf\settings.xml，在文件中添加：? ?

? ? ? ?<localRepository>D:\spark_study\localWarehouse</localRepository>

接下来设置 国内maven仓库 如阿里仓库，在 <mirrors>标签中添加：
<mirror>
?? ?<id>nexus-aliyun</id>
?? ?<mirrorOf>central</mirrorOf>
?? ?<name>Nexus aliyun</name>
?? ?<url>http://maven.aliyun.com/nexus/content/groups/public</url>
</mirror>

验证：

C:\Users\edz>mvn -V
Apache Maven 3.6.3 (cecedd343002696d0abb50b32b541b8a6ba2883f)
Maven home: D:\spark_study\apache-maven-3.6.3\bin\..
Java version: 1.8.0_91, vendor: Oracle Corporation, runtime: C:\Program Files\Java\jdk1.8.0_91\jre
Default locale: zh_CN, platform encoding: GBK
OS name: "windows 10", version: "10.0", arch: "amd64", family: "windows"

三、配置 intellij idea

1、安装?intellij idea

注意勾选红色框部分，然后一步一步安装就行。

?2、安装scala插件

通过菜单 File -》Settings 进入如下页面，然后输入 scala 找到要安装的插件，点击 安装。按照提示，需要重启 IDE。

?如果 显示找不到插件，可以通过 点击 Auto-detect proxy settings 来设置代理，点击保存。

?3、配置java、scala、maven

通过菜单 File -》Project Structure 进入页面进行设置：

?Global Libraries 点击 + 号，选择 Scala SDK：

?

通过菜单 File-》Settings -》?Build,Exection,Deployment -》?Build Tools -》?Maven进入页面，要修改?Maven home directory，User settings file，Local repository，最后点击 OK 保存。

?然后 继续点击 Maven 左侧的向右的三角形，展开子菜单，点击 Importing ，再勾选 红色框的3个 复选框，点击 OK 保存。

四、intellij idea中新建项目

File -》New -》Project，注意 不要勾选 “Create from archetype”，因为?scala-archetype-simple:1.2 版本太低，会有很多问题。?

项目名称 都按照默认，没有修改，最后点击 Finish ：

?修改pom.xml文件，在 </project> 前面增加 依赖项：

   <dependencies>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.11</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_2.11</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <dependency>
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-reflect</artifactId>
            <version>${scala.version}</version>
            <scope>${scope.flag}</scope>
        </dependency>
        <dependency>
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-compiler</artifactId>
            <version>${scala.version}</version>
            <scope>${scope.flag}</scope>
        </dependency>
        <dependency>
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-library</artifactId>
            <version>${scala.version}</version>
            <scope>${scope.flag}</scope>
        </dependency>

    </dependencies>

    <build>
        <plugins>

            <plugin>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.2</version>
                <configuration>
                    <source>1.8</source>
                    <target>1.8</target>
                </configuration>
            </plugin>

            <plugin>
                <groupId>net.alchim31.maven</groupId>
                <artifactId>scala-maven-plugin</artifactId>
                <version>3.2.0</version>
                <configuration>
                    <scalaCompatVersion>${scala.binary.version}</scalaCompatVersion>
                    <scalaVersion>${scala.version}</scalaVersion>
                </configuration>

                <executions>
                    <execution>
                        <phase>compile</phase>
                        <goals>
                            <goal>compile</goal>
                            <goal>testCompile</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>

        </plugins>
    </build>

然后 右键项目中的 pom.xml 文件 -》Maven -》reload project 下载依赖包：

?五、编写WordCount代码

右键 Main 目录 -》 New -》 Directory ，目录名称为： scala

右键 scala 目录 -》Make Directory as -》Generate Sources Root

?右键 scala 目录-》New -》scala class -》 object ，名称为：WordCount

输入代码：

import org.apache.spark.SparkContext
import org.apache.spark.SparkConf

object WordCount {
  def main(args: Array[String]) {
    val inputFile =  "D:\\spark_study\\wordcount.txt"
    
    val conf = new SparkConf().setAppName("WordCount").setMaster("local")
    val sc = new SparkContext(conf)
    val textFile = sc.textFile(inputFile)
    val wordCount = textFile.flatMap(line => line.split(" ")).map(word => (word, 1)).reduceByKey((a, b) => a + b)
    wordCount.foreach(println)
  }
}

在D盘的 spark_study 目录下创建文件 wordcount.txt，在上面程序中会引用这个文件（以空格来分隔单词），内容如下：

spark sparkstreaming flink hadoop hbase kafka redis hadoop spark flink clickhouse

右键 WordCount ，选择 Run test ，运行结果如下：

"C:\Program Files\Java\jdk1.8.0_91\bin\java.exe" "-javaagent:C:\Program Files\JetBrains\IntelliJ IDEA Community Edition 2020.1.4\lib\idea_rt.jar=52207:C:\Program Files\JetBrains\IntelliJ IDEA Community Edition 2020.1.4\bin" -Dfile.encoding=UTF-8 -classpath "C:\Program Files\Java\jdk1.8.0_91\jre\lib\charsets.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\deploy.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\ext\access-bridge-64.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\ext\cldrdata.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\ext\dnsns.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\ext\jaccess.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\ext\jfxrt.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\ext\localedata.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\ext\nashorn.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\ext\sunec.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\ext\sunjce_provider.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\ext\sunmscapi.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\ext\sunpkcs11.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\ext\zipfs.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\javaws.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\jce.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\jfr.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\jfxswt.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\jsse.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\management-agent.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\plugin.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\resources.jar;C:\Program Files\Java\jdk1.8.0_91\jre\lib\rt.jar;C:\Users\edz\IdeaProjects\untitled\target\classes;C:\Program Files (x86)\scala\lib\scala-library.jar;C:\Program Files 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ons-cli-1.2.jar;D:\spark_study\localWarehouse\commons-logging\commons-logging\1.1.3\commons-logging-1.1.3.jar;D:\spark_study\localWarehouse\org\datanucleus\datanucleus-api-jdo\3.2.6\datanucleus-api-jdo-3.2.6.jar;D:\spark_study\localWarehouse\org\datanucleus\datanucleus-rdbms\3.2.9\datanucleus-rdbms-3.2.9.jar;D:\spark_study\localWarehouse\commons-pool\commons-pool\1.5.4\commons-pool-1.5.4.jar;D:\spark_study\localWarehouse\commons-dbcp\commons-dbcp\1.4\commons-dbcp-1.4.jar;D:\spark_study\localWarehouse\javax\jdo\jdo-api\3.0.1\jdo-api-3.0.1.jar;D:\spark_study\localWarehouse\javax\transaction\jta\1.1\jta-1.1.jar;D:\spark_study\localWarehouse\commons-httpclient\commons-httpclient\3.1\commons-httpclient-3.1.jar;D:\spark_study\localWarehouse\org\apache\calcite\calcite-avatica\1.2.0-incubating\calcite-avatica-1.2.0-incubating.jar;D:\spark_study\localWarehouse\org\apache\calcite\calcite-core\1.2.0-incubating\calcite-core-1.2.0-incubating.jar;D:\spark_study\localWarehouse\org\apache\calcite\calcite-linq4j\1.2.0-incubating\calcite-linq4j-1.2.0-incubating.jar;D:\spark_study\localWarehouse\net\hydromatic\eigenbase-properties\1.1.5\eigenbase-properties-1.1.5.jar;D:\spark_study\localWarehouse\org\apache\httpcomponents\httpclient\4.5.4\httpclient-4.5.4.jar;D:\spark_study\localWarehouse\org\codehaus\jackson\jackson-mapper-asl\1.9.13\jackson-mapper-asl-1.9.13.jar;D:\spark_study\localWarehouse\commons-codec\commons-codec\1.10\commons-codec-1.10.jar;D:\spark_study\localWarehouse\joda-time\joda-time\2.9.3\joda-time-2.9.3.jar;D:\spark_study\localWarehouse\org\jodd\jodd-core\3.5.2\jodd-core-3.5.2.jar;D:\spark_study\localWarehouse\org\datanucleus\datanucleus-core\3.2.10\datanucleus-core-3.2.10.jar;D:\spark_study\localWarehouse\org\apache\thrift\libthrift\0.9.3\libthrift-0.9.3.jar;D:\spark_study\localWarehouse\org\apache\thrift\libfb303\0.9.3\libfb303-0.9.3.jar;D:\spark_study\localWarehouse\org\apache\derby\derby\10.12.1.1\derby-10.12.1.1.jar;D:\spark_study\localWarehouse\org\apache\spark\spark-mllib_2.11\2.3.0\spark-mllib_2.11-2.3.0.jar;D:\spark_study\localWarehouse\org\scala-lang\modules\scala-parser-combinators_2.11\1.0.4\scala-parser-combinators_2.11-1.0.4.jar;D:\spark_study\localWarehouse\org\apache\spark\spark-graphx_2.11\2.3.0\spark-graphx_2.11-2.3.0.jar;D:\spark_study\localWarehouse\com\github\fommil\netlib\core\1.1.2\core-1.1.2.jar;D:\spark_study\localWarehouse\net\sourceforge\f2j\arpack_combined_all\0.1\arpack_combined_all-0.1.jar;D:\spark_study\localWarehouse\org\apache\spark\spark-mllib-local_2.11\2.3.0\spark-mllib-local_2.11-2.3.0.jar;D:\spark_study\localWarehouse\org\scalanlp\breeze_2.11\0.13.2\breeze_2.11-0.13.2.jar;D:\spark_study\localWarehouse\org\scalanlp\breeze-macros_2.11\0.13.2\breeze-macros_2.11-0.13.2.jar;D:\spark_study\localWarehouse\com\github\rwl\jtransforms\2.4.0\jtransforms-2.4.0.jar;D:\spark_study\localWarehouse\org\spire-math\spire_2.11\0.13.0\spire_2.11-0.13.0.jar;D:\spark_study\localWarehouse\org\spire-math\spire-macros_2.11\0.13.0\spire-macros_2.11-0.13.0.jar;D:\spark_study\localWarehouse\org\typelevel\machinist_2.11\0.6.1\machinist_2.11-0.6.1.jar;D:\spark_study\localWarehouse\com\chuusai\shapeless_2.11\2.3.2\shapeless_2.11-2.3.2.jar;D:\spark_study\localWarehouse\org\typelevel\macro-compat_2.11\1.1.1\macro-compat_2.11-1.1.1.jar;D:\spark_study\localWarehouse\org\scala-lang\scala-reflect\2.11.8\scala-reflect-2.11.8.jar;D:\spark_study\localWarehouse\org\scala-lang\scala-compiler\2.11.8\scala-compiler-2.11.8.jar;D:\spark_study\localWarehouse\org\scala-lang\modules\scala-xml_2.11\1.0.4\scala-xml_2.11-1.0.4.jar;D:\spark_study\localWarehouse\org\scala-lang\scala-library\2.11.8\scala-library-2.11.8.jar" WordCount
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
21/07/23 13:47:46 INFO SparkContext: Running Spark version 2.3.0
21/07/23 13:47:46 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
21/07/23 13:47:46 ERROR Shell: Failed to locate the winutils binary in the hadoop binary path
java.io.IOException: Could not locate executable null\bin\winutils.exe in the Hadoop binaries.
	at org.apache.hadoop.util.Shell.getQualifiedBinPath(Shell.java:378)
	at org.apache.hadoop.util.Shell.getWinUtilsPath(Shell.java:393)
	at org.apache.hadoop.util.Shell.<clinit>(Shell.java:386)
	at org.apache.hadoop.util.StringUtils.<clinit>(StringUtils.java:79)
	at org.apache.hadoop.security.Groups.parseStaticMapping(Groups.java:116)
	at org.apache.hadoop.security.Groups.<init>(Groups.java:93)
	at org.apache.hadoop.security.Groups.<init>(Groups.java:73)
	at org.apache.hadoop.security.Groups.getUserToGroupsMappingService(Groups.java:293)
	at org.apache.hadoop.security.UserGroupInformation.initialize(UserGroupInformation.java:283)
	at org.apache.hadoop.security.UserGroupInformation.ensureInitialized(UserGroupInformation.java:260)
	at org.apache.hadoop.security.UserGroupInformation.loginUserFromSubject(UserGroupInformation.java:789)
	at org.apache.hadoop.security.UserGroupInformation.getLoginUser(UserGroupInformation.java:774)
	at org.apache.hadoop.security.UserGroupInformation.getCurrentUser(UserGroupInformation.java:647)
	at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$1.apply(Utils.scala:2464)
	at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$1.apply(Utils.scala:2464)
	at scala.Option.getOrElse(Option.scala:121)
	at org.apache.spark.util.Utils$.getCurrentUserName(Utils.scala:2464)
	at org.apache.spark.SparkContext.<init>(SparkContext.scala:292)
	at WordCount$.main(WordCount.scala:9)
	at WordCount.main(WordCount.scala)
21/07/23 13:47:46 INFO SparkContext: Submitted application: WordCount
21/07/23 13:47:46 INFO SecurityManager: Changing view acls to: edz
21/07/23 13:47:46 INFO SecurityManager: Changing modify acls to: edz
21/07/23 13:47:46 INFO SecurityManager: Changing view acls groups to: 
21/07/23 13:47:46 INFO SecurityManager: Changing modify acls groups to: 
21/07/23 13:47:46 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(edz); groups with view permissions: Set(); users  with modify permissions: Set(edz); groups with modify permissions: Set()
21/07/23 13:47:48 INFO Utils: Successfully started service 'sparkDriver' on port 52244.
21/07/23 13:47:49 INFO SparkEnv: Registering MapOutputTracker
21/07/23 13:47:49 INFO SparkEnv: Registering BlockManagerMaster
21/07/23 13:47:49 INFO BlockManagerMasterEndpoint: Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
21/07/23 13:47:49 INFO BlockManagerMasterEndpoint: BlockManagerMasterEndpoint up
21/07/23 13:47:49 INFO DiskBlockManager: Created local directory at C:\Users\edz\AppData\Local\Temp\blockmgr-2ef0a030-120a-49aa-ad7e-2da8fdd565d8
21/07/23 13:47:49 INFO MemoryStore: MemoryStore started with capacity 1981.2 MB
21/07/23 13:47:49 INFO SparkEnv: Registering OutputCommitCoordinator
21/07/23 13:47:50 INFO Utils: Successfully started service 'SparkUI' on port 4040.
21/07/23 13:47:50 INFO SparkUI: Bound SparkUI to 0.0.0.0, and started at http://LAPTOP-0VG107DP:4040
21/07/23 13:47:50 INFO Executor: Starting executor ID driver on host localhost
21/07/23 13:47:50 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 52257.
21/07/23 13:47:50 INFO NettyBlockTransferService: Server created on LAPTOP-0VG107DP:52257
21/07/23 13:47:50 INFO BlockManager: Using org.apache.spark.storage.RandomBlockReplicationPolicy for block replication policy
21/07/23 13:47:50 INFO BlockManagerMaster: Registering BlockManager BlockManagerId(driver, LAPTOP-0VG107DP, 52257, None)
21/07/23 13:47:50 INFO BlockManagerMasterEndpoint: Registering block manager LAPTOP-0VG107DP:52257 with 1981.2 MB RAM, BlockManagerId(driver, LAPTOP-0VG107DP, 52257, None)
21/07/23 13:47:50 INFO BlockManagerMaster: Registered BlockManager BlockManagerId(driver, LAPTOP-0VG107DP, 52257, None)
21/07/23 13:47:50 INFO BlockManager: Initialized BlockManager: BlockManagerId(driver, LAPTOP-0VG107DP, 52257, None)
21/07/23 13:47:50 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 214.5 KB, free 1981.0 MB)
21/07/23 13:47:50 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 20.4 KB, free 1981.0 MB)
21/07/23 13:47:50 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on LAPTOP-0VG107DP:52257 (size: 20.4 KB, free: 1981.2 MB)
21/07/23 13:47:50 INFO SparkContext: Created broadcast 0 from textFile at WordCount.scala:10
21/07/23 13:47:51 INFO FileInputFormat: Total input paths to process : 1
21/07/23 13:47:51 INFO SparkContext: Starting job: foreach at WordCount.scala:12
21/07/23 13:47:51 INFO DAGScheduler: Registering RDD 3 (map at WordCount.scala:11)
21/07/23 13:47:51 INFO DAGScheduler: Got job 0 (foreach at WordCount.scala:12) with 1 output partitions
21/07/23 13:47:51 INFO DAGScheduler: Final stage: ResultStage 1 (foreach at WordCount.scala:12)
21/07/23 13:47:51 INFO DAGScheduler: Parents of final stage: List(ShuffleMapStage 0)
21/07/23 13:47:51 INFO DAGScheduler: Missing parents: List(ShuffleMapStage 0)
21/07/23 13:47:51 INFO DAGScheduler: Submitting ShuffleMapStage 0 (MapPartitionsRDD[3] at map at WordCount.scala:11), which has no missing parents
21/07/23 13:47:51 INFO MemoryStore: Block broadcast_1 stored as values in memory (estimated size 4.7 KB, free 1981.0 MB)
21/07/23 13:47:51 INFO MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 2.8 KB, free 1981.0 MB)
21/07/23 13:47:51 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on LAPTOP-0VG107DP:52257 (size: 2.8 KB, free: 1981.2 MB)
21/07/23 13:47:51 INFO SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:1039
21/07/23 13:47:51 INFO DAGScheduler: Submitting 1 missing tasks from ShuffleMapStage 0 (MapPartitionsRDD[3] at map at WordCount.scala:11) (first 15 tasks are for partitions Vector(0))
21/07/23 13:47:51 INFO TaskSchedulerImpl: Adding task set 0.0 with 1 tasks
21/07/23 13:47:51 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, localhost, executor driver, partition 0, PROCESS_LOCAL, 7870 bytes)
21/07/23 13:47:51 INFO Executor: Running task 0.0 in stage 0.0 (TID 0)
21/07/23 13:47:51 INFO HadoopRDD: Input split: file:/D:/spark_study/wordcount.txt:0+81
21/07/23 13:47:51 INFO Executor: Finished task 0.0 in stage 0.0 (TID 0). 1156 bytes result sent to driver
21/07/23 13:47:51 INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 263 ms on localhost (executor driver) (1/1)
21/07/23 13:47:51 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool 
21/07/23 13:47:51 INFO DAGScheduler: ShuffleMapStage 0 (map at WordCount.scala:11) finished in 0.379 s
21/07/23 13:47:51 INFO DAGScheduler: looking for newly runnable stages
21/07/23 13:47:51 INFO DAGScheduler: running: Set()
21/07/23 13:47:51 INFO DAGScheduler: waiting: Set(ResultStage 1)
21/07/23 13:47:51 INFO DAGScheduler: failed: Set()
21/07/23 13:47:51 INFO DAGScheduler: Submitting ResultStage 1 (ShuffledRDD[4] at reduceByKey at WordCount.scala:11), which has no missing parents
21/07/23 13:47:51 INFO MemoryStore: Block broadcast_2 stored as values in memory (estimated size 3.1 KB, free 1981.0 MB)
21/07/23 13:47:51 INFO MemoryStore: Block broadcast_2_piece0 stored as bytes in memory (estimated size 1945.0 B, free 1981.0 MB)
21/07/23 13:47:51 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on LAPTOP-0VG107DP:52257 (size: 1945.0 B, free: 1981.2 MB)
21/07/23 13:47:51 INFO SparkContext: Created broadcast 2 from broadcast at DAGScheduler.scala:1039
21/07/23 13:47:51 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 1 (ShuffledRDD[4] at reduceByKey at WordCount.scala:11) (first 15 tasks are for partitions Vector(0))
21/07/23 13:47:51 INFO TaskSchedulerImpl: Adding task set 1.0 with 1 tasks
21/07/23 13:47:51 INFO TaskSetManager: Starting task 0.0 in stage 1.0 (TID 1, localhost, executor driver, partition 0, ANY, 7649 bytes)
21/07/23 13:47:51 INFO Executor: Running task 0.0 in stage 1.0 (TID 1)
21/07/23 13:47:51 INFO ShuffleBlockFetcherIterator: Getting 1 non-empty blocks out of 1 blocks
21/07/23 13:47:51 INFO ShuffleBlockFetcherIterator: Started 0 remote fetches in 4 ms
(spark,2)
(hadoop,2)
(sparkstreaming,1)
(flink,2)
(kafka,1)
(clickhouse,1)
(redis,1)
(hbase,1)
21/07/23 13:47:51 INFO Executor: Finished task 0.0 in stage 1.0 (TID 1). 1138 bytes result sent to driver
21/07/23 13:47:51 INFO TaskSetManager: Finished task 0.0 in stage 1.0 (TID 1) in 48 ms on localhost (executor driver) (1/1)
21/07/23 13:47:51 INFO TaskSchedulerImpl: Removed TaskSet 1.0, whose tasks have all completed, from pool 
21/07/23 13:47:51 INFO DAGScheduler: ResultStage 1 (foreach at WordCount.scala:12) finished in 0.062 s
21/07/23 13:47:51 INFO DAGScheduler: Job 0 finished: foreach at WordCount.scala:12, took 0.742531 s
21/07/23 13:47:51 INFO SparkContext: Invoking stop() from shutdown hook
21/07/23 13:47:51 INFO SparkUI: Stopped Spark web UI at http://LAPTOP-0VG107DP:4040
21/07/23 13:47:51 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
21/07/23 13:47:51 INFO MemoryStore: MemoryStore cleared
21/07/23 13:47:51 INFO BlockManager: BlockManager stopped
21/07/23 13:47:51 INFO BlockManagerMaster: BlockManagerMaster stopped
21/07/23 13:47:51 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
21/07/23 13:47:51 INFO SparkContext: Successfully stopped SparkContext
21/07/23 13:47:51 INFO ShutdownHookManager: Shutdown hook called
21/07/23 13:47:51 INFO ShutdownHookManager: Deleting directory C:\Users\edz\AppData\Local\Temp\spark-4c379c11-3156-4fac-9cef-261adb05a623

Process finished with exit code 0

输出大部分都为日志，wordcount的结果是：

(spark,2)
(hadoop,2)
(sparkstreaming,1)
(flink,2)
(kafka,1)
(clickhouse,1)
(redis,1)
(hbase,1)

至此，环境配置成功。