基于IDEA环境下的Spark2.X程序开发

我们选择在线安装

这个是windows下的scala,直接双击安装就可以了

安装好之后可以验证一下

这个是我本地的jdk1.8安装包，直接双击安装

安装完成后可以验证一下

https://archive.apache.org/dist/maven/maven-3/3.3.9/binaries/

解压

我的本地是win10系统

配置好环境变量我们可以验证一下

修改这个文件

这个是默认的

改成这样子

把本地的maven配置进来

接下来就是等待自动把相应的架包下载下来

把scala添加进来了

接下来我们创建目录

在scala目录下建包

在这个包里面创建一个scala的类

输入以下代码

配置maven的 pom.xml文件

<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/maven-v4_0_0.xsd">
  <modelVersion>4.0.0</modelVersion>
  <groupId>com.spark</groupId>
  <artifactId>sparkStu</artifactId>
  <packaging>war</packaging>
  <version>1.0-SNAPSHOT</version>
  <name>sparkStu Maven Webapp</name>
  <url>http://maven.apache.org</url>

  <properties>
    <hadoop.version>2.6.0</hadoop.version>
    <scala.binary.version>2.11</scala.binary.version>
    <spark.version>2.2.0</spark.version>
  </properties>

  <dependencies>
    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-core_${scala.binary.version}</artifactId>
      <version>${spark.version}</version>
    </dependency>

    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-sql_${scala.binary.version}</artifactId>
      <version>${spark.version}</version>
    </dependency>

<!--
    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-core_2.11</artifactId>
      <version>2.2.0</version>
    </dependency>
-->
    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-streaming_${scala.binary.version}</artifactId>
      <version>${spark.version}</version>
    </dependency>

    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-hive_${scala.binary.version}</artifactId>
      <version>${spark.version}</version>
    </dependency>

    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-streaming-kafka-0-10_${scala.binary.version}</artifactId>
      <version>${spark.version}</version>
    </dependency>

    <dependency>
      <groupId>org.apache.spark</groupId>
      <artifactId>spark-sql-kafka-0-10_${scala.binary.version}</artifactId>
      <version>${spark.version}</version>
    </dependency>

    <dependency>
      <groupId>org.apache.hadoop</groupId>
      <artifactId>hadoop-client</artifactId>
      <version>${hadoop.version}</version>
    </dependency>

    <dependency>
      <groupId>junit</groupId>
      <artifactId>junit</artifactId>
      <version>3.8.1</version>
      <scope>test</scope>
    </dependency>

  </dependencies>
  <build>
    <finalName>sparkStu</finalName>
  </build>
</project>

在Test.scala里加上这段内容

我们编写一个简单的代码

package com.spark.test

import org.apache.spark.sql.SparkSession

object Test {

  def main(args: Array[String]): Unit = {
   val spark= SparkSession
       .builder
         .appName("HdfsTest")
           .getOrCreate()
     val filePart = "E://Mycode/datas/stu.txt"
     val rdd= spark.sparkContext.textFile(filePart)

     val lines= rdd.flatMap(x => x.split(" ")).collect().toList
     println(lines)
  }
}

运行一下

结果报错了

E:\software\jdk1.\bin\java "-javaagent:E:\software\IDEA\IntelliJ IDEA 2017.2.6\lib\idea_rt.jar=59010:E:\software\IDEA\IntelliJ IDEA 2017.2.6\bin" -Dfile.encoding=UTF- -classpath E:\software\jdk1.\jre\lib\charsets.jar;E:\software\jdk1.\jre\lib\deploy.jar;E:\software\jdk1.\jre\lib\ext\access-bridge-.jar;E:\software\jdk1.\jre\lib\ext\cldrdata.jar;E:\software\jdk1.\jre\lib\ext\dnsns.jar;E:\software\jdk1.\jre\lib\ext\jaccess.jar;E:\software\jdk1.\jre\lib\ext\jfxrt.jar;E:\software\jdk1.\jre\lib\ext\localedata.jar;E:\software\jdk1.\jre\lib\ext\nashorn.jar;E:\software\jdk1.\jre\lib\ext\sunec.jar;E:\software\jdk1.\jre\lib\ext\sunjce_provider.jar;E:\software\jdk1.\jre\lib\ext\sunmscapi.jar;E:\software\jdk1.\jre\lib\ext\sunpkcs11.jar;E:\software\jdk1.\jre\lib\ext\zipfs.jar;E:\software\jdk1.\jre\lib\javaws.jar;E:\software\jdk1.\jre\lib\jce.jar;E:\software\jdk1.\jre\lib\jfr.jar;E:\software\jdk1.\jre\lib\jfxswt.jar;E:\software\jdk1.\jre\lib\jsse.jar;E:\software\jdk1.\jre\lib\management-agent.jar;E:\software\jdk1.\jre\lib\plugin.jar;E:\software\jdk1.\jre\lib\resources.jar;E:\software\jdk1.\jre\lib\rt.jar;E:\Mycode\SparkStu\target\classes;E:\software\Scala\lib\scala-actors-2.11..jar;E:\software\Scala\lib\scala-actors-migration_2.-1.1..jar;E:\software\Scala\lib\scala-library.jar;E:\software\Scala\lib\scala-parser-combinators_2.-1.0..jar;E:\software\Scala\lib\scala-reflect.jar;E:\software\Scala\lib\scala-swing_2.-1.0..jar;E:\software\Scala\lib\scala-xml_2.-1.0..jar;E:\software\maven3.3.9\repository\org\apache\spark\spark-core_2.\2.2.\spark-core_2.-2.2..jar;E:\software\maven3.3.9\repository\org\apache\avro\avro\1.7.\avro-1.7..jar;E:\software\maven3.3.9\repository\org\codehaus\jackson\jackson-core-asl\1.9.\jackson-core-asl-1.9..jar;E:\software\maven3.3.9\repository\com\thoughtworks\paranamer\paranamer\2.3\paranamer-2.3.jar;E:\software\maven3.3.9\repository\org\apache\commons\commons-compress\1.4.\commons-compress-1.4..jar;E:\software\maven3.3.9\repository\org\tukaani\xz\1.0\xz-1.0.jar;E:\software\maven3.3.9\repository\org\apache\avro\avro-mapred\1.7.\avro-mapred-1.7.-hadoop2.jar;E:\software\maven3.3.9\repository\org\apache\avro\avro-ipc\1.7.\avro-ipc-1.7..jar;E:\software\maven3.3.9\repository\org\apache\avro\avro-ipc\1.7.\avro-ipc-1.7.-tests.jar;E:\software\maven3.3.9\repository\com\twitter\chill_2.\0.8.\chill_2.-0.8..jar;E:\software\maven3.3.9\repository\com\esotericsoftware\kryo-shaded\3.0.\kryo-shaded-3.0..jar;E:\software\maven3.3.9\repository\com\esotericsoftware\minlog\1.3.\minlog-1.3..jar;E:\software\maven3.3.9\repository\org\objenesis\objenesis\2.1\objenesis-2.1.jar;E:\software\maven3.3.9\repository\com\twitter\chill-java\0.8.\chill-java-0.8..jar;E:\software\maven3.3.9\repository\org\apache\xbean\xbean-asm5-shaded\4.4\xbean-asm5-shaded-4.4.jar;E:\software\maven3.3.9\repository\org\apache\spark\spark-launcher_2.\2.2.\spark-launcher_2.-2.2..jar;E:\software\maven3.3.9\repository\org\apache\spark\spark-network-common_2.\2.2.\spark-network-common_2.-2.2..jar;E:\software\maven3.3.9\repository\org\fusesource\leveldbjni\leveldbjni-all\1.8\leveldbjni-all-1.8.jar;E:\software\maven3.3.9\repository\com\fasterxml\jackson\core\jackson-annotations\2.6.\jackson-annotations-2.6..jar;E:\software\maven3.3.9\repository\org\apache\spark\spark-network-shuffle_2.\2.2.\spark-network-shuffle_2.-2.2..jar;E:\software\maven3.3.9\repository\org\apache\spark\spark-unsafe_2.\2.2.\spark-unsafe_2.-2.2..jar;E:\software\maven3.3.9\repository\net\java\dev\jets3t\jets3t\0.9.\jets3t-0.9..jar;E:\software\maven3.3.9\repository\org\apache\httpcomponents\httpcore\4.3.\httpcore-4.3..jar;E:\software\maven3.3.9\repository\javax\activation\activation\1.1.\activation-1.1..jar;E:\software\maven3.3.9\repository\mx4j\mx4j\3.0.\mx4j-3.0..jar;E:\software\maven3.3.9\repository\javax\mail\mail\1.4.\mail-1.4..jar;E:\software\maven3.3.9\repository\org\bouncycastle\bcprov-jdk15on\1.51\bcprov-jdk15on-1.51.jar;E:\software\maven3.3.9\repository\com\jamesmurty\utils\java-xmlbuilder\1.0\java-xmlbuilder-1.0.jar;E:\software\maven3.3.9\repository\net\iharder\base64\2.3.\base64-2.3..jar;E:\software\maven3.3.9\repository\org\apache\curator\curator-recipes\2.6.\curator-recipes-2.6..jar;E:\software\maven3.3.9\repository\org\apache\curator\curator-framework\2.6.\curator-framework-2.6..jar;E:\software\maven3.3.9\repository\org\apache\zookeeper\zookeeper\3.4.\zookeeper-3.4..jar;E:\software\maven3.3.9\repository\com\google\guava\guava\16.0.\guava-16.0..jar;E:\software\maven3.3.9\repository\javax\servlet\javax.servlet-api\3.1.\javax.servlet-api-3.1..jar;E:\software\maven3.3.9\repository\org\apache\commons\commons-lang3\3.5\commons-lang3-3.5.jar;E:\software\maven3.3.9\repository\org\apache\commons\commons-math3\3.4.\commons-math3-3.4..jar;E:\software\maven3.3.9\repository\com\google\code\findbugs\jsr305\1.3.\jsr305-1.3..jar;E:\software\maven3.3.9\repository\org\slf4j\slf4j-api\1.7.\slf4j-api-1.7..jar;E:\software\maven3.3.9\repository\org\slf4j\jul-to-slf4j\1.7.\jul-to-slf4j-1.7..jar;E:\software\maven3.3.9\repository\org\slf4j\jcl-over-slf4j\1.7.\jcl-over-slf4j-1.7..jar;E:\software\maven3.3.9\repository\log4j\log4j\1.2.\log4j-1.2..jar;E:\software\maven3.3.9\repository\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;E:\software\maven3.3.9\repository\org\apache\spark\spark-catalyst_2.\2.2.\spark-catalyst_2.-2.2..jar;E:\software\maven3.3.9\repository\org\codehaus\janino\janino\3.0.\janino-3.0..jar;E:\software\maven3.3.9\repository\org\codehaus\janino\commons-compiler\3.0.\commons-compiler-3.0..jar;E:\software\maven3.3.9\repository\org\antlr\antlr4-runtime\4.5.\antlr4-runtime-4.5..jar;E:\software\maven3.3.9\repository\org\apache\parquet\parquet-column\1.8.\parquet-column-1.8..jar;E:\software\maven3.3.9\repository\org\apache\parquet\parquet-common\1.8.\parquet-common-1.8..jar;E:\software\maven3.3.9\repository\org\apache\parquet\parquet-encoding\1.8.\parquet-encoding-1.8..jar;E:\software\maven3.3.9\repository\org\apache\parquet\parquet-hadoop\1.8.\parquet-hadoop-1.8..jar;E:\software\maven3.3.9\repository\org\apache\parquet\parquet-format\2.3.\parquet-format-2.3..jar;E:\software\maven3.3.9\repository\org\apache\parquet\parquet-jackson\1.8.\parquet-jackson-1.8..jar;E:\software\maven3.3.9\repository\org\apache\spark\spark-streaming_2.\2.2.\spark-streaming_2.-2.2..jar;E:\software\maven3.3.9\repository\org\apache\spark\spark-hive_2.\2.2.\spark-hive_2.-2.2..jar;E:\software\maven3.3.9\repository\com\twitter\parquet-hadoop-bundle\1.6.\parquet-hadoop-bundle-1.6..jar;E:\software\maven3.3.9\repository\org\spark-project\hive\hive-exec\1.2..spark2\hive-exec-1.2..spark2.jar;E:\software\maven3.3.9\repository\commons-io\commons-io\2.4\commons-io-2.4.jar;E:\software\maven3.3.9\repository\commons-lang\commons-lang\2.6\commons-lang-2.6.jar;E:\software\maven3.3.9\repository\javolution\javolution\5.5.\javolution-5.5..jar;E:\software\maven3.3.9\repository\log4j\apache-log4j-extras\1.2.\apache-log4j-extras-1.2..jar;E:\software\maven3.3.9\repository\org\antlr\antlr-runtime\3.4\antlr-runtime-3.4.jar;E:\software\maven3.3.9\repository\org\antlr\stringtemplate\3.2.\stringtemplate-3.2..jar;E:\software\maven3.3.9\repository\antlr\antlr\2.7.\antlr-2.7..jar;E:\software\maven3.3.9\repository\org\antlr\ST4\4.0.\ST4-4.0..jar;E:\software\maven3.3.9\repository\com\googlecode\javaewah\JavaEWAH\0.3.\JavaEWAH-0.3..jar;E:\software\maven3.3.9\repository\org\iq80\snappy\snappy\0.2\snappy-0.2.jar;E:\software\maven3.3.9\repository\stax\stax-api\1.0.\stax-api-1.0..jar;E:\software\maven3.3.9\repository\net\sf\opencsv\opencsv\2.3\opencsv-2.3.jar;E:\software\maven3.3.9\repository\org\spark-project\hive\hive-metastore\1.2..spark2\hive-metastore-1.2..spark2.jar;E:\software\maven3.3.9\repository\com\jolbox\bonecp\0.8..RELEASE\bonecp-0.8..RELEASE.jar;E:\software\maven3.3.9\repository\commons-cli\commons-cli\1.2\commons-cli-1.2.jar;E:\software\maven3.3.9\repository\commons-logging\commons-logging\1.1.\commons-logging-1.1..jar;E:\software\maven3.3.9\repository\org\apache\derby\derby\10.10.2.0\derby-10.10.2.0.jar;E:\software\maven3.3.9\repository\org\datanucleus\datanucleus-api-jdo\3.2.\datanucleus-api-jdo-3.2..jar;E:\software\maven3.3.9\repository\org\datanucleus\datanucleus-rdbms\3.2.\datanucleus-rdbms-3.2..jar;E:\software\maven3.3.9\repository\commons-pool\commons-pool\1.5.\commons-pool-1.5..jar;E:\software\maven3.3.9\repository\commons-dbcp\commons-dbcp\1.4\commons-dbcp-1.4.jar;E:\software\maven3.3.9\repository\javax\jdo\jdo-api\3.0.\jdo-api-3.0..jar;E:\software\maven3.3.9\repository\javax\transaction\jta\1.1\jta-1.1.jar;E:\software\maven3.3.9\repository\commons-httpclient\commons-httpclient\3.1\commons-httpclient-3.1.jar;E:\software\maven3.3.9\repository\org\apache\calcite\calcite-avatica\1.2.-incubating\calcite-avatica-1.2.-incubating.jar;E:\software\maven3.3.9\repository\org\apache\calcite\calcite-core\1.2.-incubating\calcite-core-1.2.-incubating.jar;E:\software\maven3.3.9\repository\org\apache\calcite\calcite-linq4j\1.2.-incubating\calcite-linq4j-1.2.-incubating.jar;E:\software\maven3.3.9\repository\net\hydromatic\eigenbase-properties\1.1.\eigenbase-properties-1.1..jar;E:\software\maven3.3.9\repository\org\apache\httpcomponents\httpclient\4.5.\httpclient-4.5..jar;E:\software\maven3.3.9\repository\org\codehaus\jackson\jackson-mapper-asl\1.9.\jackson-mapper-asl-1.9..jar;E:\software\maven3.3.9\repository\commons-codec\commons-codec\1.10\commons-codec-1.10.jar;E:\software\maven3.3.9\repository\joda-time\joda-time\2.9.\joda-time-2.9..jar;E:\software\maven3.3.9\repository\org\jodd\jodd-core\3.5.\jodd-core-3.5..jar;E:\software\maven3.3.9\repository\org\datanucleus\datanucleus-core\3.2.\datanucleus-core-3.2..jar;E:\software\maven3.3.9\repository\org\apache\thrift\libthrift\0.9.\libthrift-0.9..jar;E:\software\maven3.3.9\repository\org\apache\thrift\libfb303\0.9.\libfb303-0.9..jar;E:\software\maven3.3.9\repository\org\apache\spark\spark-streaming-kafka--10_2.\2.2.\spark-streaming-kafka--10_2.-2.2..jar;E:\software\maven3.3.9\repository\org\apache\kafka\kafka_2.\0.10.0.1\kafka_2.-0.10.0.1.jar;E:\software\maven3.3.9\repository\com\101tec\zkclient\0.8\zkclient-0.8.jar;E:\software\maven3.3.9\repository\com\yammer\metrics\metrics-core\2.2.\metrics-core-2.2..jar;E:\software\maven3.3.9\r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com.spark.test.Test
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
// :: INFO SparkContext: Running Spark version 2.2.
// :: WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
// :: 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:)
    at org.apache.hadoop.util.Shell.getWinUtilsPath(Shell.java:)
    at org.apache.hadoop.util.Shell.<clinit>(Shell.java:)
    at org.apache.hadoop.util.StringUtils.<clinit>(StringUtils.java:)
    at org.apache.hadoop.security.Groups.parseStaticMapping(Groups.java:)
    at org.apache.hadoop.security.Groups.<init>(Groups.java:)
    at org.apache.hadoop.security.Groups.<init>(Groups.java:)
    at org.apache.hadoop.security.Groups.getUserToGroupsMappingService(Groups.java:)
    at org.apache.hadoop.security.UserGroupInformation.initialize(UserGroupInformation.java:)
    at org.apache.hadoop.security.UserGroupInformation.ensureInitialized(UserGroupInformation.java:)
    at org.apache.hadoop.security.UserGroupInformation.loginUserFromSubject(UserGroupInformation.java:)
    at org.apache.hadoop.security.UserGroupInformation.getLoginUser(UserGroupInformation.java:)
    at org.apache.hadoop.security.UserGroupInformation.getCurrentUser(UserGroupInformation.java:)
    at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$.apply(Utils.scala:)
    at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$.apply(Utils.scala:)
    at scala.Option.getOrElse(Option.scala:)
    at org.apache.spark.util.Utils$.getCurrentUserName(Utils.scala:)
    at org.apache.spark.SparkContext.<init>(SparkContext.scala:)
    at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$.apply(SparkSession.scala:)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$.apply(SparkSession.scala:)
    at scala.Option.getOrElse(Option.scala:)
    at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:)
    at com.spark.test.Test$.main(Test.scala:)
    at com.spark.test.Test.main(Test.scala)
// :: ERROR SparkContext: Error initializing SparkContext.
org.apache.spark.SparkException: A master URL must be set in your configuration
    at org.apache.spark.SparkContext.<init>(SparkContext.scala:)
    at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$.apply(SparkSession.scala:)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$.apply(SparkSession.scala:)
    at scala.Option.getOrElse(Option.scala:)
    at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:)
    at com.spark.test.Test$.main(Test.scala:)
    at com.spark.test.Test.main(Test.scala)
// :: INFO SparkContext: Successfully stopped SparkContext
Exception in thread "main" org.apache.spark.SparkException: A master URL must be set in your configuration
    at org.apache.spark.SparkContext.<init>(SparkContext.scala:)
    at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$.apply(SparkSession.scala:)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$.apply(SparkSession.scala:)
    at scala.Option.getOrElse(Option.scala:)
    at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:)
    at com.spark.test.Test$.main(Test.scala:)
    at com.spark.test.Test.main(Test.scala)

Process finished with exit code 

这是因为我本地没有配置好hadoop,现在我们配一个

这个是我本地的hadoop/bin

下面把本地win10的环境变量配置一下

再重启一下idea,再运行一下程序

报了另外一个错误，但是可以确定的是前面的错误我们解决了

E:\software\jdk1.\bin\java "-javaagent:E:\software\IDEA\IntelliJ IDEA 2017.2.6\lib\idea_rt.jar=60011:E:\software\IDEA\IntelliJ IDEA 2017.2.6\bin" -Dfile.encoding=UTF- -classpath 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com.spark.test.Test
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
// :: INFO SparkContext: Running Spark version 2.2.
// :: ERROR SparkContext: Error initializing SparkContext.
org.apache.spark.SparkException: A master URL must be set in your configuration
    at org.apache.spark.SparkContext.<init>(SparkContext.scala:)
    at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$.apply(SparkSession.scala:)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$.apply(SparkSession.scala:)
    at scala.Option.getOrElse(Option.scala:)
    at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:)
    at com.spark.test.Test$.main(Test.scala:)
    at com.spark.test.Test.main(Test.scala)
// :: INFO SparkContext: Successfully stopped SparkContext
Exception in thread "main" org.apache.spark.SparkException: A master URL must be set in your configuration
    at org.apache.spark.SparkContext.<init>(SparkContext.scala:)
    at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$.apply(SparkSession.scala:)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$.apply(SparkSession.scala:)
    at scala.Option.getOrElse(Option.scala:)
    at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:)
    at com.spark.test.Test$.main(Test.scala:)
    at com.spark.test.Test.main(Test.scala)

Process finished with exit code 

这里的错误是说要指明你的程序运行在什么地方

在程序里加上这一句，指明我们现在在本地运行

我们再运行一次，可以看到没问题了

我们继续修改程序，加上这一句

再次运行看看结果

把相同的单词进行累加

我们看看运行结果

刚刚我们使用的是rdd的方式，接下来我们使用dataSet的方式

dataSet可以近似的理解为数据库的一张张表

我们运行的结果

用空格切分单词

运行结果

E:\software\jdk1.\bin\java "-javaagent:E:\software\IDEA\IntelliJ IDEA 2017.2.6\lib\idea_rt.jar=62232:E:\software\IDEA\IntelliJ IDEA 2017.2.6\bin" -Dfile.encoding=UTF- -classpath 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com.spark.test.Test
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
// :: INFO SparkContext: Running Spark version 2.2.
// :: INFO SparkContext: Submitted application: HdfsTest
// :: INFO SecurityManager: Changing view acls to: Brave
// :: INFO SecurityManager: Changing modify acls to: Brave
// :: INFO SecurityManager: Changing view acls groups to:
// :: INFO SecurityManager: Changing modify acls groups to:
// :: INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(Brave); groups with view permissions: Set(); users  with modify permissions: Set(Brave); groups with modify permissions: Set()
// :: INFO Utils: Successfully started service 'sparkDriver' on port .
// :: INFO SparkEnv: Registering MapOutputTracker
// :: INFO SparkEnv: Registering BlockManagerMaster
// :: INFO BlockManagerMasterEndpoint: Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
// :: INFO BlockManagerMasterEndpoint: BlockManagerMasterEndpoint up
// :: INFO DiskBlockManager: Created local directory at C:\Users\Brave\AppData\Local\Temp\blockmgr-2ad95228--4a24-b6b6-b09973c4a4ff
// :: INFO MemoryStore: MemoryStore started with capacity 1998.3 MB
// :: INFO SparkEnv: Registering OutputCommitCoordinator
// :: INFO Utils: Successfully started service 'SparkUI' on port .
// :: INFO SparkUI: Bound SparkUI to 0.0.0.0, and started at http://192.168.56.1:4040
// :: INFO Executor: Starting executor ID driver on host localhost
// :: INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port .
// :: INFO NettyBlockTransferService: Server created on 192.168.56.1:
// :: INFO BlockManager: Using org.apache.spark.storage.RandomBlockReplicationPolicy for block replication policy
// :: INFO BlockManagerMaster: Registering BlockManager BlockManagerId(driver, 192.168.56.1, , None)
// :: INFO BlockManagerMasterEndpoint: Registering block manager 192.168.56.1: with 1998.3 MB RAM, BlockManagerId(driver, 192.168.56.1, , None)
// :: INFO BlockManagerMaster: Registered BlockManager BlockManagerId(driver, 192.168.56.1, , None)
// :: INFO BlockManager: Initialized BlockManager: BlockManagerId(driver, 192.168.56.1, , None)
// :: INFO SharedState: Setting hive.metastore.warehouse.dir ('null') to the value of spark.sql.warehouse.dir ('file:/E:/Mycode/SparkStu/spark-warehouse/').
// :: INFO SharedState: Warehouse path is 'file:/E:/Mycode/SparkStu/spark-warehouse/'.
// :: INFO StateStoreCoordinatorRef: Registered StateStoreCoordinator endpoint
// :: INFO FileSourceStrategy: Pruning directories with:
// :: INFO FileSourceStrategy: Post-Scan Filters:
// :: INFO FileSourceStrategy: Output Data Schema: struct<value: string>
// :: INFO FileSourceScanExec: Pushed Filters:
// :: INFO CodeGenerator: Code generated in 321.911944 ms
// :: INFO CodeGenerator: Code generated in 9.798824 ms
// :: INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 213.6 KB, free 1998.1 MB)
// :: INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 20.2 KB, free 1998.1 MB)
// :: INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on 192.168.56.1: (size: 20.2 KB, free: 1998.3 MB)
// :: INFO SparkContext: Created broadcast  from show at Test.scala:
// :: INFO FileSourceScanExec: Planning scan with bin packing, max size:  bytes, open cost is considered as scanning  bytes.
// :: INFO SparkContext: Starting job: show at Test.scala:
// :: INFO DAGScheduler: Got job  (show at Test.scala:) with  output partitions
// :: INFO DAGScheduler: Final stage: ResultStage  (show at Test.scala:)
// :: INFO DAGScheduler: Parents of final stage: List()
// :: INFO DAGScheduler: Missing parents: List()
// :: INFO DAGScheduler: Submitting ResultStage  (MapPartitionsRDD[] at show at Test.scala:), which has no missing parents
// :: INFO MemoryStore: Block broadcast_1 stored as values in memory (estimated size 13.0 KB, free 1998.1 MB)
// :: INFO MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 6.1 KB, free 1998.1 MB)
// :: INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on 192.168.56.1: (size: 6.1 KB, free: 1998.3 MB)
// :: INFO SparkContext: Created broadcast  from broadcast at DAGScheduler.scala:
// :: INFO DAGScheduler: Submitting  missing tasks from ResultStage  (MapPartitionsRDD[] at show at Test.scala:) (first  tasks are for partitions Vector())
// :: INFO TaskSchedulerImpl: Adding task set 0.0 with  tasks
// :: INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID , localhost, executor driver, partition , PROCESS_LOCAL,  bytes)
// :: INFO Executor: Running task 0.0 in stage 0.0 (TID )
// :: INFO CodeGenerator: Code generated in 13.617205 ms
// :: INFO FileScanRDD: Reading File path: file:///E:/Mycode/datas/stu.txt, range: 0-113, partition values: [empty row]
// :: INFO CodeGenerator: Code generated in 11.971125 ms
// :: INFO Executor: Finished task 0.0 in stage 0.0 (TID ).  bytes result sent to driver
// :: INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID ) in  ms on localhost (executor driver) (/)
// :: INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool
// :: INFO DAGScheduler: ResultStage  (show at Test.scala:) finished in 0.284 s
// :: INFO DAGScheduler: Job  finished: show at Test.scala:, took 0.483521 s
// :: INFO CodeGenerator: Code generated in 23.334109 ms
+------+
| value|
+------+
|hadoop|
|hadoop|
|  java|
|  java|
| spark|
| spark|
|  hive|
| hbase|
| sqoop|
| sqoop|
| mysql|
| redit|
| flume|
| flume|
|  join|
|   hue|
| scala|
|python|
+------+

// :: INFO SparkContext: Invoking stop() from shutdown hook
// :: INFO SparkUI: Stopped Spark web UI at http://192.168.56.1:4040
// :: INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
// :: INFO MemoryStore: MemoryStore cleared
// :: INFO BlockManager: BlockManager stopped
// :: INFO BlockManagerMaster: BlockManagerMaster stopped
// :: INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
// :: INFO SparkContext: Successfully stopped SparkContext
// :: INFO ShutdownHookManager: Shutdown hook called
// :: INFO ShutdownHookManager: Deleting directory C:\Users\Brave\AppData\Local\Temp\spark-2c920b38-6a7f--a2ef-9ee345492414

Process finished with exit code 

增加这个字段

运行结果

分组统计

运行结果

把最后的代码放上来

package com.spark.test

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

  def main(args: Array[String]): Unit = {
   val spark= SparkSession
       .builder
         .master("local")
         .appName("HdfsTest")
           .getOrCreate()
     val filePart = "E://Mycode/datas/stu.txt"
//     val rdd= spark.sparkContext.textFile(filePart)
//     val lines= rdd.flatMap(x => x.split(" ")).map(x=>(x,1)).reduceByKey((a,b)=>(a+b)).collect().toList
    //     println(lines)
    import spark.implicits._
    val dataSet= spark.read.textFile(filePart)
      .flatMap(x => x.split(" "))
      .map(x=>(x,)).groupBy("_1").count()
      .show()

  }
}

现在我们把程序打包

我们把代码稍微改一下

package com.spark.test

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

  def main(args: Array[String]): Unit = {
   val spark= SparkSession
       .builder
         .master("local")
         .appName("HdfsTest")
           .getOrCreate()

    val filePart = args()
    //  val filePart = "E://Mycode/datas/stu.txt"
//     val rdd= spark.sparkContext.textFile(filePart)
//     val lines= rdd.flatMap(x => x.split(" ")).map(x=>(x,1)).reduceByKey((a,b)=>(a+b)).collect().toList
    //     println(lines)
    import spark.implicits._
    val dataSet= spark.read.textFile(filePart)
      .flatMap(x => x.split(" "))
      .map(x=>(x,)).groupBy("_1").count()
      .show()

  }
}

把这些都剔除掉

剩下这两个

打包完成了

把这个包上传到我们的集群上

这个是我们的数据文件

我们把数据文件上传的hdfs上面去，先启动hdfs

同时记得把zookeeper也启动了，不然会出问题的

现在hdfs上创建一个目录

把本地的文件上传

我们在集群上跑一下

bin/spark-submit --master local[] /opt/jars/sparkStu.jar hdfs://bigdata-pro01.kfk.com:9000/user/datas/stu.txt

可以看到跑下来的结果