2023_Spark_实验十六：编写LoggerLevel方法及getLocalSparkSession方法

一、搭建Spark项目结构

在SparkProject模块的pom.xml文件中增加一下依赖，并等待依赖包下载完毕，如上图。

​<!-- Spark及Scala的版本号 --><properties><scala.version>2.11</scala.version><spark.version>2.1.1</spark.version></properties><!-- Mysql组件<dependency><groupId>mysql</groupId><artifactId>mysql-connector-java</artifactId><version>5.7.22.1</version></dependency> 的依赖 --><!-- Spark各个组件的依赖 --><dependencies><!-- https://mvnrepository.com/artifact/com.thoughtworks.paranamer/paranamer --><dependency><groupId>com.thoughtworks.paranamer</groupId><artifactId>paranamer</artifactId><version>2.8</version></dependency><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-sql_${scala.version}</artifactId><version>${spark.version}</version></dependency><dependency><groupId>org.apache.spark</groupId><artifactId>spark-streaming_2.11</artifactId><version>${spark.version}</version></dependency><dependency><groupId>org.apache.spark</groupId><artifactId>spark-mllib_2.11</artifactId><version>2.1.1</version></dependency><dependency><groupId>org.apache.spark</groupId><artifactId>spark-streaming-kafka-0-10_2.11</artifactId><version>2.3.0</version></dependency><dependency><groupId>org.apache.spark</groupId><artifactId>spark-streaming-kafka-0-8_${scala.version}</artifactId><version>2.3.0</version></dependency><dependency><groupId>net.jpountz.lz4</groupId><artifactId>lz4</artifactId><version>1.3.0</version></dependency><dependency><groupId>mysql</groupId><artifactId>mysql-connector-java</artifactId><version>8.0.18</version></dependency><dependency><groupId>org.apache.flume.flume-ng-clients</groupId><artifactId>flume-ng-log4jappender</artifactId><version>1.7.0</version></dependency><!-- <dependency>--><!-- <groupId>org.apache.spark</groupId>--><!-- <artifactId>spark-streaming-flume-sink_2.10</artifactId>--><!-- <version>1.5.2</version>--><!-- </dependency>--><dependency><groupId>org.apache.spark</groupId><artifactId>spark-hive_2.12</artifactId><version>2.4.8</version></dependency></dependencies><!-- 配置maven打包插件及打包类型 --><build><plugins><plugin><groupId>org.apache.maven.plugins</groupId><artifactId>maven-compiler-plugin</artifactId><version>3.8.1</version><configuration><source>1.8</source><target>1.8</target></configuration></plugin><plugin><groupId>org.apache.maven.plugins</groupId><artifactId>maven-assembly-plugin</artifactId><configuration><descriptorRefs><descriptorRef>jar-with-dependencies</descriptorRef></descriptorRefs></configuration></plugin></plugins></build>​

二、解决无法创建scala文件问题

三、编写LoggerLevel特质

在特质  下增加如下代码

Logger.getLogger("org").setLevel(Level.ERROR)

这个时候需要导包

完整代码如下：

 

import org.apache.log4j.{Level, Logger}trait LoggerLevel {Logger.getLogger("org").setLevel(Level.ERROR)}

四、编写getLocalSparkSession方法

以下是完整代码：

import org.apache.spark.sql.SparkSessionobject SparkUnit {/*** 一个class参数**/def getLocalSparkSession(appName: String): SparkSession = {SparkSession.builder().appName(appName).master("local[2]").getOrCreate()}def getLocalSparkSession(appName: String, support: Boolean): SparkSession = {if (support) SparkSession.builder().master("local[2]").appName(appName).enableHiveSupport().getOrCreate()else getLocalSparkSession(appName)}def getLocalSparkSession(appName: String, master: String): SparkSession = {SparkSession.builder().appName(appName).master(master).getOrCreate()}def getLocalSparkSession(appName: String, master: String, support: Boolean): SparkSession = {if (support) SparkSession.builder().appName(appName).master(master).enableHiveSupport().getOrCreate()else getLocalSparkSession(appName, master)}def stopSpark(ss: SparkSession) = {if (ss != null) {ss.stop()}}}