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。

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<!-- 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.SparkSession

object 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()

}

}

}