一、读取配置
driver.properties
#mysql driver=com.mysql.jdbc.Driver url=jdbc:mysql://192.168.56.111:3306/myshops2 user=root password=root #hadoop hadoop_url=hdfs://192.168.56.111:9000
package com.njbdqn.util import java.io.FileInputStream import java.util.Properties object ReadPropertiesFileTool { def readProperties(flag:String): Map[String,String] ={ val prop = new Properties() prop.load(new FileInputStream (ReadPropertiesFileTool.getClass.getClassLoader.getResource("driver.properties").getPath)) var map:Map[String,String] = Map.empty if(flag.equalsIgnoreCase("mysql")){ map+=("driver"->prop.getProperty("driver")) map+=("url"->prop.getProperty("url")) map+=("user"->prop.getProperty("user")) map+=("password"->prop.getProperty("password")) }else{ map+=("hadoop_url"->prop.getProperty("hadoop_url")) } map } }
二、读取resource中配置,操作Mysql
package com.njbdqn.util import java.util.Properties import org.apache.spark.sql.{DataFrame, SaveMode, SparkSession} object MYSQLConnection { val paramMap = ReadPropertiesFileTool.readProperties("mysql") // 读取数据库中指定的表 def readMySql(spark:SparkSession,tableName:String): DataFrame ={ val map:Map[String,String] = Map( "driver"->paramMap("driver"), "url"->paramMap("url"), "user"->paramMap("user"), "password"->paramMap("password"), "dbtable"->tableName ) spark.read.format("jdbc").options(map) // Adds input options for the underlying data source .load() } // 将df写入数据库到指定的表 def writeTable(spark:SparkSession,df:DataFrame,tableName:String): Unit ={ val prop = new Properties() prop.put("user","root") prop.put("password","root") df.write.mode(SaveMode.Overwrite).jdbc("jdbc:mysql://192.168.56.111:3306/myshops2",tableName,prop) } }
三、上传/下载HDFS
package com.njbdqn.util import org.apache.spark.ml.classification.{LogisticRegression, LogisticRegressionModel} import org.apache.spark.sql.{DataFrame, SaveMode, SparkSession} /** * HDFS操作 */ object HDFSConnection { val paramMap = ReadPropertiesFileTool.readProperties("hadoop") /** * 将数据写入到hdfs */ def writeDataToHDFS(path:String,df:DataFrame): Unit ={ df.write.mode(SaveMode.Overwrite).save(paramMap("hadoop_url")+path) } /** * 从hdfs的指定位置读到内存中 */ def readDataToHDFS(spark:SparkSession,path:String): DataFrame ={ spark.read.parquet(paramMap("hadoop_url")+path) } /** * 从hdfs读取LR */ def readLRModelToHDFS(path:String): LogisticRegressionModel ={ LogisticRegressionModel.read.load(paramMap("hadoop_url")+path) } /** * LR模型写入HDFS */ def writeLRModelToHDFS(lr:LogisticRegressionModel,path:String): Unit ={ lr.save(paramMap("hadoop_url")+path) } }