Spark读取csv文件，清洗后存入Hive库中

配置好相关依赖，然后将集群中的hive-site.xml文件复制一份放在项目中的resources目录下。

import org.apache.spark.rdd.RDD
import org.apache.spark.sql.SparkSession

import scala.util.matching.Regex

object A_my_rush {
  def main(args: Array[String]): Unit = {

    val spark: SparkSession = SparkSession
      .builder()
      .appName("A_my_rush")
      .master("local[*]")
      .enableHiveSupport()  //注意添加hive支持
      .getOrCreate()

    import spark.implicits._  //导入隐式转换，注意这个spark是我上头定义的spark，不是系统的。


    //读取本地csv文件
    val rdd: RDD[String] = spark.sparkContext.textFile(
      "C:\Users\Administrator\Desktop\Spark练习题\my_exam_A\shoping.csv"
    )


   //进行清洗操作，你们不用知道干了什么，就是清洗过滤
    rdd
      .filter(action => {
        val datas: Array[String] = action.split(",")
        var data_isGood: Boolean = datas.length == 8
        for (i <- datas) {
          if (i == "" || i == null) {
            data_isGood = false
          }
        }
        data_isGood
      })
      .map((_, 1))
      .groupByKey()
      .keys
      .map(action => {

        val datas: Array[String] = action.split(",")

        var result = ""
        var num = 0
        var fuhao = ","

        val event_time_pattern: Regex = "[0-9]{4}-[0-9]{2}-[0-9]{2}".r

        val detail_time_pattern: Regex = "[0-9]{2}:[0-9]{2}:[0-9]{2}".r

        for (i <- datas) {

          var tmp: String = i

          if (num == 0) {

            val event_time: String =
              event_time_pattern.findAllIn(tmp).mkString(",").split(",")(0)

            val detail_time: String =
              detail_time_pattern.findAllIn(tmp).mkString(",").split(",")(0)

            tmp = event_time + "," + detail_time

          }

          if (num == 4) {
            val arr: Array[String] = tmp.split("[.]")
            var str = ""
            var count = 0
            var s = "|"
            for (i <- arr) {
              if (arr.length - 1 == count) {
                s = ""
              }
              str += i
                .replaceFirst(
                  i.charAt(0).toString,
                  i.charAt(0).toUpper.toString
                ) + s
              count += 1
            }
            tmp = str
          }

          if (num == 7) {
            fuhao = ""
          }

          result += tmp + fuhao

          num += 1

        }
        result
      })
      .toDF()  //关键部分：转换为dateframe，方便进行后续的sparkSql操作
      .createOrReplaceTempView("rush_data") //创建临时表
 

    //利用sparkSql在hive中创建一个表
    spark.sql("""
        |create table if not exists mydb.shop(
        |event_time string,  
        |detail_time string,  
        |order_id string,  
        |product_id string,  
        |category_id string,  
        |category_code string,
        |brand string,  
        |price string,
        |user_id string)
        |row format delimited fields terminated by 't'
        |""".stripMargin)

   
    
    spark.sql("""
        |select 
        |split(value,",")[0] event_time,  
        |split(value,",")[1] detail_time,  
        |split(value,",")[2] order_id,  
        |split(value,",")[3] product_id,  
        |split(value,",")[4] category_id,  
        |split(value,",")[5] category_code,  
        |split(value,",")[6] brand,  
        |split(value,",")[7] price,
        |split(value,",")[8] user_id
        |from rush_data
        |""".stripMargin).createOrReplaceTempView("data")

   //将数据插入上面创建的表中，检查是否成功插入，完成
    spark.sql("""
        |insert into table mydb.shop
        |select * from data
        |""".stripMargin)

    spark.stop()
  }
}