基础的 sparkSQL操作

spark连接mysql操作 数据库jdbc 连接封装
package test.com

import org.apache.spark.sql.{DataFrame, SparkSession}
/**
  * Created by sx on 2018/5/31.
  */
object JDBC_db {
  val url = "jdbc:mysql://ip:3306/db"
  val driver = "com.mysql.jdbc.Driver"
  val user = "root"
  val password = "root"

  def count(sparkSession: SparkSession, table: String): DataFrame = {
    val sparkDF = sparkSession.read
      .format("jdbc")
      .option("url", s"${url}")
      .option("driver", s"${driver}")
      .option("dbtable", table)
      .option("user", s"${user}")
      .option("password", s"${password}")
      .load()
    return sparkDF

  }
}

创建类连接
import java.util.logging
import org.apache.log4j.{Level, Logger}
import org.apache.spark.sql.SparkSession
import test.com.JDBC_db

object JDBC_DB {
  System.setProperty("hadoop.home.dir", "D:\\hadoop\\hadoop-common-2.2.0-bin-master")
  Logger.getLogger("org").setLevel(Level.WARN)

  def main(args: Array[String]): Unit = {
    val spark = SparkSession.builder().master("local").getOrCreate()
    val sparkDF = JDBC_db.count(spark, "test1")
    sparkDF.createOrReplaceTempView("aa")
    sparkDF.show()

    val sparkDF2 = JDBC_db.count(spark, "test2")
    sparkDF2.createOrReplaceTempView("bb")
    sparkDF2.show()
    spark.sql("select * from aa union select * from bb").show()
  }
}