rddとDFデータをMYSQLに格納

1.RDD関数による一括データの格納

object RDDtoMysql {
  def myFun(iterator: Iterator[(String, Int)]): Unit = {
    var conn: Connection = null
    var ps: PreparedStatement = null
    val sql = "insert into sparktomysql(name, age) values (?, ?)"
    try {
         conn = DriverManager.getConnection("jdbc:mysql://127.0.0.1:3306/test_dw","test_dw", "123456")
         iterator.foreach(data => {
          ps = conn.prepareStatement(sql)
          ps.setString(1, data._1)
          ps.setInt(2, data._2)
          ps.executeUpdate()
        }
      )
    } catch {
      case e: Exception => println("Mysql Exception")
    } finally {
      if (ps != null) {
        ps.close()
      }
      if (conn != null) {
        conn.close()
      }
    }
  }

  def main(args: Array[String]) {
    val conf = new SparkConf().setAppName("RDDToMysql").setMaster("local")
    val sc = new SparkContext(conf)
    val data = sc.parallelize(List(("www", 10), ("iteblog", 20), ("com", 30)))
    data.foreachPartition(myFun) //    
  }
}

2.DataFrameクラス操作mysql格納(新規テーブルおよび元データのクリア)

def main(args: Array[String]): Unit = {
val url = "jdbc:mysql://localhost:3306/spark?user=iteblog&password=iteblog"
val sc = new SparkContext
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
val schema = StructType(
StructField("name", StringType) ::
StructField("age", IntegerType)
    :: Nil)
val data = sc.parallelize(List(("iteblog", 30), ("iteblog", 29),("com", 40), ("bt", 33), ("www", 23))).map(item => Row.apply(item._1, item._2))
val df = sqlContext.createDataFrame(data, schema)
    df.insertIntoJDBC(url, "sparktomysql", true)//true            
    sc.stop
  }