Spark-Save the Rdd to the Rmdb (MYSQL) database

Scala Connection Database BULK INSERT:

Scala> Import Java.sql.DriverManager

scala> var url = "Jdbc:mysql://localhost:3306/mydb?useunicode=true&characterencoding=utf8"

scala> var username = "Cui"

scala> var password = "Dbtest"

Scala> Val conn= drivermanager.getconnection (Url,username,password)

scala> val pstat = conn.preparestatement ("INSERT into ' TEST ' (' ID ', ' age ') VALUES (?,?)")

Scala> Pstat.clearbatch

Scala> Pstat.setint (1,501)

Scala> Pstat.setint (2,501)

Scala> Pstat.addbatch

Scala> Pstat.setint (1,502)

Scala> Pstat.setint (2,502)

Scala> Pstat.addbatch

Scala> Pstat.setint (1,503)

Scala> Pstat.setint (2,503)

Scala> Pstat.addbatch

Scala> Pstat.executebatch
Res24:array[int] = Array (1, 1, 1)

The RDD is saved to the database:

Just use Foreachpartition to create and execute a SQL statement via JDBC over a batch of records. The code is just normal JDBC code.

https://community.cloudera.com/t5/Advanced-Analytics-Apache-Spark/Spark-Streaming-save-output-to-mysql-DB/td-p/25607

ImportJava.sql.DriverManagervar Data= Sc.parallelize (Array (1,10), (1,100), (1,1000), (1,10000), (2,10), (2,100), (2,1000), (2,10000)), 2) data.foreachpartition (It={var URL= "Jdbc:mysql://localhost:3306/mydb?useunicode=true&characterencoding=utf8"Val Conn= Drivermanager.getconnection (URL, "username", "password") Val PStat= Conn.preparestatement ("INSERT into ' TEST ' (' ID ', ' age ') VALUES (?,?)")         for(obj <-it) {Pstat.setint (1, Obj._1) pstat.setint (2, obj._2) Pstat.addbatch}Try{Pstat.executebatch}finally{pstat.close Conn.close}})

Spark-Save the Rdd to the Rmdb (MYSQL) database