Mysql jdbc connector how to#
Mysql jdbc connector install#
Mysql jdbc connector driver#
Mysql jdbc connector code#
Mysql jdbc connector download#

There are three tables in the sample database. The following illustrates the database diagram: We will use a sample database named mysqljdbc for the sake of demonstration.

Mysql jdbc connector install#

Once the install process completes, you can find the JAR file that you will include into your Java application as the screen below: Load MySQL JDBC sample database Third, double-click on installation file to install the MySQL Connector/J. You can choose your platform specified in the Select Platform drop-down list. Second, select your appropriate platform.

Mysql jdbc connector download#

Download and install MySQL Connector/Jįirst, go to the Download Connector/J page on website. Third, once the installation completes, you can launch it by double click on the NetBeans IDE icon. You just have to click Next button until it completes. Second, double-click on the installation file, and go through the process. It takes few minutes to complete the download. To download and install NetBeans IDE with JDK, you follow the steps below:įirst, you need to go to Oracle Java download page and click on the NetBeans with JDK download button.

Download and install MySQL Connector/J.ĭownload and install NetBeans IDE with JDK.

Oracle provides also provide use NetBeans IDE and JDK in one installation file, so you just need to download one and install both JDK and NetBeans. We choose NetBeans IDE because it’s easy to install and simple to use. You can use any Java IDE such as Eclipse or IntelliJ, which is also fine.

Download and install JDK if it is not available on your local machine.

To set up the development environment, you need to:

Mysql jdbc connector how to#

It also illustrates how to load a sample database into MySQL for practicing in the subsequent tutorials. What other examples would you like to see with Spark SQL and JDBC? Please leave ideas or questions in comments below.įor more Spark tutorials, check out Spark SQL with ScalaĪnd to keep up with changes in Spark SQL, especially DataFrame vs DataSet, check the Apache Spark SQL documentation from time-to-time.This tutorial shows you how to setup development environment that helps you work with MySQL and JDBC. This example was designed to get you up and running with Spark SQL and mySQL or any JDBC compliant database quickly. We are now in a position to run some SQL such as scala> dataframe_('select * from names').collect.foreach(println) Conclusion Spark SQL with MySQL (JDBC) Register the data as a temp table for future SQL queries scala> dataframe_mysql.registerTempTable('names')Ĥ. Let’s confirm the dataframe by show the schema of the table scala> dataframe_mysql.showģ.

Mysql jdbc connector code#

Scala> val dataframe_mysql = ('jdbc').option('url', 'jdbc:mysql://localhost/sparksql').option('driver', '').option('dbtable', 'baby_names').option('user', 'root').option('password', 'root').load()Ĭhange the mySQL url and user/password values in the above code appropriate to your environment.ģ. Type in expressions to have them evaluated. Using Scala version 2.10.4 (Java HotSpot(TM) 64-Bit Server VM, Java 1.7.0_79) Once the Spark shell is running, let’s establish a connection to mySQL db and read the baby_names table: Welcome to $ SPARK_HOME / bin / spark - shell -jars /home/example/jars/mysql-connector-java-5.1.26.jarĢ. If it is not, you can specify the path location such as: This example assumes the mySQL connector JDBC jar file is located in the same directory as where you are calling spark-shell. $ SPARK_HOME / bin / spark - shell -jars mysql-connector-java-5.1.26.jar Start the spark shell with – jars argument Spark SQL with MySQL (JDBC) Example Tutorialġ.

Mysql jdbc connector driver#

To build and deploy and Spark application with mySQL JDBC driver you may wish to check out the Spark cluster deploy with extra jars tutorial. This is a getting started with Spark mySQL example. (In a Spark application, any third party libs such as a JDBC driver would be included in package.)įrom Spark shell we’re going to establish a connection to the mySQL db and then run some queries via Spark SQL. We need to pass in the mySQL JDBC driver jar when we start up the Spark Shell. If you have any questions about the environment setup, leave comments on this post. `id` int(11) unsigned NOT NULL AUTO_INCREMENT, The SQL to create the baby_names table: DROP TABLE IF EXISTS `baby_names`