Working with the Spark JDBC API

In the previous section, we introduced the Spark JDBC API and some of its most commonly used options. In order to understand them better, we need to see them in action, which is going to be the focus of this section. It is now time to start working with the mysql community server that we installed in Chapter 2.

Follow the steps outlined ahead to create a few tables needed for the examples covered in this chapter:

1. Log in to the mysql service using the following command:

   mysql --local-infile=1 -u root -p

   Enter password:

   Welcome to the MySQL monitor.    Commands end with ; or \g.

   Your MySQL connection id is 11

   Server version: 8.0.32 MySQL Community Server - GPL

   Copyright (c) 2000, 2023, Oracle and/or its affiliates.

   Oracle is a registered trademark of Oracle Corporation and/or its

   affiliates. Other names may be trademarks of their respective

   owners.

   Type 'help;' or '\h' for help. Type '\c' to clear the...