Spark Programming in Python for Beginners with Apache Spark 3 - Spark Databases and Tables

This video tutorial covers the basics of Apache Spark as a database, focusing on the creation and management of databases and tables. It explains the concept of metadata and the role of the metastore, particularly the use of the Apache Hive metastore for persistence. The tutorial distinguishes between managed and unmanaged tables, highlighting their differences in data storage and management. It also discusses the implications of dropping tables and the future enhancements in Spark SQL, emphasizing the advantages of managed tables.

What are the two main parts of a table in Spark?

Describe the role of the metastore in Spark.

Explain the difference between managed tables and unmanaged tables in Spark.

What is the Spark SQL Warehouse directory?

How does Spark handle metadata for unmanaged tables?

What happens to the data files when a managed table is dropped?

Why are managed tables preferred over unmanaged tables in Spark?