Description: A temporary view in Apache Spark is a representation of a dataset created during the duration of a Spark session. This view allows users to execute SQL queries on the data similarly to how they would with a table in a relational database. Temporary views are useful because they enable analysts and developers to work with structured data without the need to create permanent tables in the storage system. They can be defined from DataFrames or datasets, and their scope is limited to the current session, meaning they are automatically dropped when the session ends. This provides flexibility and efficiency in data handling, as users can perform ad hoc analysis without worrying about data persistence. Additionally, temporary views can be used to simplify complex queries, allowing users to break their operations into more manageable and understandable steps. In summary, temporary views are a powerful tool in Apache Spark that facilitate real-time data analysis and dynamic execution of SQL queries efficiently.
