Description: The table format refers to the way data is structured and stored in a table in data processing frameworks like Apache Spark. This format allows for organizing information into rows and columns, facilitating its manipulation and analysis. The table format integrates with distributed processing engines, enabling efficient SQL queries and data analysis operations. Tables can be viewed as an extension of DataFrames, where each column has a specific data type and rows represent individual records. This structured approach enhances data readability while optimizing the performance of query and transformation operations. Additionally, the table format is compatible with various data sources, such as relational databases, CSV files, and cloud storage systems, making it a versatile tool for analyzing large volumes of information. The ability to handle data in table format allows users to perform complex analyses and gain valuable insights quickly and efficiently, leveraging the parallelization and scalability that modern data processing frameworks offer.
