Apache Spark SQL
Apache Spark SQL is a module within Apache Spark that provides a programming interface for working with structured and semi-structured data using SQL queries and DataFrame APIs. It enables developers to query data stored in various formats (e.g., JSON, Parquet, Hive) and integrate relational processing with Spark's functional programming. It optimizes queries using the Catalyst optimizer and supports integration with external data sources and Hive.
Developers should learn Apache Spark SQL when working with big data analytics, as it allows efficient querying and processing of large datasets using familiar SQL syntax and DataFrame operations. It is particularly useful for ETL (Extract, Transform, Load) pipelines, data warehousing, and real-time analytics in distributed environments, such as in financial analysis, log processing, or machine learning workflows.