I like when humans gives weird reasons for their actions, like HRs saying “Oh, we needed 5 more YOE for this role” after taking final management round. Even google says that Parquet is a columnar…

TowardsDev's platform is a resource for developers, offering insights into software development, coding tutorials, and technology news. Through articles, tutorials, and coding challenges, TowardsDev offers insights into programming languages, development frameworks, and best practices in software engineering. Readers can learn about algorithms, data structures, and problem-solving techniques to enhance their coding skills and prepare for technical interviews.

Towards Dev

Parquet is a hybrid columnar and row-group storage format that combines the benefits of both approaches. The format organizes data into row groups containing column chunks, which are further divided into pages with metadata for efficient querying. Apache Spark leverages Parquet's structure through column pruning, predicate pushdown, vectorized reading, partition pruning, and compression optimizations. These features enable Spark to skip unnecessary data, read only required columns, and process data in batches, resulting in significant performance improvements for big data analytics workloads.

Understand Parquet file format and how Apache Spark makes the best of it

4. Partition Pruning (at directory level)