Apache Parquet is a game-changer in the world of big data processing and analytics. Unlike traditional row-based formats like CSV or JSON, Parquet stores data in a columnar format. This means each column's values are stored together, enabling super-efficient compression, encoding, and data processing. Why Parquet? 🔹 Efficient Storage : Columnar format means better compression and reduced storage costs. 🔹 Faster Queries : Only read the columns you need, speeding up query performance. 🔹 Optimized for OLAP : Supports both projection (selecting columns) and predicates (row selection criteria), perfect for complex analytical workflows.   Minimize image Edit image Delete image We’ll delve into the intricate details of how Parquet files are structured, how metadata and data pages are organized, and why concepts like dictionary encoding and predicate pushdown play a crucial role in optimizing data storage and query performance. Structure of Parquet Files: Parquet files are organized in ...