This article explains how SQL, built on relational algebra, became the standard analysis language for OLAP engines, covering its history, data models, syntax, functions, aggregation techniques, window functions, subqueries, and practical optimization considerations for modern data warehouses.
This article introduces Apache Calcite as a modular data‑management framework, explains its architecture and SQL processing pipeline—from parsing and validation to relational‑algebra conversion, optimization, and execution—and demonstrates a complete CSV‑based query example with code snippets.
This article walks through PostgreSQL’s query processing pipeline—from parsing SQL into relational algebra, through semantic analysis, query rewriting, optimization techniques like sub‑query elimination and join ordering, to the executor’s sequential scan algorithm—illustrating each step with code snippets and diagrams.
