This article explains the technical reasons behind limiting MySQL single‑table rows to around 20 million, covering primary‑key limits, InnoDB data‑page structure, B+‑tree storage math, and practical estimation methods for large‑scale databases.
This article explains MySQL's InnoDB storage engine, covering where data files are kept, the different row formats (compact, redundant, dynamic, compressed), the internal 16 KB page layout, record header fields, overflow handling, and how B‑Tree indexes (clustered and secondary) are built and accessed.
This article explains why a single MySQL table should stay below about twenty million rows by examining primary‑key limits, InnoDB data‑page structure, B+‑tree storage calculations, and provides a practical recommendation based on row size and fragmentation.
This article delves into MySQL InnoDB's storage engine, explaining the COMPACT row format, hidden columns, data page structure, page header, directory, and how B+‑tree indexes—including clustered and secondary indexes—operate and are optimized for fast queries.
This article explains how InnoDB stores data in 16 KB pages, links pages via a double‑linked list, uses page directories and primary‑key directories for binary search, and builds B+‑tree index pages to accelerate MySQL queries, covering free space, page splits, and the overall search flow.
This article explains how MySQL’s InnoDB engine stores data on disk and in memory, detailing the structure of data pages, the role of hidden columns, record linking, page headers, footers, and directory mechanisms that ensure efficient access and durability.
