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The article demonstrates, through a concrete MySQL example, how adding a seemingly small secondary index can unexpectedly inflate a table’s on‑disk size by up to 80%, explains the underlying InnoDB storage mechanics, and offers practical schema‑design recommendations to mitigate such growth.
This article explores MySQL single‑table row limits, demonstrates how to generate massive test data, explains InnoDB page and index structures, calculates theoretical maximum rows based on B+‑tree parameters, and provides practical tuning tips for handling large tables.
This article explores how MySQL tables store data in 16 KB pages, demonstrates how to generate massive test data, explains the impact of primary‑key size and B+Tree depth on query performance, and derives the practical 20 million‑row recommendation for single‑table limits.
This article experimentally explores MySQL single‑table row limits, demonstrates how to generate massive test data, analyzes InnoDB page and B+Tree index structures, and derives the commonly cited 20 million‑row recommendation by calculating storage capacity and query‑performance implications.
This article explains how MySQL InnoDB stores data in 16 KB pages, analyzes the practical limits of single‑table row counts, demonstrates data‑generation experiments, and derives the commonly cited 20 million‑row recommendation by examining B+‑tree structures, index pages, and storage parameters.
This article explains why deleting rows in MySQL does not decrease the physical table file size, describes the underlying InnoDB storage mechanisms, and shows how to reclaim space using OPTIMIZE TABLE, ALTER TABLE, and Online DDL options.
This article explains why retrieving a MySQL table's on‑disk size via INFORMATION_SCHEMA.TABLES is unreliable, describes the impact of storage engines and row formats, and shows how to obtain accurate sizes by querying INNODB_SYS_TABLESPACES, including considerations for compression and configuration settings.