Programming Tutorials

  There are few log entries as frustrating to a backend engineer as   ERROR 1213 (40001): Deadlock found when trying to get lock; try restarting transaction . It often appears sporadically under high load, vanishing when you attempt to reproduce it locally. While the error message suggests a simple retry, treating Error 1213 merely as a signal to "try again" is a mistake. In high-throughput systems—like payment gateways or inventory management systems—deadlocks are symptoms of conflicting access patterns that degrade database performance and user experience. This guide moves beyond generic advice. We will analyze how InnoDB handles locking, dissect a real-world eCommerce deadlock scenario, and implement an architectural solution to resolve it. The Anatomy of an InnoDB Deadlock To fix a deadlock, you must first understand what InnoDB is actually locking. A common misconception is that MySQL locks specific rows of data. In reality,  InnoDB locks index records. If you execut...

  You have identified a slow API endpoint. You enabled the slow query log, isolated the bottleneck SQL statement, and realized a crucial   WHERE   clause was filtering on an unindexed column. You confidently deployed a migration to add a B-Tree index. You ran the migration, verified the schema, and triggered the query again. The result? The query is still slow. When you run  EXPLAIN ANALYZE , you see the dreaded words:  Seq Scan  (PostgreSQL),  Table Scan  (SQL Server), or  ALL  (MySQL). The optimizer is completely ignoring your new index. This is not a bug in the database engine. It is a mathematical decision made by the Cost-Based Optimizer (CBO). This article explores exactly why databases ignore indexes and provides the rigorous technical fixes required to resolve it. The Cost-Based Optimizer: It's Just Math To fix the problem, you must understand the "Why." The Query Optimizer’s job is not to use indexes; its job is to retrieve data...