PostgreSQL Stories: From slow query to fast—via stats

The text provides an in-depth narrative about debugging a slow query in a PostgreSQL database used for Render's staging deployment pipeline, focusing on the practical application of database tools and concepts to resolve performance issues. Initially, a simple query was identified as the root cause of the delay, but understanding the data's distribution and the query's execution plan revealed inefficiencies, such as scanning unnecessary rows due to the alphabetical order of index entries. The article describes using EXPLAIN to analyze query plans, ultimately implementing manual fixes with WHERE clauses to guide the database to skip irrelevant data, achieving significant performance improvements. However, the exploration continued to identify the deeper issue: insufficient statistics on the JSON data structure within the database. By creating explicit statistics for the serviceId field, the optimizer could choose a more efficient execution plan, drastically reducing query execution time. The text concludes by highlighting the value of tools like EXPLAIN, PEV2, and PostgreSQL's pg_stats for database performance tuning, emphasizing Render's ability to manage complex cloud infrastructure while developers focus on application development.