PostgreSQL Server Capacity Planning and Optimization: Conduct a thorough assessment of current and projected workload demands on the database server's critical resources. This evaluation should cover key factors such as CPU utilization, RAM consumption, storage requirements, I/O performance, and network bandwidth usage. Consider both short-term fluctuations and long-term usage patterns to accurately forecast future needs and potential bottlenecks. Collect and analyze performance metrics over extended periods, including peak and off-peak hours, to gain a comprehensive understanding of server behavior. Use appropriate monitoring tools to gather detailed data on query execution times, resource utilization patterns, and system responsiveness under varying loads. Identify recurring performance issues, resource contention points, or capacity limitations that may affect the overall efficiency of the PostgreSQL environment. Based on this analysis, develop actionable recommendations...
PostgreSQL’s VACUUM and VACUUM FULL are not separate processes but rather different operational modes of the same maintenance command. Here’s why: Core Implementation Both commands share the same underlying codebase and are executed through the vacuum_rel() function in PostgreSQL’s source code ( src/backend/commands/vacuum.c ). The key distinction lies in the FULL option, which triggers additional steps: Standard VACUUM : Removes dead tuples (obsolete rows) and marks space reusable within PostgreSQL Updates the visibility map to optimize future queries Runs concurrently with read/write operations VACUUM FULL : Rewrites the entire table into a new disk file, compressing it and reclaiming space for the operating system Rebuilds all indexes and requires an ACCESS EXCLUSIVE lock, blocking other operations Key Differences in Behavior Aspect Standard VACUUM VACUUM FULL Space Reclamation Internal reuse onl...