Query profiling and monitoring tools

Database Statistics and Their Maintenance

Database statistics play a crucial role in query optimization. They provide the database engine with information about data distribution, table sizes, index efficiency, and other metadata that influence query execution plans.

1. What Are Database Statistics?

Database statistics include:
✅ Table Statistics: Number of rows, table size, and distribution of values.
✅ Index Statistics: Cardinality, uniqueness, and clustering factor.
✅ Column Statistics: Minimum, maximum, and most common values (histograms).
✅ Query Execution Statistics: Cached execution plans and cost estimations.

2. Why Are Database Statistics Important?

The query optimizer relies on up-to-date statistics to:
🔹 Choose the best index for a query.
🔹 Determine whether to use full table scans, indexed lookups, or joins.
🔹 Optimize execution plans for efficiency.

📌 If statistics are outdated, the optimizer may choose inefficient execution plans, leading to poor performance.

3. Collecting and Updating Statistics

3.1 PostgreSQL: `ANALYZE` and `VACUUM`

✅ Analyze a single table:

ANALYZE customers;

✅ Analyze the entire database:

ANALYZE;

✅ Auto-Vacuum (Automatic Statistics Update)
PostgreSQL runs autovacuum to update statistics periodically.
🔹 You can fine-tune it in postgresql.conf:

autovacuum = on
autovacuum_vacuum_scale_factor = 0.2
autovacuum_analyze_scale_factor = 0.1

3.2 MySQL: `ANALYZE TABLE` and `OPTIMIZE TABLE`

✅ Update table statistics manually:

ANALYZE TABLE customers;

✅ Rebuild and optimize fragmented tables:

OPTIMIZE TABLE orders;

📌 MySQL also updates statistics automatically based on workload.

3.3 SQL Server: `UPDATE STATISTICS` and Auto-Updates

✅ Manually refresh statistics:

UPDATE STATISTICS customers;

✅ Enable automatic updates (default setting):

ALTER DATABASE mydb SET AUTO_UPDATE_STATISTICS ON;

3.4 Oracle: `DBMS_STATS` Package

✅ Gather statistics for a table:

EXEC DBMS_STATS.GATHER_TABLE_STATS('HR', 'EMPLOYEES');

✅ Gather statistics for the entire schema:

EXEC DBMS_STATS.GATHER_SCHEMA_STATS('HR');

4. Monitoring and Maintaining Statistics

✅ Check if statistics are outdated
- PostgreSQL:

SELECT relname, last_analyze FROM pg_stat_all_tables WHERE schemaname = 'public';

- MySQL:

SHOW TABLE STATUS LIKE 'customers';

- SQL Server:

SELECT name, STATS_DATE(object_id, index_id) FROM sys.stats;

✅ Schedule Automatic Maintenance
- PostgreSQL: Autovacuum does this automatically.
- SQL Server: Use sp_updatestats to refresh all table statistics.
- MySQL: Optimize and analyze large tables periodically.

5. Best Practices

🔹 Enable automatic statistics updates where possible.
🔹 Manually update statistics after major data changes.
🔹 Monitor query execution plans and adjust indexing strategies.
🔹 Avoid frequent full-table statistics updates unless necessary.
🔹 Use histograms (if supported) to improve optimizer accuracy.

Keeping database statistics updated ensures efficient query execution and optimized performance.