SQL tuning and database performance essentials Databases often slow down as data grows or queries become more complex. Tuning is about understanding how the engine executes SQL and making small, safe changes that add up. The goal is to move work efficiently from disk to result, with fewer full scans and less waiting time for users.
Common bottlenecks Missing or weak indexes for frequent filters and joins. Queries that fetch more data than needed or use SELECT * Outdated statistics that lead the planner to choose expensive plans. Large temporary data and inefficient joins. Contention and locking under high concurrent load. Practical steps to improve performance Establish a baseline: track slow queries, their frequency, and current runtimes. Collect data over several days if possible. Inspect queries with execution plans: run EXPLAIN ANALYZE and look for sequential scans on big tables, large costs, or unexpected nested loops. Tune the query first: fetch only needed columns, reduce joins, push predicates earlier, and avoid heavy subqueries. Improve indexing: add indexes on columns used in WHERE, JOIN, and ORDER BY. Consider composite or covering indexes, but avoid over-indexing. Check statistics and maintenance: regularly ANALYZE or UPDATE STATISTICS so the planner sees current data distribution. Configure for the workload: tune memory settings such as work_mem or the equivalent in your engine to keep hot data in memory, without oversizing. Monitor and iterate: set up a simple monitor for slow queries and plan changes. Recheck plans after adjustments. Quick example A query on users that joins orders and filters by a date range can be slow if there is no index on (user_id, order_date). Adding that composite index often shifts the plan from a full scan to an index scan, cutting runtime noticeably.
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