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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11An index can make a query slower because it gives the database another possible execution plan, not an instruction to use that index. If many rows match, fetching them through the index—especially when they are scattered across the table—can cost more than reading the table sequentially. The right diagnosis comes from comparing execution plans and timings before and after the change; the index alone does not establish the cause.
How an index can add work instead of removing it
An index helps locate rows without scanning every table row, but an ordinary index scan can involve two kinds of access: reading the index and then fetching the matching rows from the table. If a query returns many rows, or those rows require scattered table access, that route may be more expensive than a sequential scan. PostgreSQL documents this distinction for index scans and index-only scans in its index-only scan guidance.
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The planner chooses among available plans using estimated costs. PostgreSQL explains that its planner considers possible paths and selects one based on those estimates in its planner and optimizer documentation. An index may therefore be ignored because another plan looks cheaper, or used even when the estimates do not match the workload well.
Compare the plans before blaming the index
Capture the exact query, schema, database engine and version, parameter values, and representative data conditions. Then inspect the plan before and after adding the index with the engine’s EXPLAIN facility. A plan shows what the optimizer selected; in PostgreSQL, EXPLAIN can also report execution statistics when requested. See the PostgreSQL EXPLAIN documentation.
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- Note the chosen scan type and whether the new index is used.
- Compare estimated rows with actual rows where execution statistics are available.
- Look at filters, joins, rows fetched, heap fetches, and any additional sorting work.
- Compare elapsed time under comparable cache and system-load conditions.
Do not read PostgreSQL EXPLAIN cost units as milliseconds. EXPLAIN ANALYZE executes and profiles the statement, and that profiling adds overhead, so interpret its timing in context rather than treating it as a perfectly isolated measurement.
Check whether the index fits the query
An index is useful only when the query’s conditions and requested data align with what the index can support. Check whether the predicate targets the indexed column or columns, and whether the query returns so many matching rows that repeated index-to-table lookups become costly. An index can also be valuable when it supplies ordering or covers the data needed by the query, but that benefit depends on the plan and the workload.
In PostgreSQL, an index-only scan can avoid heap reads when its conditions are met; it is not guaranteed merely because an index contains relevant columns. The engine’s index-only scan documentation describes the requirements and behavior.
Verify planner statistics and correlated filters
The planner relies on statistics to estimate how many rows a condition will return. If the data has changed substantially or the estimates look unlike actual row counts, refresh or verify the statistics. PostgreSQL’s index usage guidance states: “Always run ANALYZE first.” Its documentation explains that ANALYZE gathers distribution information used for row and cost estimates; substantial table changes may warrant running it manually.
When a query filters on multiple correlated columns, estimates based on an independence assumption can be misleading. PostgreSQL supports extended statistics for selected column groups; see Statistics Used by the Planner. This is a targeted option when the plan’s row estimates suggest that ordinary statistics are not representing the relationship between those columns.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Decide whether to keep the index across the workload
Do not drop an index solely because one query does not use it or became slower after it was added. Judge it against the queries it helps as well as the costs it imposes: indexes consume storage and need maintenance as data changes. PostgreSQL discusses these trade-offs in its index usage guidance; MySQL likewise documents index space, optimizer work, and insert, update, and delete overhead in its optimization and indexes guide.
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For MySQL, use its execution-plan information for the corresponding engine-specific plan review: Understanding the Query Execution Plan. Exact plan details and available features vary by database engine and version, so confirm the documentation for the version you run.
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