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MySQL guide · Published and updated 24 September 2026

How to choose MySQL composite index column order

A composite index stores columns in a defined left-to-right order. Choose that order from important queries’ predicates, joins, ordering, and real data distribution, then confirm the optimizer can use it.

Direct answer: Put columns used together by important queries into an order that supports their usable leftmost prefix. Equality predicates often precede a range predicate, but there is no universal “most selective first” rule. Ordering, grouping, workload, and selectivity can change the best design.

Scope and version

This guide covers InnoDB indexes on MySQL 8.0 and 8.4. Index usability and optimizer decisions depend on SQL, data types, collations, statistics, and server version. It does not describe MariaDB or other engines in detail.

Understand the leftmost prefix

For an index on (customer_id, status, created_at), MySQL can use the leftmost column and prefixes such as (customer_id, status). A condition only on status generally cannot seek directly using that index’s leading key part. The optimizer may still scan the index or choose another plan, so inspect the actual plan.

CREATE INDEX idx_orders_customer_status_created ON orders (customer_id, status, created_at);

This index may support equality conditions and ordering for a query filtering customer and status, but avoiding a sort or selecting the index depends on direction, query shape, data, and optimizer costs.

Use the whole query pattern

  • Start with actual important queries: predicates, join keys, ordering, grouping, and selected columns.
  • Equality conditions are often useful before a range condition when one index serves that query, because range access can limit lookup use of later key parts.
  • For ordering and grouping, match the required sequence and direction where supported; equality constrained leading parts affect whether later parts provide order.
  • Choose based on workload, not a selectivity slogan. A selective column can help one query while reducing index reuse for another.
  • Balance covering access and narrower indexes against storage and write costs.

Common traps

Do not assume a composite index helps when SQL applies a function to a key column, compares incompatible types, uses a leading wildcard in LIKE, or filters only on a non-leading column. Prefix indexes for strings have additional limits. An index can be correctly ignored for a small table or when many rows are needed.

Verify before keeping an index

  1. Capture exact query, parameter values, schema, existing indexes, and approximate row counts.
  2. Inspect EXPLAIN: possible keys, selected key, access type, estimated rows, and extra operations.
  3. Compare representative parameter values; skew can produce different plans.
  4. On safe representative data, use EXPLAIN ANALYZE when supported and acceptable; it executes the statement.
  5. Measure read latency and write overhead against a controlled baseline. Check workload consumers before removing indexes.

Primary sources

Editorial review

Written and reviewed by the TuningLens editorial team. Published and updated 24 September 2026.

TuningLens analyzes submitted SQL and evidence; it does not inspect your live schema or guarantee gains. Review and measure proposals in your environment.

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