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Recommandation d'index SQL

Spot missing indexes from WHERE / JOIN / ORDER clauses.

Runs in your browser

Recommendations · 4

  • u.created_athigh

    Used in WHERE — high selectivity benefit

    CREATE INDEX idx_u_created_at ON …(created_at);
  • p.author_idhigh

    Join column — index speeds up the lookup

    CREATE INDEX idx_p_author_id ON …(author_id);
  • u.idhigh

    Join column — index speeds up the lookup

    CREATE INDEX idx_u_id ON …(id);
  • postsmed

    ORDER BY — composite index can avoid filesort

    CREATE INDEX idx_posts ON …(posts);

Note de la rédaction

Understanding · B-trees by default — and the five other kinds for when they're not enough.

Ce chapitre approfondi n'est actuellement disponible qu'en anglais. L'outil de conversion ci-dessus fonctionne dans votre langue ; le long article explicatif n'a pas encore été traduit.

Questions fréquentes

Quick answers.

Which SQL dialects are supported?

The analyzer works with standard SQL syntax compatible with PostgreSQL, MySQL, and SQL Server. It focuses on identifyng `WHERE`, `JOIN`, and `ORDER BY` clauses common to all relational engines.

Does this tool access my database?

No. The analyzer is a static parser that runs entirely in your browser. It evaluates the text of your query and does not require a connection to your live database infrastructure.

Why does it suggest composite indexes?

Composite indexes are recommended when a query filters on multiple columns simultaneously. This allows the database engine to locate records more efficiently than using two separate single-column indexes.

Are there risks to adding too many indexes?

Yes. While indexes speed up read operations, they slow down `INSERT`, `UPDATE`, and `DELETE` actions because the index must also be updated. Only implement recommendations for queries that run frequently or are noticeably slow.

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