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포매터 및 코드

SQL 인덱스 추천

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);

편집자 노트

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

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자주 묻는 질문

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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