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What pitfalls can occur when adding indexes to large tables?
sobes.tech AI
Answer from AI
- Execution time: Creating an index on a large table can take a significant amount of time, blocking write operations or affecting performance.
- Disk space: Indexes consume disk space. For large tables, indexes can occupy a substantial amount of space.
- Impact on write operations (INSERT, UPDATE, DELETE): When data in the table changes, related indexes must also be updated. This slows down write operations.
- Column selection: Incorrectly choosing columns for indexing can lead to inefficient use of indexes or even their being ignored by the query optimizer.
- Index redundancy: Creating a large number of indexes can degrade write performance and increase disk space usage without significant benefits for reading.
- Locks: During index creation, locks may occur, which hinder other operations on the table.
- Concurrency load: Creating an index under high concurrency can exacerbate locking and performance issues.
- Index type: Choosing an inappropriate index type (e.g., B-tree, hash index) for specific query types can reduce its effectiveness.
- Maintenance: Indexes require periodic maintenance (reorganization, rebuilding) to maintain optimal performance, especially after large data changes.