Which of the following descriptions of database SQL optimization methods is wrong?

Question

Options

• AUse paging query to avoid throughput of all data at once, which can reduce data network traffic.
• BB-Tree index reduces hard disk IO operations according to query conditions and improves query
• CReduce large-scale transaction operations in the business, avoid processing too much data in one
• DAppropriately increase cache capacity to increase cache hit rate and reduce hard disk IO load

• A
  11% (2)
• B
  5% (1)
• C
  79% (15)
• D
  5% (1)

Explanation

Option C is the odd one out because it describes a business logic / application-layer design strategy - managing transaction scope and batch size - rather than a true SQL optimization technique. SQL optimization concerns how queries retrieve data efficiently (indexes, caching, pagination), not how an application structures its business transactions. The other three options each describe a direct, query-level optimization.

• A is correct: Pagination (e.g., LIMIT/OFFSET) fetches only a page of rows at a time, genuinely reducing the volume of data transferred over the network per request.
• B is correct: B-Tree indexes let the engine jump directly to matching rows via a tree traversal instead of scanning every row, cutting disk I/O substantially.
• D is correct: A larger buffer/cache (e.g., MySQL's InnoDB buffer pool) holds more data in memory, so repeated reads hit RAM instead of disk, lowering I/O load.

Memory tip: Group the three correct answers by where they act - A optimizes network transfer, B optimizes disk lookup, D optimizes disk reads via memory. C is the only one that targets how many operations a business process runs, making it the misfit when the question is specifically about SQL-level optimizations.

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