SQL Performance Quant Interview Guide
SQL performance quant interview guide for filters, indexes conceptually, joins, aggregation, explain plans, tradeoffs, and examples.
Candidates writing queries over larger research or event tables.
Performance starts with less data
Filter early when it preserves correctness, select only needed columns, and aggregate at the right grain. Smaller intermediate tables are usually easier to execute.
Indexes are access paths
An index can speed up filters, joins, and ordering when it matches the query pattern. The exact behavior depends on database engine and data distribution.
Concrete example
A query filtering trades by date and symbol may benefit from storage or indexing aligned with those fields, but only if the filter is selective.
Explain plans are evidence
When performance matters, inspect whether the query scans, joins, sorts, or materializes more data than expected. Use the plan to guide changes.
Common mistakes
Candidates often optimize before proving correctness. A fast wrong query is still wrong, so keep validation in the loop.
Practice the pattern
Use the LeetQuidity curriculum and calibration to turn this topic into a focused practice plan.