InterviewStack.io LogoInterviewStack.io

Indexing Strategy and Selection Questions

Covers index design principles and practical selection of indexes to accelerate queries while managing storage and write cost. Topics include index types such as B tree hash and bitmap indexes and full text and functional indexes; single column composite and covering indexes; clustered versus nonclustered index architectures and partial or filtered indexes. Candidates should reason about index selectivity and cardinality and how statistics and histograms influence optimizer choices. Also assess index maintenance overhead fragmentation and rebuild strategies and the trade off between faster reads and slower inserts updates and deletes. Practical skills include reading execution plans to identify missing or inefficient indexes proposing index consolidation or covering index designs testing and benchmarking index changes and understanding interactions between indexing partitioning and denormalization.

HardTechnical
0 practiced
Create an index audit plan for a reporting schema that contains 500 tables and 1,200 indexes. Which automated checks would you implement to find unused, duplicate, or highly-costly indexes, how would you prioritize candidates for removal, and what safety checks would you include before dropping indexes in production?
HardTechnical
0 practiced
You are asked to lead a cross-functional project to cut dashboard latency by 50% using indexing, partitioning, and denormalization. Outline a project plan: stakeholders, phases (discovery, prototype, benchmark, rollout), risk assessment, rollback strategy, and key validation steps you would include.
MediumTechnical
0 practiced
Compare full-text indexes with traditional B-tree indexes for BI search features such as product description search. Cover differences in query capabilities (tokenization, ranking), storage, and recommended scenarios for use in dashboards and ad-hoc exploration.
MediumTechnical
0 practiced
Write a PostgreSQL CREATE INDEX statement for a filtered index that accelerates queries frequently run by analysts: WHERE status = 'completed' AND amount > 1000. Explain how this reduces index size and maintenance cost compared to a full index.
HardTechnical
0 practiced
Describe advanced remedies when optimizer chooses a nested-loop plan due to histogram skew on a highly-skewed column: options include increasing histogram resolution, creating filtered statistics, using extended statistics (multi-column), rewriting predicates, or enforcing join hints. Discuss trade-offs and long-term maintenance implications.

Unlock Full Question Bank

Get access to hundreds of Indexing Strategy and Selection interview questions and detailed answers.

Sign in to Continue

Join thousands of developers preparing for their dream job.