C100DBA Indexing and Performance Practice Question
A collection 'logs' receives continuous inserts and is queried by both timestamp ranges and a rarely used severity field. A DBA creates six indexes to cover every query variant, and now insert throughput has dropped sharply while index sizes dominate the working set. Which action best restores insert throughput while preserving the important query paths?
⚠ Common exam trap
The trap here is reaching for write concern or cache tuning to fix insert slowdown, when the actual cost is index maintenance from too many overlapping indexes.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Drop redundant indexes and consolidate overlapping ones into compound indexes that serve multiple query shapes.
Every index adds maintenance work to each insert, update, and delete, so a collection with many overlapping indexes suffers write amplification and cache pressure. Auditing index usage, dropping unused or redundant indexes, and consolidating overlapping prefixes into compound indexes reduces per-write maintenance while keeping the timestamp range and severity access paths covered. Write concern and cache tuning do not remove index maintenance cost.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Convert all indexes to hashed indexes to reduce index size.
Why it's wrong here
Hashed indexes support only equality matches and cannot serve timestamp range queries, which are the primary access pattern here. Converting would break the important query paths entirely while providing no benefit for ranges. This action fails to preserve required query capability and does not address the root cause of excess indexes.
- ✗
Set the collection's write concern to w:0 to avoid index maintenance waits.
Why it's wrong here
Write concern governs acknowledgement and durability, not whether index entries are written. Index maintenance still occurs on every insert regardless of acknowledgement level, so w:0 does not reduce index-related work. It only removes acknowledgment latency and durability guarantees, which is unsafe and does not solve the index bloat problem.
- ✗
Increase the WiredTiger cache size so more indexes stay resident.
Why it's wrong here
Cache size affects how much of the working set stays in memory, but it does not reduce the CPU and I/O cost of maintaining six indexes on every insert. A larger cache may mask read pressure but leaves the fundamental write amplification from excess indexes intact, so it does not restore insert throughput.
- ✓
Drop redundant indexes and consolidate overlapping ones into compound indexes that serve multiple query shapes.
Why this is correct
Each additional index must be maintained on every insert, so excess and overlapping indexes multiply write cost and consume cache. Reviewing index usage, removing unused or redundant ones, and merging overlapping prefixes into compound indexes reduces per-insert maintenance while still serving the timestamp range and severity queries. This directly restores insert throughput without sacrificing needed access paths.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official MongoDB exam blueprint
This C100DBA practice question is part of Courseiva's free MongoDB certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the C100DBA exam.