C100DBA Sharding Practice Question
An administrator needs to distribute a high-throughput collection evenly across a sharded cluster using a hashed shard key. What is the primary characteristic of MongoDB's hashed sharding strategy that makes it effective for preventing write bottlenecks?
⚠ Common exam trap
Candidates often incorrectly believe that hashed sharding provides faster read performance, confusing the write-distribution benefits of random hashing with query-routing optimization.
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
✓
It computes an MD5 hash of the field value to distribute documents pseudo-randomly across all available chunks and shards, preventing single-shard write bottlenecks.
Hashed sharding applies an MD5 hash function to the specified field value before routing documents. This transforms sequential or correlated inputs into pseudo-random hash values, ensuring that writes scatter uniformly across all available cluster shards. Understanding hashed sharding mechanisms enables administrators to design resilient write-heavy architectures that prevent the single-shard bottlenecks common with monotonic keys.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
It computes an MD5 hash of the field value to distribute documents pseudo-randomly across all available chunks and shards, preventing single-shard write bottlenecks.
Why this is correct
It computes an MD5 hash of the field value to distribute documents pseudo-randomly across all available chunks and shards, preventing single-shard write bottlenecks. By randomizing the distribution of incoming documents based on their hash values, even sequential identifiers like auto-incrementing integers or timestamps achieve optimal write throughput across the cluster.
- ✗
It compresses all chunk migration payloads using cryptographic hashing algorithms to minimize network bandwidth consumption during background balancing operations.
Why it's wrong here
It compresses all chunk migration payloads using cryptographic hashing algorithms to minimize network bandwidth consumption during background balancing operations. Hashing applies exclusively to document routing keys rather than serving as a data compression utility or network optimization mechanism for balancer migrations.
- ✗
It automatically converts multi-key array fields into single scalar values to prevent indexing errors on distributed sharded collections.
Why it's wrong here
It automatically converts multi-key array fields into single scalar values to prevent indexing errors on distributed sharded collections. Hashed indexes do not support multi-key arrays and will throw an explicit error if an application attempts to shard a collection using an array field as the hash key.
- ✗
It locks the target shard during write operations to guarantee strict serializable isolation levels across distributed cluster environments.
Why it's wrong here
It locks the target shard during write operations to guarantee strict serializable isolation levels across distributed cluster environments. MongoDB does not provide distributed serializable transactions across shards by default without explicit multi-document transaction wrappers, and hashing is strictly a routing mechanism.
About these practice questions
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JA
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.