Intermediate MongoDB Interview Questions

Create an Aggregation Pipeline

Write an aggregation pipeline to find the average rating per product from a reviews collection.

Expected output: A pipeline that outputs each product with its average rating.

Hint: Use $group to calculate averages and $project to format output.

Design Indexes for Query Optimization

Given a query filtering by 'category' and sorting by 'price', design an appropriate index.

Expected output: An index definition that supports efficient filtering and sorting.

Hint: Consider a compound index on category and price fields.

An aggregation pipeline is a framework for data aggregation modeled as a sequence of stages that transform documents. Each stage performs an operation like filtering, grouping, or sorting to produce aggregated results.

Indexes allow MongoDB to quickly locate documents without scanning the entire collection, significantly speeding up query execution by using data structures optimized for search.

Replica sets provide data redundancy and high availability by maintaining multiple copies of data across servers. They enable automatic failover and read scaling.

Embed data when related information is frequently accessed together and is relatively small. Use references when data is large, changes independently, or has complex relationships.