Lookup joins related collections during aggregation. Its cost depends on matching keys, indexes and the number of input documents.
Before you start
You should understand documents, collections and indexes. Sketch representative documents and the reads and writes they must support. MongoDB-specific examples assume a collection with the shown fields; deployment topology, permissions and existing indexes can affect the operational behavior being discussed.
The practical goal is to reason through this situation: Join a bounded page of orders to customer details. Read the walkthrough first, then try the interview exercise before opening its answer. The important part is explaining the decision and its consequences, rather than remembering a definition alone.
Step-by-step walkthrough
Step 1: Bound the listing
Determine which filters and ordering define the requested page.
Step 2: Index the relationship
Provide an appropriate foreign-key access path for the join.
Step 3: Fetch needed fields only
Avoid expanding unrelated data when the response needs a small projection.
Worked scenario
Join a bounded page of orders to customer details.
A page of 24 orders needs customer names. Joining every historical order before applying an otherwise valid page boundary can perform unnecessary work. Moving the boundary is safe only if joined data does not determine eligibility or sorting; otherwise it can select the wrong page.
Common mistake
Joining a huge collection and paginating afterward can do unnecessary work.
Verify the behavior
Compare result semantics and examined work before and after stage changes.
Interview exercise
Design an efficient listing.
Answer and reasoning
Filter and limit according to correct ordering semantics, index the relationship and avoid fetching unused related data.
Continue learning
Compare the scenario with the MongoDB interview questions and test your understanding with the MongoDB MCQs. For terminology and implementation details, consult the reference material.