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FC0-U71 Practice Question: A small e-commerce website uses a relational…

A small e-commerce website uses a relational database to manage its products and orders. The most common query is retrieving a product by its unique product ID. This query is executed thousands of times per minute. The database currently has no indexes, and the query is slow, causing user-facing delays. The database administrator wants to improve performance with minimal downtime and cost. Which action should be taken first?

⚠ Common exam trap

It's easy for candidates to choose increasing memory (Option C) because they confuse caching with indexing, not realizing that caching only helps after the first access and does not prevent full table scans on cache misses or for new data.

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

Add an index on the product ID column

Adding an index on the product ID column creates a B-tree data structure that allows the database to locate rows using a logarithmic search instead of a full table scan. Since the query is executed thousands of times per minute and the table has no indexes, this single-column index directly addresses the bottleneck with minimal downtime and cost, as it requires only a CREATE INDEX statement.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Partition the table by product category

    Why it's wrong here

    Partitioning helps with range scans, not exact ID lookups.

  • Add an index on the product ID column

    Why this is correct

    An index on the searched column accelerates lookups.

  • Increase the server's memory to allow more caching

    Why it's wrong here

    Caching helps but adding an index is more fundamental.

  • Change the database to a NoSQL system for faster key-value access

    Why it's wrong here

    Migrating to a NoSQL system would introduce a fundamentally different data model, breaking the existing relational schema that manages products and orders with joins and transactions, thus requiring a full application rewrite and causing significant downtime and cost. It is tempting because NoSQL databases are optimised for key-value lookups by a unique identifier, which matches the described query pattern; in a greenfield project where the data model is simple and consistency requirements are low, this would be a correct choice.

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