C100DBA Indexing and Performance Practice Question

Answer analysis

Option-by-option breakdown

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

• ✗

  When you need to ensure the index covers all documents.

  Why it's wrong here

  A standard index is required if the query needs to access all documents in the collection. A partial index specifically ignores documents that do not match the filter criteria, so it would fail to satisfy queries that require a full scan or search across the entire collection.

• ✓

  When only a subset of data is frequently queried.

  Why this is correct

  Partial indexes reduce index size by only including documents that meet a filter condition. This is highly effective when your application only queries active or specific subsets of data, leading to smaller index memory footprints and faster performance for those specific, high-frequency query patterns compared to full indexes.

• ✗

  To improve performance for all possible queries.

  Why it's wrong here

  Partial indexes are narrow in scope and only optimize queries that include the specific filter expression defined for the index. They do not provide broad performance benefits for every possible query, as they ignore documents not matching the criteria, potentially leading to slow performance for non-targeted queries.

• ✗

  To automatically shard the collection data.

  Why it's wrong here

  Partial indexes and sharding serve different purposes. Sharding is a horizontal scaling mechanism that partitions data across multiple nodes, whereas a partial index is a local storage optimization technique. Using a partial index does not trigger or manage the sharding process within a MongoDB cluster configuration.