Pass the MongoDB Certified DBA Associate C100DBA Questions and answers with ExamsMirror

The query first applies .sort({ price: -1 }). In MongoDB, -1 specifies descending order, so the result stream is ordered from the highest price to the lowest: Laptop at 1500, Smartphone at 800, Tablet at 600, Monitor at 300, and Headphones at 200. The subsequent .limit(2) restricts the cursor to the first two documents in that sorted sequence. Therefore, only Laptop and Smartphone are returned. Option B identifies the two lowest-priced products rather than the highest. Option C reflects the sort but ignores the limit(2) stage. Option D shows the two lowest products in ascending order and therefore contradicts both the requested sort direction and the limit semantics. For a large collection, a single-field index on price could support this sort efficiently because MongoDB can traverse an index in either direction; an ascending index can be scanned backward to satisfy a descending sort and vice versa. The logical query result, however, is independent of whether such an index exists. Option A is the correct output.

Study Guide reference/topic:MongoDB Architecture and Core Operations - cursor sorting, limiting result sets, and query result ordering.

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A replica-set secondary maintains a replicated copy of the primary ' s dataset. The primary records data-changing operations in its oplog, and secondary members continuously copy and apply those oplog entries asynchronously to keep their data synchronized. This redundancy allows an eligible secondary to participate in an election and potentially become primary if the current primary becomes unavailable. mongos, option B, is the query-routing process used in a sharded cluster; it does not store an application dataset copy. An arbiter, option C, participates in replica-set voting and elections but deliberately does not maintain a copy of the database data. A shard, option D, is a data partition in a sharded cluster and is normally implemented as a replica set in production, but “shard” is not the replica-set member role that replicates the primary ' s data. Secondary behavior is central to MongoDB high availability, read-scaling options, backup strategies, and failover. Administrators monitor secondary replication lag and health to ensure the copies remain sufficiently current. Therefore the member responsible for maintaining copies of the primary ' s data is the secondary, making option A correct.

Study Guide reference/topic:Cluster Reliability and Data Resilience - replica-set primaries, secondaries, oplog replication, and redundancy.

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When MongoDB ' s winning query plan uses a B-tree index, the plan includes an IXSCAN stage. That stage contains the index-specific information a DBA needs to identify how the query is being serviced, including the key pattern, index name, traversal direction, and index bounds. For example, keyPattern can show a compound definition such as { status: 1, createdAt: -1 }, making it straightforward to confirm which indexed keys participate in the chosen plan. A FETCH stage indicates that MongoDB is retrieving full documents, often after an index has produced candidate record identifiers; the fetch stage itself does not identify the index key. A COLLSCAN stage means MongoDB is scanning the collection and therefore is not using a normal index scan for the predicate. GROUP is unrelated to index selection. Effective DBA query analysis usually involves inspecting both queryPlanner.winningPlan and execution statistics such as totalKeysExamined, totalDocsExamined, and nReturned. But for the narrow question of which stage exposes the index key used by the winning plan, IXSCAN is the correct answer. Therefore option C is correct.

Study Guide reference/topic:Indexing and Query Optimization - explain output, winning plans, IXSCAN, key patterns, and index bounds.

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The first argument to find() is the query filter and the second argument is the projection. Because the requirement applies to every employee, the filter must be an empty document {}. The projection must include name and age while explicitly suppressing _id. MongoDB includes _id by default even in inclusion projections, so { name: 1, age: 1 } would return three fields: _id, name, and age. Adding _id: 0 is the documented exception that allows _id to be excluded from an otherwise inclusion-style projection. Option C therefore produces exactly the requested fields. Options A and B mistakenly place projection-like expressions in the filter position, which would cause MongoDB to search for documents where those fields literally match the specified values rather than controlling returned fields. Option D is close but violates the word “ONLY” because _id remains present. Projection design can also reduce network traffic and, when a suitable index covers both the predicate and projected fields, can contribute to covered-query plans. For this requirement, however, the essential syntax is find({}, {name:1, age:1, _id:0}), so C is correct.

Study Guide reference/topic:MongoDB Architecture and Core Operations - find(), filters, projections, inclusion fields, and _id exclusion.

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