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

The proposed index is a compound index across home_score and away_score. MongoDB supports compound multikey indexes, but it imposes an important restriction: for any one indexed document, no more than one field covered by the compound index may contain an array. Document 1 is valid because only away_score is an array. Document 2 is also valid because only home_score is an array. Document 4 contains scalar values for both fields. Document 3 contains arrays in both indexed fields: home_score: [5,8] and away_score: [9,6] . Indexing that document would require a compound multikey index to expand two independent array dimensions, which MongoDB prohibits. Therefore document 3 prevents the compound index from being valid. The restriction is important because a single multikey field already creates multiple index keys per document; allowing multiple independently array-valued keys in the same compound index would create ambiguous and potentially combinatorial key combinations. DBAs designing indexes over document schemas with arrays must understand these multikey constraints before building compound indexes. The failing document is _id:3, making option D correct.

Study Guide reference/topic:Indexing and Query Optimization - multikey indexes, compound multikey restrictions, and array-valued fields.

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MongoDB Enterprise auditing supports three standard destination values for audit events: syslog, file, and console. With the syslog destination, audit records are sent to the operating system ' s syslog facility where supported. With the file destination, events are written to a configured audit log path, and administrators can control the output format according to the supported audit configuration. With the console destination, audit events are emitted to standard output, which can be useful in containerized or centrally collected logging environments. A raw TCP/IP port is not itself an auditLog.destination value. Organizations can certainly forward logs over the network using operating-system or observability tooling, but that transport is external to MongoDB ' s destination setting. A MongoDB database is likewise not one of the supported audit destinations; keeping audit evidence independent from the system being audited is also preferable for integrity and compliance. Auditing records security-relevant actions and can be filtered to meet regulatory or operational requirements. Therefore the three valid destinations among the choices are syslog, file, and console: A, B, and E.

Study Guide reference/topic:Security, Networking, and Encryption - auditing, auditLog.destination, compliance logging, and audit configuration.

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In MongoDB explain output, a COLLSCAN stage means the winning plan is scanning documents in the collection rather than traversing a suitable index. This is the clearest indicator that the query is not being serviced by a normal index scan for the relevant predicate. By contrast, IXSCAN explicitly indicates an index scan and typically includes details such as the index key pattern, direction, and bounds. A FETCH stage represents retrieval of full documents, often after an index has already identified candidate record locations; its presence does not imply that no index was used. GROUP relates to grouping behavior and is not the stage used to identify missing index support. A collection scan is not automatically wrong: for tiny collections or queries that return most documents, it can be efficient. However, on large collections with selective predicates, repeated COLLSCAN plans are a strong signal that the DBA should evaluate indexing. Administrators should compare totalDocsExamined, totalKeysExamined, execution time, and the winning/rejected plans before deciding to add an index. For the terminology tested by the question, COLLSCAN is the correct stage, so C is correct.

Study Guide reference/topic:Indexing and Query Optimization - explain plans, COLLSCAN, IXSCAN, and missing index diagnostics.

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