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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Security and Access Control | 15% | - Role-based access control - Encryption, auditing, and security best practices - Authentication mechanisms |
| Topic 2: Backup, Recovery and Maintenance | 10% | - Restore procedures and disaster recovery - Data consistency and integrity checks - Logical and physical backup methods |
| Topic 3: Monitoring, Performance and Troubleshooting | 10% | - Performance tuning and optimization - Monitoring tools and metrics - Diagnostics and resolving common issues |
| Topic 4: Replication and High Availability | 15% | - Replica set architecture and components - Deployment and maintenance of replica sets - Failover, elections, read/write concern |
| Topic 5: MongoDB Architecture and Deployment | 20% | - Storage engines and server management - Installation and configuration - Core concepts, JSON/BSON, data model |
| Topic 6: CRUD Operations and Indexing | 20% | - Create, Read, Update, Delete operations - Index types, creation, and management - Query optimization and aggregation |
| Topic 7: Sharding and Scalability | 10% | - Query routing and cluster operations - Sharded cluster architecture - Shard keys, chunk management, balancing |
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NEW QUESTION # 33
What command lists all indexes for a collection?
Answer: A
Explanation:
db.collection.getIndexes() is the mongosh method used to return the definitions of all indexes that currently exist on a collection. The result is an array of index specification documents that can show fields such as the index name, key pattern, index version, uniqueness, partial-filter settings, sparse configuration, collation, and whether the index is hidden. This makes the method useful for index audits, troubleshooting, and confirming the physical indexes available to the query planner. Option A is not a documented method for enumerating collection indexes. Option B resembles the $indexStats aggregation stage, which reports usage statistics for indexes, but db.collection.indexStats() is not the method used to list full index definitions. Option C, findIndexes(), is also not the documented mongosh collection helper. Administrators should distinguish between listing index definitions, examining index usage, and inspecting an individual query ' s winning plan:
getIndexes() addresses the first requirement, $indexStats addresses usage metrics, and explain() addresses query-planner behavior. Therefore option D is the correct command for listing all indexes on the collection.
Study Guide reference/topic:Indexing and Query Optimization - index administration, index metadata, and db.
collection.getIndexes().
NEW QUESTION # 34
Which of the following are common uses of the mongo shell? Check all that apply
Answer: A,B
NEW QUESTION # 35
Which of the following is true about sharding?
Answer: B
NEW QUESTION # 36
A department store maintains a clothing collection:
{ " _id " : 1, " item " : " sweater " , " sizes " : [ " XS " , " S " , " L " ] }
{ " _id " : 2, " item " : " t-shirt " , " sizes " : [ " S " , " M " , " L " ] }
{ " _id " : 3, " item " : " vest " , " sizes " : [ " M " , " L " , " XL " , " XXL " ] } An employee runs:
db.clothing.find( { " sizes " : " M " } )
Which index should improve performance for this query the MOST?
Answer: B
Explanation:
The query filters only on the sizes field, so the most direct supporting index is a single-field index on sizes.
Because sizes contains arrays, MongoDB automatically treats the resulting index as a multikey index and creates index entries derived from the array elements. That allows the query { sizes: " M " } to locate matching documents through the index rather than scanning every document in the collection. Option B indexes item, which is not part of the predicate and therefore does not help this query. Option C contains sizes, but _id is the leading key and the query provides no equality restriction on _id; this prevents efficient use of the later key as a standalone prefix for the query. Option D has the same structural problem because item precedes sizes and is not constrained. MongoDB ' s index-prefix rules make a targeted { sizes: 1 } index the strongest choice here. In a real workload, DBAs should also consider write overhead and whether additional queries can share a compound index before creating redundant indexes. For this single query pattern, option A is optimal.
Study Guide reference/topic:Indexing and Query Optimization - multikey indexes, array fields, index prefixes, and query support.
NEW QUESTION # 37
Suposse tou have the following collection with only 2 documents:
If you run an aggregation query and use { $unwind: "$traits" } as the first stage, how many documents will be passed to the next stage of the aggregation pipeline?
Answer: D
NEW QUESTION # 38
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