MongoDB Certified DBA Associate Exam (Based on MongoDB 4.4) valid test questions & C100DBA pdf vce & C100DBA torrent dumps

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MongoDB C100DBA Exam Syllabus Topics:

Section	Objectives
Sharding	- Cluster Scaling 1. Query Routing 2. Shard Keys 3. Chunk Distribution 4. Balancer Operations
Application Administration	- Security and Access Control 1. Authorization 2. Authentication 3. Role-Based Access Control 4. User Management
Replication	- Replica Sets 1. Read Preferences 2. Primary and Secondary Nodes 3. Write Concerns 4. Elections
Server Administration	- Database Operations 1. Storage Management 2. Monitoring 3. Backup and Restore 4. Configuration Management
Philosophy and Features	- MongoDB Architecture 1. Scalability Concepts 2. Collections and Databases 3. High Availability Concepts 4. Document Model
CRUD Operations	- Data Manipulation 1. Update Operations 2. Insert Operations 3. Read Queries 4. Delete Operations
Indexes	- Index Management 1. Query Performance Optimization 2. Compound Indexes 3. Single Field Indexes 4. Index Selection

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MongoDB Certified DBA Associate Exam (Based on MongoDB 4.4) Sample Questions (Q115-Q120):

NEW QUESTION # 115
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?

A. db.clothing.createIndex( { item: -1 } )
B. db.clothing.createIndex( { item: 1, sizes: 1 } )
C. db.clothing.createIndex( { _id: 1, sizes: 1 } )
D. db.clothing.createIndex( { sizes: 1 } )

Answer: D

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 # 116
Below is a sample document of " orders " collection

Answer:

Explanation:
$project

NEW QUESTION # 117
Consider that you have a collection called population which has fields state and city. Which of the following query will calculate the population grouped by state and city?

A. db.population.aggregate( [{ $group: { _id: { state: Estate", city: n$city" },pop: { $sum: "$pop" } } }] )
B. db.population.aggregate( [{ $group: { _id: { state: Estate", city: "$city" },pop: { $pop: 1 } } }] )
C. db.population.aggregate( [{ $group: { _id: { state: "$state", city; "$city" },pop: { $sum: 1 > > >] )
D. db.population.aggregate( [{ $group: { _id: { city: "$city" },pop: { $sum: "$pop" } } }] )Multi Document Transaction is not supported by MongoDB

Answer: A

NEW QUESTION # 118
In a replica set with a primary and two secondaries, what should the write concern be set to so only a single node is required to acknowledge a write operation before it is deemed successful?

A. { writeConcern: { w: 1 } }
B. { writeConcern: 1 }
C. { writeConcern: { w: " 1 " } }
D. { writeConcern: " 1 " }

Answer: A

Explanation:
MongoDB write concern defines the level of acknowledgment requested for a write. Setting the numeric value w: 1 means that a write is considered acknowledged after the primary has accepted it; no secondary acknowledgment is required. In a replica set with one primary and two secondaries, those secondaries can replicate the operation asynchronously after the client has already received success. That configuration is represented by { writeConcern: { w: 1 } }, making option D correct. The numeric type matters: w can be specified as an integer count or certain strings such as " majority " , but the string " 1 " is not the intended numeric node count shown by the question. Options B and C also omit the w field structure expected inside a write concern document. The durability trade-off is important: a w:1 write can be acknowledged before any secondary has replicated it, so a sudden primary failure before replication may result in that write being rolled back after failover. If the workload requires stronger durability, w: " majority " is commonly used. For exactly one acknowledging node, however, the correct setting is D.
Study Guide reference/topic:Cluster Reliability and Data Resilience - write concern, w acknowledgments, replica-set durability, and rollback risk.

NEW QUESTION # 119
Which mongodb tools allow us to work with our data in a human readable format?

A. mongoimport
B. mongostat
C. mongodump
D. mongoexport

Answer: A,D

NEW QUESTION # 120
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