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MongoDB C100DBA Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: MongoDB Architecture and Deployment	20%	- Installation and configuration - Core concepts, JSON/BSON, data model - Storage engines and server management
Topic 2: Security and Access Control	15%	- Authentication mechanisms - Role-based access control - Encryption, auditing, and security best practices
Topic 3: Sharding and Scalability	10%	- Shard keys, chunk management, balancing - Query routing and cluster operations - Sharded cluster architecture
Topic 4: Backup, Recovery and Maintenance	10%	- Data consistency and integrity checks - Restore procedures and disaster recovery - Logical and physical backup methods
Topic 5: Replication and High Availability	15%	- Failover, elections, read/write concern - Deployment and maintenance of replica sets - Replica set architecture and components
Topic 6: Monitoring, Performance and Troubleshooting	10%	- Performance tuning and optimization - Diagnostics and resolving common issues - Monitoring tools and metrics
Topic 7: CRUD Operations and Indexing	20%	- Index types, creation, and management - Create, Read, Update, Delete operations - Query optimization and aggregation

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MongoDB Certified DBA Associate Exam (Based on MongoDB 4.4) Sample Questions (Q54-Q59):

NEW QUESTION # 54
A collection named scores includes:
[
{ _id: 1, home_score: 6, away_score: [ 5, 7 ] },
{ _id: 2, home_score: [ 8, 6 ], away_score: 9 },
{ _id: 3, home_score: [ 5, 8 ], away_score: [ 9, 6 ] },
{ _id: 4, home_score: 5, away_score: 10 }
]
Given the following index:
db.scores.createIndex( { home_score: 1, away_score: 1 } )
What document will cause the index to fail?

A. Document with _id: 2
B. Document with _id: 1
C. Document with _id: 4
D. Document with _id: 3

Answer: D

Explanation:
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.

NEW QUESTION # 55
The following aggregation option is used to specify the specific fields that needs to be passed to the next stage of the aggregation pipeline:

A. $aggregate
B. $project
C. $group
D. $match

Answer: B

NEW QUESTION # 56
Dada una coleccion, cuales devuelve con la siguiente query
db.coleccion.find({nombre:"ruben",apellido:"gomez"},{nombre:l,apellido:l,aficion:l});

A. { "-id" : Objectld("580a42b5dfblb5al7427d302"), "nombre" : "ruben", "apellido" : "gomez", "aficion" :
v u "flipar" }
B. { "_id" : Objectld("580a42acdfblb5al7427d301"), "nombre" : "ruben", "apellido" : "gomez" >
C. { "_id" : Objectld("580a42acdfblb5al7427d301"), "nombre" : "ruben", "apellido" : "Pablo" , "aficion" : u
"flipar"}
D. { "_id" : Objectld("580a42acdfblb5al7427d301"), "nombre" : "Luis", "apellido" : "gomez", "aficion" : u
"flipar" }

Answer: A,B

NEW QUESTION # 57
You have a replicated cluster with 1 primary, 3 secondary, 1 arbiter. One of the secondary is hidden. What is the replication factor of this replicated cluster?

A. 06
B. 0
C. 04
D. 03

Answer: C

NEW QUESTION # 58
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: " $city " },pop: { $sum: " $pop " } }
}] )
B. db.population.aggregate( [{ $group: { _id: { city: " $city " },pop: { $sum: " $pop " } } }] )Multi Document Transaction is not supported by MongoDB
C. db.population.aggregate( [{ $group: { _id: { state: " $state " , city: " $city " },pop: { $pop: 1 } } }] )
D. db.population.aggregate( [{ $group: { _id: { state: Estate " , city: " $city " },pop: { $sum: 1 > > > ] )

Answer: A

NEW QUESTION # 59
......

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