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MongoDB C100DBA Exam Syllabus Topics:

Section	Objectives
Topic 1: Security	- Encryption at rest and in transit - Authentication and authorization - Role-based access control (RBAC)
Topic 2: Aggregation Framework	- Data transformation and grouping - Aggregation operators - Aggregation pipeline stages
Topic 3: Data Modeling	- Schema design principles - Embedding vs referencing - Relationships in MongoDB
Topic 4: Replication and High Availability	- Replica set architecture - Read/write concerns - Failover and elections
Topic 5: Indexing and Performance Tuning	- Query performance optimization - Index types and usage - Explain plans and diagnostics
Topic 6: Sharding and Scalability	- Shard keys and distribution strategy - Balancing and scaling operations - Sharded cluster architecture
Topic 7: Backup, Restore, and Operations	- Monitoring and maintenance - Restore procedures - Backup strategies and tools
Topic 8: MongoDB CRUD Operations	- Working with documents and BSON types - Insert, update, and delete operations - Querying and filtering documents

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MongoDB Certified DBA Associate Exam (Based on MongoDB 4.4) Sample Questions (Q123-Q128):

NEW QUESTION # 123
Which of the following aggregation commands in MongoDB does not support sharded collections?

A. mapReduce
B. aggregate
C. All of the above
D. group

Answer: D

NEW QUESTION # 124
If the value of totalKeysExamined is 30000 and the value of totalDocsExamined is 0, which of the following option is correct?

A. The query used an index to fetch the results
B. The query returned 30000 documents after scanning the documents
C. None of the above
D. The query returned 0 documents

Answer: A

NEW QUESTION # 125
A MongoDB administrator needs to create a new role with only the read privileges for the products database.
What command should the administrator use?

A. db.createRole({ role: " productRead " , privileges: [ { resource: { db: " products " , collection: " * " }, actions: [ " readAnyDatabase " ] } ] , roles: [] }, { w: " majority " , wtimeout: 5000 })
B. db.createRole({ role: " productRead " , privileges: [ { resource: { db: " products " , collection: " " }, actions: [ " find " ] } ] , roles: [] }, { w: " majority " , wtimeout: 5000 })
C. db.createRole({ role: " productRead " , privileges: [ { resource: { db: " products " , collection: " * " }, actions: [ " readWrite " ] } ] , roles: [] }, { w: " majority " , wtimeout: 5000 })
D. db.createRole({ role: " productRead " , privileges: [ { resource: { db: " products " , collection: " * " }, actions: [ " read " ] } ] , roles: [] }, { w: " majority " , wtimeout: 5000 })

Answer: B

Explanation:
MongoDB custom roles are defined in terms of privileges, and each privilege specifies a resource plus one or more allowed actions. For read/query access, find is a valid privilege action. To represent all normal collections in a specified database, MongoDB uses a resource document with the target database and an empty collection name, for example { db: " products " , collection: " " }. Option B therefore combines the correct resource scope with the find action and does not grant write capability. The distractors confuse built-in role names with privilege actions. read, readWrite, and readAnyDatabase are built-in roles or role concepts, not the appropriate action values for the privileges[].actions list shown here. Likewise, a literal " * " collection value is not the documented database-wide resource form for this custom privilege. In practice, an administrator could also assign MongoDB ' s built-in read role rather than creating a custom role if its permissions exactly match the requirement. Given the specific createRole() choices, however, option B is the technically correct construction.
Study Guide reference/topic:Security, Networking, and Encryption - RBAC, custom roles, resources, and privilege actions.

NEW QUESTION # 126
Consider a contacts collection that contains these documents:
{ " _id " : 1, " name " : " Poppy " , " birthday " : " 03-09-1984 " }
{ " _id " : 2, " name " : " Ashley " , " birthday " : " 08-12-1990 " }
{ " _id " : 3, " name " : " Cleo " , " birthday " : " 11-02-1976 " }
What query returns the document where the field name is " Poppy " ?

A. db.contacts.find({ " Poppy " : 1 })
B. db.contacts.find({ " name " : " Poppy " })
C. db.contacts.find({ " name.Poppy " : 1 })
D. db.contacts.find({ " name " : " poppy " })

Answer: B

Explanation:
MongoDB equality filters use the form { field: value }. To return the document whose name field contains the exact string " Poppy " , the query therefore uses { name: " Poppy " }, as shown in option D. This shorthand equality syntax is equivalent to explicitly using $eq. Option B uses the correct field but the value is lowercase
" poppy " . Normal MongoDB string equality is case-sensitive unless a suitable collation or another case- insensitive technique is deliberately configured, so it does not match the displayed " Poppy " value. Option A uses name.Poppy as a dot-notation path. Dot notation is for accessing a nested field inside an embedded document, but here name stores a scalar string and has no nested Poppy field. Option C searches for a field literally named Poppy, which the sample documents do not contain. This question tests the basic field/value predicate syntax used by find(). The correct command is db.contacts.find({ " name " : " Poppy " }), making option D correct.
Study Guide reference/topic:MongoDB Architecture and Core Operations - find(), equality predicates, string matching, and dot notation.

NEW QUESTION # 127
Below is a sample document in a given collection test.
{ a : 5, b : 3, c: 2, d : 1 >
Given a compound index { a: 1, b:l, c:l, d:l}, Which of the below query will not use in-memory sorting? Select all valid.

A. db.test.find( { a: 5, b: 3 } ).sort( { a: 1, b: 1, c: 1 > )
B. db.test.find( { a: 5, b: 3 } ).sort( { c: 1, d : 1 } )
C. db.test.find( { a: 5, b: 3 } ).sort( { a: 1} )
D. db.test.find( { a: 5, b: 3 } ).sort( {c: 1 } )

Answer: B,D

NEW QUESTION # 128
......

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