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MongoDB C100DBA Exam Syllabus Topics:

Section	Objectives
Topic 1: Application Administration	- Security and Access Control 1. Authentication 2. User Management 3. Role-Based Access Control 4. Authorization
Topic 2: Server Administration	- Database Operations 1. Monitoring 2. Backup and Restore 3. Storage Management 4. Configuration Management
Topic 3: Replication	- Replica Sets 1. Elections 2. Primary and Secondary Nodes 3. Read Preferences 4. Write Concerns
Topic 4: Indexes	- Index Management 1. Compound Indexes 2. Index Selection 3. Query Performance Optimization 4. Single Field Indexes
Topic 5: Philosophy and Features	- MongoDB Architecture 1. Document Model 2. High Availability Concepts 3. Collections and Databases 4. Scalability Concepts
Topic 6: Sharding	- Cluster Scaling 1. Shard Keys 2. Query Routing 3. Chunk Distribution 4. Balancer Operations
Topic 7: CRUD Operations	- Data Manipulation 1. Insert Operations 2. Update Operations 3. Read Queries 4. Delete Operations

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MongoDB Certified DBA Associate Exam (Based on MongoDB 4.4) Sample Questions (Q164-Q169):

NEW QUESTION # 164
The oplog (operations log) is a special capped collection that keeps a rolling record of all operations that modify the data stored in your databases. All the replica set members contain a copy of the oplog in the following collection:

A. oplog.rs
B. local.oplog.rs
C. <replicasetid>.oplog.rs
D. <database>..oplog.rs

Answer: B

NEW QUESTION # 165
What does the following aggregate query perform?

A. Fetches the posts with likes between 100 and 200, sets the _id of the first document as null and then increments it 1 every time
B. Fetches the posts with likes between 100 and 200 and sets their _id as null
C. Calculates the number of posts with likes between 100 and 200
D. Groups the posts by number of likes (101, 102, 103.) by adding 1 every time

Answer: C

NEW QUESTION # 166
Consider the following example document:
{
"_id": Objectld("5360c0a0a655a60674680bbe"),
"user"
"login": "irOn"
"description": "Made of steel"
"date": ISODate("2014-04-30T09:16:45.836Z"),
}
>
and index creation command:
db.users.createlndex( { "user.login": 1, "user.date": -1 }, "mylndex" ) When performing the following query:
db.users.find( { "user.login": /Air.*/ },
{ "user":1, "_id":0 > ).sort( { "user.date":1 > )
which of the following statements correctly describe how MongoDB will handle the query? Check all that apply.

A. As an indexed query using "mylndex" because field "user.login" is indexed
B. As an optimized sort query (scanAndOrder = false) using "mylndex" because we are sorting on an indexed field
C. As a covered query using "mylndex" because we are filtering out "_id" and only returning "user.login"
D. MongoDB will need to do a table/collection scan to find matching documents
E. None of the above

Answer: A

NEW QUESTION # 167
The difference between $push and $addToSet is:

A. There is no major difference between them. $addToSet is a deprecated version of $push.
B. $addToSet adds the item to the field only if it does not exist already; while $push pushes the item to the field irrespective of whether it was present or not
C. $addToSet adds the item to the field only if the new item is of the same datatype
D. $addToSet needs the fields to be already present while $push will work even if the field is not present

Answer: B

NEW QUESTION # 168
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: { state: Estate " , city: " $city " },pop: { $sum: 1 > > > ] )
C. db.population.aggregate( [{ $group: { _id: { state: " $state " , city: " $city " },pop: { $pop: 1 } } }] )
D. db.population.aggregate( [{ $group: { _id: { city: " $city " },pop: { $sum: " $pop " } } }] )Multi Document Transaction is not supported by MongoDB

Answer: A

NEW QUESTION # 169
......

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