C100DBA덤프내용 & C100DBA완벽한덤프공부자료

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MongoDB C100DBA Exam Syllabus Topics:

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

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최신 MongoDB Certified DBA Associate C100DBA 무료샘플문제 (Q154-Q159):

질문 # 154
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: 4
B. Document with _id: 3
C. Document with _id: 1
D. Document with _id: 2

정답：B

설명：
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.

질문 # 155
A collection and a document in MongoDB is equivalent to which of the SQL concepts respectively?

A. Table and Row
B. Column and Row
C. Database and Table
D. Table and Column

정답：A

질문 # 156
Which is the correct order (lowest to highest) in which MongoDB compares the BSON types?

A. Number, Null, String and Object
B. Null, Number, String and Object
C. Null, Number, Object and String
D. String, Null, Number and Object

정답：B

질문 # 157
Which of the following is a valid Replica Set configuration if you want:
1-Have 3 copies of everything
2- That RS3 is never primary
2- That RSI and RS2 can be primary?
You had to see the different configurations, RS3 could be hidden or priority 0 (But not a referee because we need
3 replicas), while RSI and RS2 could NOT have priority 0 or be hidden or anything like that In a 4-member RS RSO , RSI, RS2 and RS3 + Referee, RSO (primary) falls after some write operations that have replicated RSI and RS2 (but NOT RS3), who can get up as the new primary?
The configuration comes and in it we see that RS2 has a hidden: true (or a priority: 0, (I don't remember)

A. ORS1
B. RSO
C. ORS3
D. ORS2
E. O arbiter

정답：A

질문 # 158
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( [{ $group: { _id: { state: "$state", city; "$city" },pop: { $sum: 1 > > >] )
B. db.population.aggregate( [{ $group: { _id: { state: Estate", city: n$city" },pop: { $sum: "$pop" } } }] )
C. db.population.aggregate( [{ $group: { _id: { state: Estate", city: "$city" },pop: { $pop: 1 } } }] )
D. db.population.aggregate( [{ $group: { _id: { city: "$city" },pop: { $sum: "$pop" } } }] )Multi Document Transaction is not supported by MongoDB

정답：B

질문 # 159
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