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| Section | Objectives |
|---|---|
| Data Modeling | - Schema design principles - Relationships in MongoDB - Embedding vs referencing |
| Replication and High Availability | - Replica set architecture - Read/write concerns - Failover and elections |
| MongoDB CRUD Operations | - Insert, update, and delete operations - Querying and filtering documents - Working with documents and BSON types |
| Security | - Role-based access control (RBAC) - Authentication and authorization - Encryption at rest and in transit |
| Indexing and Performance Tuning | - Explain plans and diagnostics - Index types and usage - Query performance optimization |
| Sharding and Scalability | - Shard keys and distribution strategy - Balancing and scaling operations - Sharded cluster architecture |
| Backup, Restore, and Operations | - Restore procedures - Backup strategies and tools - Monitoring and maintenance |
| Aggregation Framework | - Aggregation pipeline stages - Aggregation operators - Data transformation and grouping |
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NEW QUESTION # 95
In order to ensure that you can maintain high availability in the face of server failure, you should implement which of the following?
Answer: C
NEW QUESTION # 96
Which of the following index would be optimum for the query?
Select all valid. db.test.find( { a : 5, c : 2 })
Answer: A,D
NEW QUESTION # 97
Consider the following document from the products collection:
What does the following query using $elemMatch return? db.products.find( { product_code: " 345678 " }, { variations: { $elemMatch: { size:
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