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Microsoft DP-420 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Design and implement data models35-40%- Design a data partitioning strategy
  • 1. Plan for transactions with partition keys
  • 2. Evaluate throughput and data distribution
  • 3. Evaluate cross-partition query cost
  • 4. Implement synthetic partition keys
  • 5. Choose a partitioning strategy
  • 6. Choose a partition key
- Design and implement a non-relational data model for Azure Cosmos DB for NoSQL
  • 1. Store multiple related entities in the same document
  • 2. Reference between documents
  • 3. Identify partition key, id, and unique keys
  • 4. Denormalize data across documents
  • 5. Identify data and associated access patterns
  • 6. Store multiple entity types in the same container
- Implement data access
  • 1. Implement patch operations
  • 2. Implement optimistic concurrency control
  • 3. Manage transactional batch operations
  • 4. Implement SQL queries with arrays and aggregation
  • 5. Use SDKs for CRUD operations
  • 6. Use consistency and query request options
- Implement client connectivity options
  • 1. Configure client-side threading and logging
  • 2. Handle connection errors
  • 3. Create database connections
  • 4. Use Azure Cosmos DB emulator
  • 5. Choose gateway or direct connectivity mode
  • 6. Implement singleton client
- Implement server-side programming
  • 1. Implement user-defined functions
  • 2. Write and deploy stored procedures
  • 3. Implement triggers
- Plan and implement sizing and scaling
  • 1. Choose between serverless, provisioned, and free tier
  • 2. Evaluate global distribution costs
  • 3. Evaluate throughput and storage requirements
  • 4. Configure throughput
  • 5. Design resource governance and scaling
Topic 2: Maintain an Azure Cosmos DB solution25-30%- Monitor and troubleshoot Azure Cosmos DB solutions
  • 1. Monitor performance and availability
  • 2. Implement backup and recovery strategies
  • 3. Troubleshoot throughput issues
  • 4. Monitor metrics and logs
Topic 3: Optimize an Azure Cosmos DB solution15-20%- Define and implement indexing strategy
  • 1. Choose appropriate index types
  • 2. Choose read-heavy or write-heavy indexing
  • 3. Optimize index performance
  • 4. Implement composite indexes
  • 5. Configure custom indexing policies
- Design and implement change feeds
  • 1. Manage change feed instances
  • 2. Implement aggregation persistence
  • 3. Consume change feeds using SDK
  • 4. Develop Azure Functions triggers
- Optimize query performance
  • 1. Retrieve request unit cost
  • 2. Calculate query cost
  • 3. Implement integrated cache
  • 4. Adjust indexing policies
Topic 4: Integrate an Azure Cosmos DB solution5-10%- Implement solutions across services
  • 1. Integrate Azure Functions and Event Hubs
  • 2. Enforce referential integrity
  • 3. Implement Azure AI Search integration
  • 4. Use Change Feed for denormalization
  • 5. Aggregate and archive data
- Enable analytical workloads
  • 1. Query analytical store from Synapse
  • 2. Configure Azure Cosmos DB Mirroring
  • 3. Write data back from Spark
  • 4. Enable analytical store
Topic 5: Design and implement data distribution5-10%- Design and implement replication strategy
  • 1. Perform manual failovers
  • 2. Choose when to distribute data
  • 3. Evaluate consistency model impacts
  • 4. Define automatic failover policies
  • 5. Choose a consistency model
- Design and implement multi-region writes
  • 1. Choose when to use multi-region writes
  • 2. Implement multi-region writes
  • 3. Implement conflict resolution policies

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Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q112-Q117):

NEW QUESTION # 112
You have the Azure Cosmos DB for NoSQL containers shown in the following table.

You have the items shown in the following table.

When will each item expire? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 113
Hotspot Question
You have an Azure Cosmos DB for NoSQL account that contains a container named container1.
You plan to use container1 as a key-value store that will perform point reads on the item ID and partition key.
You need to define an indexing policy for container1. The solution must meet the following requirements:
- Provide the ability to set DefaultTimeToLive for container1.
- Minimize implementation time.
- Minimize costs.
How should you complete the JSON definition of the indexing policy? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 114
You have an Azure Cosmos DB for NoSQL account that hosts a container named Container1.
The DefaultTimeToLive property of Container1 is set to 500.
Container1 contains an item that has a ttl property of 1000.
The item in Container1 is modified.
When will the item be deleted automatically?

Answer: B

Explanation:
The item will be automatically deleted 1,000 seconds after its last modification time.
How Time to Live (TTL) Evaluation Works
Item-Level Override: In Azure Cosmos DB, when a container has a valid DefaultTimeToLive configured (in this case, 1000 seconds), any individual item can override this value by declaring its own ttl property. Because the item's ttl is explicitly set to 1000, the container's default of 500 is completely ignored for this specific item.
Resetting the Clock: TTL expiration calculations are tied directly to the item's system-generated
_ts (timestamp) property, which records the last modified time. Every time an item is created or updated, Azure Cosmos DB updates _ts to the current Unix epoch time.
Consequently, modifying the item resets its lifespan, and the system will automatically purge it exactly X,000 seconds after that modification occurred.
Reference:
https://learn.microsoft.com/en-us/cosmos-db/time-to-live


NEW QUESTION # 115
You have a container in an Azure Cosmos DB for NoSQL account. The database that has a manual throughput of 30,000 request units per second (RU/s). The current consumption details are shewn in the following chart.
Normalized RU Consumption (%) By PartitionKeyRangeID


Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic. NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 116
You have an Azure Cosmos DB for NoSQL container named Container1.
You run SQL queries against Container1 by using the Azure Cosmos DB .NET SDK.
You need to identify the number of request units consumed by each query.
Which two items can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

Answer: A,B

Explanation:
To identify the number of request units (RUs) consumed by each query using the Azure Cosmos DB .NET SDK (specifically v2 API / DocumentClient syntax implied by your choices), you should use IDocumentQuery and FeedResponse.
ResourceResponse: In the legacy Azure Cosmos DB .NET SDK (v2), query and item operations return a ResourceResponse<T> object. This object contains a RequestCharge property that explicitly yields the number of RUs consumed by the database operation.
IDocumentQuery: When you perform asynchronous pagination or streaming of SQL query results in the v2 .NET SDK, the IDocumentQuery<T> interface is implemented. This interface exposes properties and response fields that catch execution metrics-including total request charges-as you iterate through your data feed.
Reference:
https://learn.microsoft.com/sv-se/azure/cosmos-db/find-request-unit-charge


NEW QUESTION # 117
......

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