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Microsoft DP-420 Exam Syllabus Topics:

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

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Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q118-Q123):

NEW QUESTION # 118
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 # 119
You have a multi-region Azure Cosmos DB account named account1 that has a default consistency level of strong.
You have an app named App1 that is configured to request a consistency level of session.
How will the read and write operations of App1 be handled? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 120
You have an Azure Cosmos DB for NoSQL account.
The change feed is enabled on a container named invoice.
You create an Azure function that has a trigger on the change feed.
What is received by the Azure function?

Answer: D

Explanation:
Explanation
According to the Azure Cosmos DB documentation12, the change feed is a persistent record of changes to a container in the order they occur. The change feed outputs the sorted list of documents that were changed in the order in which they were modified.
The Azure function that has a trigger on the change feed receives all the properties of the updated items2. The change feed does not include the original items or only the changed properties. The change feed also includes some system-defined properties such as _ts (the last modified timestamp) and _lsn (the logical sequence number)3.
Therefore, the correct answer is: A. all the properties of the updated items


NEW QUESTION # 121
The settings for a container in an Azure Cosmos DB Core (SQL) API account are configured as shown in the following exhibit.

Which statement describes the configuration of the container?

Answer: B

Explanation:
When DefaultTimeToLive is -1 then your Time to Live setting is On (No default) Time to Live on a container, if present and the value is set to "-1", it is equal to infinity, and items don't expire by default.
Time to Live on an item:
This Property is applicable only if DefaultTimeToLive is present and it is not set to null for the parent container.
If present, it overrides the DefaultTimeToLive value of the parent container.


NEW QUESTION # 122
Which of the following function in Spark SQL separates the array's elements into multiple rows with positions and utilizes the column names 'pos' for position and 'col' for elements of the array?

Answer: A

Explanation:
posexplode() is a function in Spark SQL that separates the array's elements into multiple rows with positions and utilizes the column names pos for position and col for elements of the array.
https://docs.microsoft.com/en-us/learn/modules/query-azure-cosmos-db-with-apache-spark-for-azure-synapse-analytics/5-perform-complex-queries


NEW QUESTION # 123
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