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Microsoft DP-420 Exam Syllabus Topics:

Section	Weight	Objectives
Design and implement data models	35-40%	- Implement server-side programming 1. Write and deploy stored procedures 2. Implement triggers 3. Implement user-defined functions - Implement data access 1. Manage transactional batch operations 2. Use consistency and query request options 3. Implement optimistic concurrency control 4. Implement patch operations 5. Use SDKs for CRUD operations 6. Implement SQL queries with arrays and aggregation - Plan and implement sizing and scaling 1. Configure throughput 2. Design resource governance and scaling 3. Evaluate throughput and storage requirements 4. Evaluate global distribution costs 5. Choose between serverless, provisioned, and free tier - Implement client connectivity options 1. Use Azure Cosmos DB emulator 2. Configure client-side threading and logging 3. Implement singleton client 4. Handle connection errors 5. Create database connections 6. Choose gateway or direct connectivity mode - Design a data partitioning strategy 1. Choose a partition key 2. Evaluate throughput and data distribution 3. Plan for transactions with partition keys 4. Evaluate cross-partition query cost 5. Implement synthetic partition keys 6. Choose a partitioning strategy - Design and implement a non-relational data model for Azure Cosmos DB for NoSQL 1. Store multiple entity types in the same container 2. Identify partition key, id, and unique keys 3. Identify data and associated access patterns 4. Reference between documents 5. Store multiple related entities in the same document 6. Denormalize data across documents
Maintain an Azure Cosmos DB solution	25-30%	- Monitor and troubleshoot Azure Cosmos DB solutions 1. Monitor metrics and logs 2. Monitor performance and availability 3. Troubleshoot throughput issues 4. Implement backup and recovery strategies
Design and implement data distribution	5-10%	- Design and implement multi-region writes 1. Choose when to use multi-region writes 2. Implement conflict resolution policies 3. Implement multi-region writes - Design and implement replication strategy 1. Choose when to distribute data 2. Evaluate consistency model impacts 3. Define automatic failover policies 4. Choose a consistency model 5. Perform manual failovers
Optimize an Azure Cosmos DB solution	15-20%	- Design and implement change feeds 1. Manage change feed instances 2. Develop Azure Functions triggers 3. Consume change feeds using SDK 4. Implement aggregation persistence - Define and implement indexing strategy 1. Optimize index performance 2. Configure custom indexing policies 3. Choose read-heavy or write-heavy indexing 4. Implement composite indexes 5. Choose appropriate index types - Optimize query performance 1. Retrieve request unit cost 2. Implement integrated cache 3. Calculate query cost 4. Adjust indexing policies
Integrate an Azure Cosmos DB solution	5-10%	- Implement solutions across services 1. Integrate Azure Functions and Event Hubs 2. Enforce referential integrity 3. Use Change Feed for denormalization 4. Aggregate and archive data 5. Implement Azure AI Search integration - Enable analytical workloads 1. Configure Azure Cosmos DB Mirroring 2. Query analytical store from Synapse 3. Write data back from Spark 4. Enable analytical store

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Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q114-Q119):

NEW QUESTION # 114
You have a container in an Azure Cosmos DB Core (SQL) API account.
You need to use the Azure Cosmos DB SDK to replace a document by using optimistic concurrency.
What should you include in the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: ConsistencyLevel
The ItemRequestOptions Class ConsistencyLevel property gets or sets the consistency level required for the request in the Azure Cosmos DB service.
Azure Cosmos DB offers 5 different consistency levels. Strong, Bounded Staleness, Session, Consistent Prefix and Eventual - in order of strongest to weakest consistency.
Box 2: _etag
The ItemRequestOptions class helped us implement optimistic concurrency by specifying that we wanted the SDK to use the If-Match header to allow the server to decide whether a resource should be updated. The If-Match value is the ETag value to be checked against. If the ETag value matches the server ETag value, the resource is updated.
Reference:
https://docs.microsoft.com/en-us/dotnet/api/microsoft.azure.cosmos.itemrequestoptions
https://cosmosdb.github.io/labs/dotnet/labs/10-concurrency-control.html

NEW QUESTION # 115
Hotspot Question
You have an Azure Cosmos DB for NoSQL account.
You plan to create a container named container1. The container1 container will store items that include two properties named name and age.
The most commonly executed queries will query container1 for a specific name. The following is a sample of the query.

You need to define an opt-in indexing policy for container1. The solution must meet the following requirements:
- Minimize the number of request units consumed by the queries.
- Ensure that the _etag property is excluded from indexing.
How should you define 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 # 116
You have an Azure Cosmos DB Core (SQL) API account that is used by 10 web apps.
You need to analyze the data stored in the account by using Apache Spark to create machine learning models.
The solution must NOT affect the performance of the web apps.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. In an Apache Spark pool in Azure Synapse, create a table that uses cosmos.olap as the data source.
B. Create a private endpoint connection to the account.
C. In an Apache Spark pool in Azure Synapse, create a table that uses cosmos.oltp as the data source.
D. In an Azure Synapse Analytics serverless SQL pool, create a view that uses OPENROWSET and the CosmosDB provider.
E. Enable Azure Synapse Link for the account and Analytical store on the container.

Answer: A,E

Explanation:
Reference:
https://github.com/microsoft/MCW-Cosmos-DB-Real-Time-Advanced-Analytics/blob/main/Hands-on%20lab
/HOL%20step-by%20step%20-%20Cosmos%20DB%20real-time%20advanced%20analytics.md

NEW QUESTION # 117
You need to implement a trigger in Azure Cosmos DB Core (SQL) API that will run before an item is inserted into a container.
Which two actions should you perform to ensure that the trigger runs? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. For each create request, set the trigger name in RequestOptions.
B. For each create request, set the consistency level to session in RequestOptions.
C. Register the trigger as a pre-trigger.
D. For each create request, set the access condition in RequestOptions.
E. Append pre to the name of the JavaScript function trigger.

Answer: C

Explanation:
C: When triggers are registered, you can specify the operations that it can run with.
F: When executing, pre-triggers are passed in the RequestOptions object by specifying PreTriggerInclude and then passing the name of the trigger in a List object.

NEW QUESTION # 118
Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
You have an Azure Cosmos DB for NoSQL database. The database hosts a container named families that stores data in the following format.

You need to return the following data:
- The ID of the family
- The family names of the children
- The name of any pets if the pet is a cat
Solution: You run the following query.

Does this meet the goal?

A. No
B. Yes

Answer: A

Explanation:
CROSS APPLY should not be used.
Correct:
* You run the following query.

The following Azure Cosmos DB NoSQL query fulfills the requirements by unnesting child array items and filtering the pet array:
To retrieve the family ID, the children's family names, and the rabbit's name, you can use the query below.
SELECT f.id, c.familyName AS FamilyName, p.givenName AS petName
FROM families f
JOIN f.children c
JOIN (SELECT VALUE p FROM p IN c.pets WHERE p.type = 'cat') AS p
1. Flatten the Children Array
To access individual properties within the children sub-array, use a JOIN statement. In Azure Cosmos DB, a JOIN performs an inner product between the document root (f) and the array (f.children). This filters out any family documents that contain no children.
2. Isolate Cat Pets
To inspect the properties of the pets array embedded inside each child, apply a secondary JOIN on c.pets. The WHERE clause then filters these projected items to only include cases where the property $p.type$ matches the string "cat".
3. Project Specific Attributes
The SELECT clause restricts the final JSON output schema to contain exactly three custom- aliased properties:
familyId: Extracted from the root document
IDchildFamilyName: Extracted from the current child item
iterationpetName: Extracted from the matching pet item iteration
Incorrect:
* You run the following query.

Use two JOINS and one subquery, not three JOINS and a subquery.
* You run the following query.

CROSS APPLY should not be used.
Reference:
https://learn.microsoft.com/en-us/cosmos-db/query/subquery

NEW QUESTION # 119
......

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