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DP-420 Valid Test Papers - Exam DP-420 Format

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The DP-420 Certification Exam covers a range of topics related to designing and implementing cloud-native applications using Azure Cosmos DB, including data modeling, partitioning and scaling, indexing and querying, and performance tuning. Successful candidates will have demonstrated their ability to use Azure Cosmos DB to build scalable and highly available cloud-native applications that can handle large volumes of data and provide a seamless user experience. By earning this certification, professionals can showcase their skills and knowledge to potential employers and advance their careers in the field of cloud-native application development.

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Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q73-Q78):

NEW QUESTION # 73
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. Create a private endpoint connection to the account.
B. In an Apache Spark pool in Azure Synapse, create a table that uses cosmos.oltp as the data source.
C. In an Azure Synapse Analytics serverless SQL pool, create a view that uses OPENROWSET and the CosmosDB provider.
D. In an Apache Spark pool in Azure Synapse, create a table that uses cosmos.olap as the data source.
E. Enable Azure Synapse Link for the account and Analytical store on the container.

Answer: D,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 # 74
You have an Apache Spark pool in Azure Synapse Analytics that runs the following Python code in a notebook.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation
New and updated orders will be added to contoso-erp.orders: Yes
The code performs bulk data ingestion from contoso-app: No
Both contoso-app and contoso-erp have Analytics store enabled: Yes
The code uses the spark.readStream method to read data from a container named orders in a database named contoso-app. The data is then filtered by a condition and written to another container named orders in a database named contoso-erp using the spark.writeStream method. The write mode is set to "append", which means that new and updated orders will be added to the destination container1.
The code does not perform bulk data ingestion from contoso-app, but rather stream processing. Bulk data ingestion is a process of loading large amounts of data into a data store in batches. Stream processing is a process of continuously processing data as it arrives in real-time2.
Both contoso-app and contoso-erp have Analytics store enabled, because they are both accessed by Spark pools using the spark.cosmos.oltp method. This method requires that the containers have Analytics store enabled, which is a feature that allows Spark pools to query data stored in Azure Cosmos DB containers using SQL APIs3.

NEW QUESTION # 75
You have the indexing policy shown in the following exhibit.

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:

NEW QUESTION # 76
You are developing an application that will connect to an Azure Cosmos DB for NoSQL account. The account has a single readme region and one agonal read region. The regions are configured for automatic failover.
The account has the following connect strings. (Line numbers are included for reference only.)

For each of the following statements, select Yes if the statement is true. otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation
If the primary write region fails, applications that write to the database must use a different connection string to continue to use the service. = NOYou do not need to use a different connection string to continue to use the service if the primary write region fails. This is because Azure Cosmos DB supports automatic failover, which means that it will automatically switch the primary write region to another region in case of a regional outage2
. The application does not need to change the connection string or specify the failover priority3. The connection string contains a list of all the regions associated with your account, and Azure Cosmos DB will route the requests to the appropriate region based on the availability and latency1.
The primary Read-Only SQL Connection String and the Secondary Read-Only SQL Connection String will connect to different regions from an application running in the East US Azure region = YesThe primary read-only SQL connection string and the secondary read-only SQL connection string will connect to different regions from an application running in the East US Azure region. This is because the primary read-only SQL connection string contains the endpoint for the East US region, which is the same as the primary write region.
The secondary read-only SQL connection string contains the endpoint for the West US region, which is the additional read region. Therefore, if an application running in the East US Azure region uses these connection strings, it will connect to different regions depending on which one it chooses.
Applications can choose from which region by setting the PreferredLocations property within their connection properties = Yes Applications can choose from which region by setting the PreferredLocations property within their connection properties. This property allows you to specify a list of regions that you prefer to read from based on their proximity to your application2. Azure Cosmos DB will route the requests to the appropriate region based on the availability and latency1. You can also set the ApplicationRegion property to the region where your application is deployed, and Azure Cosmos DB will automatically populate the PreferredLocations property based on the geo-proximity from that location

NEW QUESTION # 77
You need to implement a solution to meet the product catalog requirements.
What should you do to implement the conflict resolution policy.

A. Remove frequently changed field from the index policy of the con-product container.
B. Disable indexing on all fields in the index policy of the con-product container.
C. Set the default consistency level for account1 to eventual.
D. Create a new container and migrate the product catalog data to the new container.

Answer: D

Explanation:
Topic 1, Litware, inc
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Overview
Litware, Inc. is a United States-based grocery retailer. Litware has a main office and a primary datacenter in Seattle. The company has 50 retail stores across the United States and an emerging online presence. Each store connects directly to the internet.
Existing environment. Cloud and Data Service Environments.
Litware has an Azure subscription that contains the resources shown in the following table.

Each container in productdb is configured for manual throughput.
The con-product container stores the company's product catalog data. Each document in con-product includes a con-productvendor value. Most queries targeting the data in con-product are in the following format.
SELECT * FROM con-product p WHERE p.con-productVendor - 'name'
Most queries targeting the data in the con-productVendor container are in the following format SELECT * FROM con-productVendor pv ORDER BY pv.creditRating, pv.yearFounded Existing environment. Current Problems.
Litware identifies the following issues:
Updates to product categories in the con-productVendor container do not propagate automatically to documents in the con-product container.
Application updates in con-product frequently cause HTTP status code 429 "Too many requests". You discover that the 429 status code relates to excessive request unit (RU) consumption during the updates.
Requirements. Planned Changes
Litware plans to implement a new Azure Cosmos DB Core (SQL) API account named account2 that will contain a database named iotdb. The iotdb database will contain two containers named con-iot1 and con-iot2.
Litware plans to make the following changes:
Store the telemetry data in account2.
Configure account1 to support multiple read-write regions.
Implement referential integrity for the con-product container.
Use Azure Functions to send notifications about product updates to different recipients.
Develop an app named App1 that will run from all locations and query the data in account1.
Develop an app named App2 that will run from the retail stores and query the data in account2. App2 must be limited to a single DNS endpoint when accessing account2.
Requirements. Business Requirements
Litware identifies the following business requirements:
Whenever there are multiple solutions for a requirement, select the solution that provides the best performance, as long as there are no additional costs associated.
Ensure that Azure Cosmos DB costs for IoT-related processing are predictable.
Minimize the number of firewall changes in the retail stores.
Requirements. Product Catalog Requirements
Litware identifies the following requirements for the product catalog:
Implement a custom conflict resolution policy for the product catalog data.
Minimize the frequency of errors during updates of the con-product container.
Once multi-region writes are configured, maximize the performance of App1 queries against the data in account1.
Trigger the execution of two Azure functions following every update to any document in the con-product container.

NEW QUESTION # 78
......

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