GET REAL MICROSOFT DP-420 EXAM QUESTIONS BY [PASSREVIEW]

Get Real Microsoft DP-420 Exam Questions By [PassReview]

Get Real Microsoft DP-420 Exam Questions By [PassReview]

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Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q76-Q81):

NEW QUESTION # 76
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 # 77
You plan to implement con-iot1 and con-iot2.
You need to configure the default Time to Live setting for each container. The solution must meet the loT telemetry requirements.
What should you configure? To answer, select the appropriate options in the answer NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 78
You have a database named db1 in an Azure Cosmos DB for NoSQL
You are designing an application that will use dbl.
In db1, you are creating a new container named coll1 that will store in coll1.
The following is a sample of a document that will be stored in coll1.

The application will have the following characteristics:
* New orders will be created frequently by different customers.
* Customers will often view their past order history.
You need to select the partition key value for coll1 to support the application. The solution must minimize costs.
To what should you set the partition key?

  • A. orderDate
  • B. customerId
  • C. id
  • D. orderId

Answer: A

Explanation:
Based on the characteristics of the application and the provided document structure, the most suitable partition key value for coll1 in the given scenario would be the customerId, Option B.
The application frequently creates new orders by different customers and customers often view their past order history. Using customerId as the partition key would ensure that all orders associated with a particular customer are stored in the same partition. This enables efficient querying of past order history for a specific customer and reduces cross-partition queries, resulting in lower costs and improved performance.
a partition key is a JSON property (or path) within your documents that is used by Azure Cosmos DB to distribute data among multiple partitions3. A partition key should have a high cardinality, which means it should have many distinct values, such as hundreds or thousands1. A partition key should also align with the most common query patterns of your application, so that you can efficiently retrieve data by using the partition key value1.
Based on these criteria, one possible partition key that you could use for coll1 is B. customerId.
This partition key has the following advantages:
* It has a high cardinality, as each customer will have a unique ID3.
* It aligns with the query patterns of the application, as customers will often view their past order history3.
* It minimizes costs, as it reduces the number of cross-partition queries and optimizes the storage and throughput utilization1.
This partition key also has some limitations, such as:
* It may not be optimal for scenarios where orders need to be queried independently from customers or aggregated by date or other criteria3.
* It may result in hot partitions or throttling if some customers create orders more frequently than others or have more data than others1.
* It may not support transactions across multiple customers, as transactions are scoped to a single logical partition2.
Depending on your specific use case and requirements, you may need to adjust this partition key or choose a different one. For example, you could use a synthetic partition key that concatenates multiple properties of an item2, or you could use a partition key with a random or pre-calculated suffix to distribute the workload more evenly2.


NEW QUESTION # 79
You maintain a relational database for a book publisher. The database contains the following tables.

The most common query lists the books for a given authorId.
You need to develop a non-relational data model for Azure Cosmos DB Core (SQL) API that will replace the relational database. The solution must minimize latency and read operation costs.
What should you include in the solution?

  • A. Create a container for Author and a container for Book. In each Author document and Book document embed the data from Bookauthorlnk.
  • B. Create a container for Author and a container for Book. In each Author document, embed bookId for each book by the author. In each Book document embed authorId of each author.
  • C. Create a container that contains a document for each Author and a document for each Book. In each Book document, embed authorId.
  • D. Create Author, Book, and Bookauthorlnk documents in the same container.

Answer: B

Explanation:
Store multiple entity types in the same container.


NEW QUESTION # 80
You have an Azure subscription that contains an Azure Cosmos DB for NoSQL database named DB1. The shared throughput provisioned for DB1 is 10,000 DTU/s. DB1 contains the containers shown in the following table.

You need to modify the throughput for the containers. The solution must meet the following requirements:
* The maximum throughput for Container1 must be 4,000 DTU/s.
* The throughput for Contained must be shared across the containers.
* Administrative effort must be minimized.
What should you do? To answer, select the appropriate options in the answer are a. NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 81
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