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Die Microsoft DP-420-Prüfung, auch bekannt als Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB, ist eine fortgeschrittene Zertifizierungsprüfung, die Ihre Kenntnisse im Entwurf und der Implementierung von Cloud-nativen Anwendungen mit Azure Cosmos DB testet. Diese Prüfung ist für Fachleute gedacht, die ihre Expertise in der Entwicklung cloud-basierter Anwendungen mit Azure Cosmos DB validieren möchten.
89. Frage
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?
Antwort: C
Begründung:
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 ID
* 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 criteria
* It may result in hot partitions or throttling if some customers create orders more frequently than others or have more data than others
* 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.
90. Frage
The following is a sample of a document in orders.
The orders container uses customerId as the partition key.
You need to provide a report of the total items ordered per month by item type. The solution must meet the following requirements:
- Ensure that the report can run as quickly as possible.
- Minimize the consumption of request units (RUs).
What should you do?
Antwort: B
91. Frage
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure Cosmos DB Core (SQL) API account named account 1 that uses autoscale throughput.
You need to run an Azure function when the normalized request units per second for a container in account1 exceeds a specific value.
Solution: You configure the function to have an Azure CosmosDB trigger.
Does this meet the goal?
Antwort: B
Begründung:
Instead configure an Azure Monitor alert to trigger the function.
You can set up alerts from the Azure Cosmos DB pane or the Azure Monitor service in the Azure portal.
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/create-alerts
92. Frage
You have an Azure Cosmos DB container named container! that has a provisioned throughput and two physical partitions. You monitor the following metrics for container1
* Normalized RU consumption
* The percentage of requests that have an HTTP status code of 429
You need to confirm that container1 is configured to maximize resource utilization.
What are the optimal values for each metric? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Antwort:
Begründung:
Explanation:
93. Frage
You have an Azure Cosmos DB for NoSQL account named account1.
You have an app named App1 that connects to account1 and uses strong consistency for all requests.
You implement the Azure Cosmos DB integrated cache for account1.
You need to ensure that App1 uses the integrated cache.
What should you do?
Antwort: C
Begründung:
To use the Azure Cosmos DB integrated cache, you must modify your application configuration to route requests through the Dedicated Gateway and, crucially, relax the consistency level for those specific requests.
The integrated cache does not support Strong consistency. If a request uses Strong consistency, it will automatically bypass the cache and go directly to the backend partitions.
Relax Request Consistency
Since your app currently uses Strong consistency, you must override this at the request level for any read (point read or query) that you want to be cached.
The cache only supports Session or Eventual consistency.
Session consistency is recommended to maintain the "read-your-own-writes" guarantee while still utilizing the cache.
Reference:
https://learn.microsoft.com/en-us/azure/cosmos-db/integrated-cache
94. Frage
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