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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB |
| Exam Number: | DP-420 |
| Real Exam Qty: | 40-60 |
| Passing Score: | 700 |
| Related Certifications: | Microsoft Certified: Azure Developer Associate Microsoft Certified: Azure Solutions Architect Expert |
| Exam Price: | $165 USD |
| Certificate Validity Period: | 12 months |
| Exam Duration: | 120 minutes |
| Exam Format: | Multiple-response, Drag-and-drop, Case studies, Multiple-choice, Practical lab scenarios |
| Available Languages: | Chinese (Simplified), English, Japanese |
| Recommended Training: | Course DP-420T00: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB |
| Exam Registration: | Pearson VUE Microsoft Learn |
| Sample Questions: | Microsoft DP-420 Sample Questions |
| Exam Way: | Online proctored or onsite test center |
| Pre Condition: | No mandatory prerequisites; recommended experience: developing Azure applications, working with NoSQL databases, proficiency in C#/Java/JavaScript/Python, familiarity with Azure management |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-420 |
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The Microsoft DP-420 Exam covers various topics related to Azure Cosmos DB, such as partitioning and scaling, data modeling, indexing, querying, and performance tuning. Additionally, candidates will be tested on their knowledge of cloud-native application design principles, including microservices, containerization, and serverless computing.
NEW QUESTION # 249
Hotspot Question
You have an Azure Cosmos DB Core (SQL) API account named storage1 that uses provisioned throughput capacity mode.
The storage1 account contains the databases shown in the following table.
The databases contain the containers shown in the following table.
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:
Box 1: No
Four containers with 1000 RU/s each.
Box 2: No
Max 8000 RU/s for db2. 8 containers, so 1000 RU/s for each container.
Box 3: Yes
Max 8000 RU/s for db2. 8 containers, so 1000 RU/s for each container. Can very well add an additional container.
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/plan-manage-costs
https://azure.microsoft.com/en-us/pricing/details/cosmos-db/
NEW QUESTION # 250
You are designing an Azure Cosmos DB for NoSQL solution to store data from IoT devices.
Writes from the devices will be occur every second. Data will be retained indefinitely.
The following is a sample of the data.
You need to select a partition key that meets the following requirements for writes:
- Minimizes the partition skew
- Avoids capacity limits
- Avoids hot partitions
What should you do?
Answer: D
Explanation:
Use a partition key with a random suffix. Distribute the workload more evenly is to append a random number at the end of the partition key value. When you distribute items in this way, you can perform parallel write operations across partitions.
Incorrect Answers:
A: You will also not like to partition the data on "DateTime", because this will create a hot partition. Imagine you have partitioned the data on time, then for a given minute, all the calls will hit one partition. If you need to retrieve the data for a customer, then it will be a fan-out query because data may be distributed on all the partitions.
B: Senser1Value has only two values.
C: All the devices could have the same manufacturer.
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/sql/synthetic-partition-keys
NEW QUESTION # 251
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 # 252
You have an Azure Cosmos DB database that contains a container named container 1. The container1 container is configured with a maximum of 20,000 RU/s and currently contains 240 GB of data.
You need to estimate the costs of container1 based on the current usage.
How many RU/s will be charged?
Answer: A
NEW QUESTION # 253
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 a container named container1 in an Azure Cosmos DB Core (SQL) API account. You need to make the contents of container1 available as reference data for an Azure Stream Analytics job.
Solution: You create an Azure function that uses Azure Cosmos DB Core (SQL) API change feed as a trigger and Azure event hub as the output.
Does this meet the goal?
Answer: A
Explanation:
The Azure Cosmos DB change feed is a mechanism to get a continuous and incremental feed of records from an Azure Cosmos container as those records are being created or modified.
Change feed support works by listening to container for any changes. It then outputs the sorted list of documents that were changed in the order in which they were modified. The following diagram represents the data flow and components involved in the solution:
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/sql/changefeed-ecommerce- solution
NEW QUESTION # 254
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