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Download Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Exam Dumps

NEW QUESTION 42
You have a container in an Azure Cosmos DB Core (SQL) API account. The container stores telemetry data from IoT devices. The container uses telemetryId as the partition key and has a throughput of 1,000 request units per second (RU/s). Approximately 5,000 IoT devices submit data every five minutes by using the same telemetryId value.
You have an application that performs analytics on the data and frequently reads telemetry data for a single IoT device to perform trend analysis.
The following is a sample of a document in the container.

You need to reduce the amount of request units (RUs) consumed by the analytics application.
What should you do?

  • A. Increase the offerThroughput value for the container.
  • B. Decrease the offerThroughput value for the container.
  • C. Move the data to a new container that uses a partition key of date.
  • D. Move the data to a new container that has a partition key of deviceId.

Answer: D

Explanation:
The partition key is what will determine how data is routed in the various partitions by Cosmos DB and needs to make sense in the context of your specific scenario. The IoT Device ID is generally the "natural" partition key for IoT applications.

 

NEW QUESTION 43
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 Data Factory pipeline that uses Azure Cosmos DB Core (SQL) API as the input and Azure Blob Storage as the output.
Does this meet the goal?

  • A. No
  • B. Yes

Answer: A

Explanation:
Instead create an Azure function that uses Azure Cosmos DB Core (SQL) API change feed as a trigger and Azure event hub as the output.
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:

 

NEW QUESTION 44
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 an Azure Monitor alert to trigger the function.
Does this meet the goal?

  • A. Yes
  • B. No

Answer: A

Explanation:
You can set up alerts from the Azure Cosmos DB pane or the Azure Monitor service in the Azure portal.
Note: Alerts are used to set up recurring tests to monitor the availability and responsiveness of your Azure Cosmos DB resources. Alerts can send you a notification in the form of an email, or execute an Azure Function when one of your metrics reaches the threshold or if a specific event is logged in the activity log.

 

NEW QUESTION 45
You are designing an Azure Cosmos DB Core (SQL) API solution to store data from IoT devices. Writes from the devices will be occur every second.
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?

  • A. Create a new synthetic key that contains deviceId and deviceManufacturer.
  • B. Create a new synthetic key that contains deviceId and sensor1Value.
  • C. Create a new synthetic key that contains deviceId and a random number.
  • D. Use timestamp as the partition key.

Answer: C

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.

 

NEW QUESTION 46
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