Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

Microsoft DP-420 Exam - Topic 2 Question 58 Discussion

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

Microsoft DP-420 Exam - Topic 2 Question 58 Discussion

Actual exam question for Microsoft's DP-420 exam
Question #: 58
Topic #: 2
[All DP-420 Questions]

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?

Show Suggested Answer Hide Answer
Suggested Answer: B

by Sueann at Feb 08, 2025, 12:23 PM

Limited Time Offer

25%

Off

Get Premium DP-420 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

0/2000 characters
Submit Cancel
Dahlia
9 months ago
Not sure about the date partition key, seems less relevant for telemetry data.
upvoted 0 times
...
Nu
9 months ago
Definitely agree with moving the data to a new container.
upvoted 0 times
...
Catalina
10 months ago
Surprised that decreasing throughput is even an option here!
upvoted 0 times
...
Heidy
10 months ago
I think increasing the throughput won't really solve the RU issue.
upvoted 0 times
...
Lavonda
10 months ago
Moving to a new container with deviceId as the partition key could help.
upvoted 0 times
...
Sabine
10 months ago
I’m leaning towards option C, but I’m a bit uncertain if it’s the best choice since we might still have a lot of data for each device.
upvoted 0 times
...
Sabine
11 months ago
I practiced a similar question where we had to optimize RUs, and I feel like increasing throughput could actually lead to higher costs instead of reducing RUs.
upvoted 0 times
...
Shelba
11 months ago
I think moving to a new container with deviceId as the partition key might help, but I need to double-check how that affects query performance.
upvoted 0 times
...
Vanda
11 months ago
I remember that using the right partition key can really impact performance, but I'm not sure if switching to deviceId or date is better for reducing RUs.
upvoted 0 times
...
Twana
11 months ago
I'm feeling pretty confident about this one. Increasing the offerThroughput value for the container seems like the most straightforward way to reduce the RU consumption.
upvoted 0 times
...
Gilberto
11 months ago
Okay, I think I've got a strategy here. Since the analytics app frequently reads data for a single IoT device, I'll try moving the data to a new container with deviceId as the partition key.
upvoted 0 times
...
Alease
11 months ago
Hmm, I'm a bit confused about the partition key and how that relates to the RU consumption. I'll need to review the Azure Cosmos DB concepts again.
upvoted 0 times
...
Chauncey
11 months ago
This looks like a tricky one. I'll need to carefully read through the details and think about the best way to optimize the RU consumption.
upvoted 0 times
...
Buck
1 year ago
Ah, the joys of Azure Cosmos DB! Where the partition keys are made up and the RUs don't matter. Just toss some more money at it, and all your problems will go away. Truly the cloud equivalent of turning it off and on again.
upvoted 0 times
...
Shad
1 year ago
B is the way to go! Increasing the throughput is the easiest solution, and it will just cost you more money. Why bother with all this partition key nonsense when you can just throw more RUs at the problem?
upvoted 0 times
Leota
1 year ago
B) Increasing the throughput is the easiest solution, and it will just cost you more money.
upvoted 0 times
...
Olen
1 year ago
A) Decrease the offerThroughput value for the container.
upvoted 0 times
...
Kris
1 year ago
B) Increase the offerThroughput value for the container.
upvoted 0 times
...
...
Jeff
1 year ago
Hmm, I'm leaning towards D. Partitioning by date sounds like a more natural fit for time-series data like this. Plus, it might make it easier to manage the data in the long run.
upvoted 0 times
Aracelis
1 year ago
Partitioning by date seems like a logical solution for trend analysis on time-series data. It could improve performance.
upvoted 0 times
...
Tatum
1 year ago
Moving the data to a new container with a partition key of date could definitely help reduce the RUs consumed.
upvoted 0 times
...
Huey
1 year ago
I think D is a good choice too. It can help optimize the queries for trend analysis based on date.
upvoted 0 times
...
...
Edison
1 year ago
I'm not sure about that. Wouldn't partitioning by date be better? That way, the application can easily access data for a specific time period, which could be useful for trend analysis.
upvoted 0 times
Helaine
1 year ago
True, that could make accessing data for a single IoT device more efficient.
upvoted 0 times
...
Leonor
1 year ago
Moving data to a new container with a partition key of deviceId might also be a good option.
upvoted 0 times
...
Jules
1 year ago
But wouldn't decreasing the offerThroughput value help reduce RUs consumed?
upvoted 0 times
...
Talia
1 year ago
Partitioning by date could be a good idea for trend analysis.
upvoted 0 times
...
...
Justa
1 year ago
That's an interesting idea. It could help reduce the RUs consumed by the analytics application.
upvoted 0 times
...
Shonda
1 year ago
I disagree, I believe we should move the data to a new container that has a partition key of deviceId.
upvoted 0 times
...
Ruth
1 year ago
Choosing C seems like the best option here. Partitioning the data by deviceId will allow the analytics application to read data for a single IoT device more efficiently, reducing the RUs consumed.
upvoted 0 times
Ashleigh
1 year ago
Let's go with option C then. It seems like the most efficient solution.
upvoted 0 times
...
Tammy
1 year ago
Moving the data to a new container with deviceId as the partition key sounds like the way to go.
upvoted 0 times
...
Nancey
1 year ago
Agreed, partitioning by deviceId will definitely reduce the RUs consumed.
upvoted 0 times
...
Lashonda
1 year ago
I think option C is the best choice. It will help optimize the analytics application.
upvoted 0 times
...
...
Justa
1 year ago
I think we should decrease the offerThroughput value for the container.
upvoted 0 times
...

Save Cancel