- A
TripID
Why wrong: TripID is unique per trip, so using it as partition key would result in each trip being in its own partition. Queries filtering by DriverID would become cross-partition queries, consuming more RU and having higher latency.
- B
DriverID
DriverID aligns with the most common query pattern. All trips for a given driver are stored together, allowing single-partition queries. This minimizes RU consumption if the number of trips per driver is within the 20 GB logical partition limit.
- C
TripDate
Why wrong: TripDate could cause hot partitions if many trips occur on the same day, leading to uneven data distribution. Also, queries for a specific driver would still need to scan multiple date partitions.
- D
RiderID
Why wrong: RiderID is not commonly used in the primary query pattern, so it would cause cross-partition queries for driver-based lookups, increasing RU cost.
DP-900 Practice Question: Describe considerations for working with non-relational data on Azure
This DP-900 practice question tests your understanding of describe considerations for working with non-relational data on azure. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A ride-sharing application uses Azure Cosmos DB for trip data. Each trip record contains TripID (unique), DriverID, RiderID, TripDate, and other details. The most common query retrieves all trips for a specific driver within a given date range. Which partition key should be chosen to minimize Request Unit (RU) consumption and ensure even data distribution?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
DriverID
DriverID is the optimal partition key because the most common query filters on DriverID and a date range. Partitioning by DriverID ensures that all trips for a specific driver are stored in the same physical partition, making the query a single-partition operation that consumes minimal Request Units (RUs). It also provides even data distribution across partitions because each driver generates a roughly similar number of trips, avoiding hot spots.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
TripID
Why it's wrong here
TripID is unique per trip, so using it as partition key would result in each trip being in its own partition. Queries filtering by DriverID would become cross-partition queries, consuming more RU and having higher latency.
- ✓
DriverID
Why this is correct
DriverID aligns with the most common query pattern. All trips for a given driver are stored together, allowing single-partition queries. This minimizes RU consumption if the number of trips per driver is within the 20 GB logical partition limit.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
TripDate
Why it's wrong here
TripDate could cause hot partitions if many trips occur on the same day, leading to uneven data distribution. Also, queries for a specific driver would still need to scan multiple date partitions.
- ✗
RiderID
Why it's wrong here
RiderID is not commonly used in the primary query pattern, so it would cause cross-partition queries for driver-based lookups, increasing RU cost.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often pick TripDate because it seems logical for date-range queries, but they overlook that the primary filter is DriverID, and partitioning by TripDate would cause cross-partition queries and potential hot spots on high-traffic dates.
Detailed technical explanation
How to think about this question
In Azure Cosmos DB, a single-partition query (where the partition key is in the filter) costs at minimum ~10 RUs for a point read, while a cross-partition query can cost 10–100+ RUs depending on the number of physical partitions. Choosing DriverID ensures that the query engine routes the request directly to the partition containing that driver's data, leveraging the index within that partition for the date range filter. In real-world scenarios, if a driver has millions of trips, the partition might grow large, but Cosmos DB automatically splits logical partitions into physical partitions when they exceed 20 GB, maintaining performance.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this DP-900 question test?
Describe considerations for working with non-relational data on Azure — This question tests Describe considerations for working with non-relational data on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: DriverID — DriverID is the optimal partition key because the most common query filters on DriverID and a date range. Partitioning by DriverID ensures that all trips for a specific driver are stored in the same physical partition, making the query a single-partition operation that consumes minimal Request Units (RUs). It also provides even data distribution across partitions because each driver generates a roughly similar number of trips, avoiding hot spots.
What should I do if I get this DP-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
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