- A
DeviceID
Why wrong: While DeviceID makes per-device queries efficient (point reads), it can create a hot partition if a single device generates a disproportionate amount of writes, because all documents for that device would reside on one partition.
- B
Timestamp (e.g., per minute)
Why wrong: Timestamp as partition key spreads writes evenly, but queries for a specific device across time would need to read every partition (cross-partition query), increasing RU consumption and latency.
- C
Location
Why wrong: Location is unlikely to be unique per device; many devices share a location, leading to hot partitions. Moreover, queries by DeviceID would still require a cross-partition scan.
- D
A synthetic key combining DeviceID and Timestamp (e.g., DeviceID_yyyy-MM-dd-HH)
This distributes writes across partitions because the suffix changes each hour, preventing a single device from overloading one partition. For the query 'get readings for DeviceID in the last hour', the application can compute the exact partition key(s) for the relevant hour(s) and perform efficient point or limited cross-partition queries.
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 company stores IoT temperature readings in Azure Cosmos DB using the NoSQL API. Each document contains: DeviceID, Timestamp, Temperature, Location. Data is ingested at a rate of 10,000 documents per second from thousands of devices. The most common query is 'Get all readings for a specific DeviceID in the last hour.' Which partition key should be chosen to avoid hot partitions while still supporting the query efficiently?
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
A synthetic key combining DeviceID and Timestamp (e.g., DeviceID_yyyy-MM-dd-HH)
Option D is correct because a synthetic key combining DeviceID and Timestamp (e.g., DeviceID_yyyy-MM-dd-HH) ensures that data for a specific device is distributed across multiple physical partitions based on the hour, preventing a single partition from becoming a hot spot. This design still supports the most common query efficiently by allowing Cosmos DB to route the query to only the partitions containing the relevant hour's data, using the partition key in the WHERE clause.
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.
- ✗
DeviceID
Why it's wrong here
While DeviceID makes per-device queries efficient (point reads), it can create a hot partition if a single device generates a disproportionate amount of writes, because all documents for that device would reside on one partition.
- ✗
Timestamp (e.g., per minute)
Why it's wrong here
Timestamp as partition key spreads writes evenly, but queries for a specific device across time would need to read every partition (cross-partition query), increasing RU consumption and latency.
- ✗
Location
Why it's wrong here
Location is unlikely to be unique per device; many devices share a location, leading to hot partitions. Moreover, queries by DeviceID would still require a cross-partition scan.
- ✓
A synthetic key combining DeviceID and Timestamp (e.g., DeviceID_yyyy-MM-dd-HH)
Why this is correct
This distributes writes across partitions because the suffix changes each hour, preventing a single device from overloading one partition. For the query 'get readings for DeviceID in the last hour', the application can compute the exact partition key(s) for the relevant hour(s) and perform efficient point or limited cross-partition queries.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose DeviceID (Option A) because it seems natural for the query, but they overlook the hot partition problem caused by high-ingestion devices, failing to realize that partition key choice must balance query efficiency with write distribution.
Detailed technical explanation
How to think about this question
Under the hood, Azure Cosmos DB uses a hash-based partition strategy where the partition key value is hashed to determine the physical partition. A synthetic key like DeviceID_yyyy-MM-dd-HH ensures that each hour's data for a device hashes to a different partition, distributing write load evenly. In a real-world scenario, if a device sends 10,000 readings per second, using DeviceID alone would cause that partition to handle 10,000 RU/s of write traffic, potentially exceeding the provisioned throughput, while the synthetic key spreads the load across 24 partitions per day.
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
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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: A synthetic key combining DeviceID and Timestamp (e.g., DeviceID_yyyy-MM-dd-HH) — Option D is correct because a synthetic key combining DeviceID and Timestamp (e.g., DeviceID_yyyy-MM-dd-HH) ensures that data for a specific device is distributed across multiple physical partitions based on the hour, preventing a single partition from becoming a hot spot. This design still supports the most common query efficiently by allowing Cosmos DB to route the query to only the partitions containing the relevant hour's data, using the partition key in the WHERE clause.
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.
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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