Question 551 of 982

Describe considerations for working with non-relational data on Azure →mediumMultiple ChoiceObjective-mapped

Quick Answer

The answer is that the query does not use the partition key, which forces a cross-partition scan. Without specifying deviceId in the filter, Azure Cosmos DB cannot route the request to a single physical partition; instead, it must fan out the query to every partition, scanning all documents across the container. This cross-partition query consumes significantly more request units (RUs) and takes longer because each partition is queried sequentially or in parallel, and results are merged server-side. On the DP-900 exam, this scenario tests your understanding of how partition key selection directly impacts query performance and cost—a common trap is assuming all queries run efficiently regardless of the filter. Remember the memory tip: “No key, full sweep”—if your WHERE clause omits the partition key, expect a slow, expensive cross-partition scan.

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. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 smart building company stores IoT sensor data in Azure Cosmos DB using the NoSQL API. Each document contains fields: deviceId (partition key), timestamp, temperature, and humidity. The most common query is to retrieve all readings for a specific device within a time range, which runs efficiently. However, the analytics team occasionally runs a query to find all devices that reported a temperature above 50 degrees Celsius in the last hour, without specifying deviceId. This query is very slow and consumes a high number of request units (RUs). What is the most likely reason for the slow performance and high RU consumption?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.

Question 1mediummultiple choice

Full question →

A
The query does not use the partition key, causing a cross-partition scan.
When a query does not include the partition key, Cosmos DB must execute the query across all partitions, which increases latency and RU consumption. This is the most likely cause.
B
The query is not using an index on the temperature field.
Why wrong: While indexes are important, Cosmos DB automatically indexes all fields by default. The absence of a partition key in the filter is the primary issue because it forces a full scan across partitions.
C
The time range filter is too large, causing a full table scan.
Why wrong: A large time range can increase the number of documents scanned, but the main issue is that the query is cross-partition. Even with a small time range, the query would still need to search each partition for matching documents.
D
The document size is too large, increasing RU per read.
Why wrong: Document size does affect RU consumption, but the dramatic increase in RUs from a query that omits the partition key is primarily due to cross-partition execution, not document size.

Full breakdown with real-world context →

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

✓

The query does not use the partition key, causing a cross-partition scan.

The query does not include the partition key (deviceId) in the filter, so Azure Cosmos DB cannot route it to a single physical partition. Instead, it must fan out the query to every partition, scanning all documents across the container. This cross-partition query consumes significantly more RUs and takes longer because each partition must be queried sequentially or in parallel, and the results are merged server-side.

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.

✓
The query does not use the partition key, causing a cross-partition scan.
Why this is correct
When a query does not include the partition key, Cosmos DB must execute the query across all partitions, which increases latency and RU consumption. This is the most likely cause.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The query is not using an index on the temperature field.
Why it's wrong here
While indexes are important, Cosmos DB automatically indexes all fields by default. The absence of a partition key in the filter is the primary issue because it forces a full scan across partitions.
✗
The time range filter is too large, causing a full table scan.
Why it's wrong here
A large time range can increase the number of documents scanned, but the main issue is that the query is cross-partition. Even with a small time range, the query would still need to search each partition for matching documents.
✗
The document size is too large, increasing RU per read.
Why it's wrong here
Document size does affect RU consumption, but the dramatic increase in RUs from a query that omits the partition key is primarily due to cross-partition execution, not document size.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates may assume indexing is the culprit (Option B) because they think a missing index causes slow queries, but Azure Cosmos DB indexes all fields automatically, so the real issue is the missing partition key forcing a cross-partition scan.

Detailed technical explanation

How to think about this question

Under the hood, Azure Cosmos DB uses a hash-based partition strategy: the partition key value is hashed to determine which physical partition stores the data. Without the partition key in the query filter, the query engine must issue a parallel query to every physical partition, and the RU charge is the sum of all partition-level query costs. In a real-world scenario, if the container has hundreds of partitions, this query could consume thousands of RUs even for a small result set, making it unsuitable for frequent or latency-sensitive operations.

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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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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: The query does not use the partition key, causing a cross-partition scan. — The query does not include the partition key (deviceId) in the filter, so Azure Cosmos DB cannot route it to a single physical partition. Instead, it must fan out the query to every partition, scanning all documents across the container. This cross-partition query consumes significantly more RUs and takes longer because each partition must be queried sequentially or in parallel, and the results are merged server-side.

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: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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