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?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
Best answer
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.
Distractor review
The query is not using an index on the temperature field.
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.
Distractor review
The time range filter is too large, causing a full table scan.
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.
Distractor review
The document size is too large, increasing RU per read.
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 trap
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Technical deep dive
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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.
Related practice questions
Related DP-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
Question 1
A data engineer needs to process streaming data from IoT devices and store the results in Azure Data Lake Storage for long-term analytics. The data must be processed in near real-time to detect anomalies and trigger alerts. Which Azure service should the engineer use for stream processing?
Question 2
A data engineer needs to query data stored in CSV files in Azure Data Lake Storage Gen2 using T-SQL in Azure Synapse Analytics, without loading the data into the database. Which feature should they use?
Question 3
A data engineer needs to process raw clickstream data from multiple websites that is stored in Azure Blob Storage as JSON files. The processing must run automatically every hour, transform the data into a structured format for reporting, and handle schema changes in the source data without manual intervention. Which Azure service should be used?
Question 4
A data engineer is designing a data lake architecture in Azure. They plan to first ingest raw data from various sources into a landing zone in Azure Data Lake Storage Gen2. Then they will clean, validate, and deduplicate that data in a second zone. Finally, they will create aggregated, business-ready datasets in a third zone for analysts. This layered approach is known as which architecture?
Question 5
A data engineer needs to transform large datasets stored in Azure Data Lake Storage Gen2 using Python and Apache Spark. They want a serverless compute option that automatically scales and requires no cluster management. Which Azure service should they use?
Question 6
A company collects customer feedback forms. Each form contains always-present fields like CustomerID and SubmissionDate, but also a free-text Comments field and optional fields like Rating or ProductCategory that vary between forms. How should this data be classified?
FAQ
Questions learners often ask
What does this DP-900 question test?
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. — In Azure Cosmos DB, the partition key is used to distribute data across physical partitions. The most efficient queries include the partition key in the filter because they are routed to a single partition. Queries that do not include the partition key must be executed across all partitions (cross-partition query), which requires scanning multiple partitions and consumes significantly more RUs. In this scenario, the query does not specify deviceId (the partition key), so Cosmos DB must fan out the query to all partitions, resulting in slow performance and high RU consumption. The correct approach is to redesign the query to include the partition key or create a materialized view based on temperature.
What should I do if I get this DP-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
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