- A
Partition key: sensor ID; row key: ISO timestamp of the reading
Co-locating readings by sensor ID allows the storage engine to scan only that partition for time-range queries. Timestamp row keys are naturally ordered, so range queries resolve efficiently without scanning unrelated partitions.
- B
Partition key: a single constant ('all-sensors'); row key: sensor ID + timestamp
Why wrong: A single partition for all sensors creates a hot partition. Every write lands in one partition, which Table Storage rate-limits at the partition level. This becomes a bottleneck at high write volumes.
- C
Partition key: timestamp (rounded to the hour); row key: sensor ID
Why wrong: Partitioning by time means queries filtering by sensor ID must scan all partitions, because a sensor's readings are spread across many time-based partitions. This eliminates the locality benefit of partitioning.
- D
Partition key: random GUID per reading; row key: timestamp
Why wrong: Random GUIDs as partition keys distribute writes evenly but destroy locality completely. Querying by sensor ID requires scanning all partitions, making range queries O(n) across the entire table.
AZ-204 Practice Question: Table Storage partition key design for…
This AZ-204 practice question tests your understanding of develop for azure storage. 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. A key principle to apply: azure Table Storage. 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.
An application stores sensor readings in Azure Table Storage. Each sensor produces thousands of readings per hour. Queries always filter by sensor ID and time range. A developer needs to choose the partition key and row key. Which design best balances query performance and write throughput?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"always"Why it matters: Absolute qualifier. An answer using 'always' is only correct if there are genuinely no exceptions — absolute statements are often wrong in networking.
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
Partition key: sensor ID; row key: ISO timestamp of the reading
Option A is correct because it uses sensor ID as the partition key, which ensures all readings for a given sensor are stored in the same partition, enabling efficient range queries by row key (timestamp). This design avoids hot partitions by distributing writes across different sensors, while the row key allows fast point lookups and range scans within a time window, balancing query performance and write throughput.
Key principle: Azure Table Storage
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Partition key: sensor ID; row key: ISO timestamp of the reading
Why this is correct
Co-locating readings by sensor ID allows the storage engine to scan only that partition for time-range queries. Timestamp row keys are naturally ordered, so range queries resolve efficiently without scanning unrelated partitions.
Clue confirmation
The clue word "always" in the question point toward this answer.
Related concept
Azure Table Storage
- ✗
Partition key: a single constant ('all-sensors'); row key: sensor ID + timestamp
Why it's wrong here
A single partition for all sensors creates a hot partition. Every write lands in one partition, which Table Storage rate-limits at the partition level. This becomes a bottleneck at high write volumes.
- ✗
Partition key: timestamp (rounded to the hour); row key: sensor ID
Why it's wrong here
Partitioning by time means queries filtering by sensor ID must scan all partitions, because a sensor's readings are spread across many time-based partitions. This eliminates the locality benefit of partitioning.
- ✗
Partition key: random GUID per reading; row key: timestamp
Why it's wrong here
Random GUIDs as partition keys distribute writes evenly but destroy locality completely. Querying by sensor ID requires scanning all partitions, making range queries O(n) across the entire table.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose a partition key that groups data by time (Option C) to optimize time-range queries, but they overlook that this creates a hot partition for all sensors in that time window, severely limiting write throughput.
Detailed technical explanation
How to think about this question
Azure Table Storage uses a partition key to distribute data across partition servers; a well-chosen partition key ensures even load distribution and supports efficient queries. The row key combined with the partition key forms the primary key, and Azure Table Storage maintains a clustered index on (PartitionKey, RowKey), so range queries on the row key within a partition are O(log n). In high-throughput scenarios, using sensor ID as the partition key allows each sensor's writes to be isolated, avoiding throttling while still enabling fast time-range queries via the row key.
KKey Concepts to Remember
- Azure Table Storage
- partition key design
- row key ordering
- hot partition
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
Azure Table Storage
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Review azure Table Storage, then practise related AZ-204 questions on the same topic to reinforce the concept.
- →
Develop for Azure storage — study guide chapter
Learn the concepts, then practise the questions
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Develop for Azure storage practice questions
Targeted practice on this topic area only
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Microsoft Azure Developer Associate AZ-204 study guide
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FAQ
Questions learners often ask
What does this AZ-204 question test?
Develop for Azure storage — This question tests Develop for Azure storage — Azure Table Storage.
What is the correct answer to this question?
The correct answer is: Partition key: sensor ID; row key: ISO timestamp of the reading — Option A is correct because it uses sensor ID as the partition key, which ensures all readings for a given sensor are stored in the same partition, enabling efficient range queries by row key (timestamp). This design avoids hot partitions by distributing writes across different sensors, while the row key allows fast point lookups and range scans within a time window, balancing query performance and write throughput.
What should I do if I get this AZ-204 question wrong?
Review azure Table Storage, then practise related AZ-204 questions on the same topic to reinforce the concept.
Are there clue words in this question I should notice?
Yes — watch for: "always". Absolute qualifier. An answer using 'always' is only correct if there are genuinely no exceptions — absolute statements are often wrong in networking.
What is the key concept behind this question?
Azure Table Storage
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Last reviewed: Jun 11, 2026
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