- A
A) Keep the clustered index on OrderID and create a non-clustered index on (CustomerID, OrderDate)
The clustered index on OrderID ensures fast point lookups. The non-clustered index on (CustomerID, OrderDate) covers the range query, allowing SQL Server to perform an index seek without accessing the full table.
- B
B) Change the clustered index to (CustomerID, OrderDate) and create a non-clustered index on OrderID
Why wrong: Changing the clustered index to (CustomerID, OrderDate) would improve the range query but degrade point lookups by OrderID because the clustered index would not be on OrderID, requiring a non-clustered index seek plus a key lookup.
- C
C) Keep the clustered index on OrderID and create a non-clustered index on (OrderDate, CustomerID)
Why wrong: While this may help, the column order (OrderDate first) is less optimal for the typical query pattern which filters on CustomerID first, then OrderDate. The index would need to scan multiple date ranges for each customer, reducing efficiency.
- D
D) Keep the clustered index on OrderID and create two separate non-clustered indexes on CustomerID and OrderDate
Why wrong: Separate indexes can help but the database may need to intersect them or perform a key lookup for each matched row, which is less efficient than a single covering composite index on (CustomerID, OrderDate).
DP-900 Practice Question: Identify considerations for relational data on Azure
This DP-900 practice question tests your understanding of identify considerations for 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. A key principle to apply: a clustered index defines the physical storage order of data rows.. 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 uses Azure SQL Database for an e-commerce application. The Orders table contains columns: OrderID (int, primary key), CustomerID (int), OrderDate (datetime), TotalAmount (decimal). Queries frequently filter by CustomerID and OrderDate to retrieve orders for a specific customer within a date range. Queries also need to retrieve a single order by OrderID quickly. Which indexing strategy will most improve the performance of these queries?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"primary"Why it matters: Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.
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) Keep the clustered index on OrderID and create a non-clustered index on (CustomerID, OrderDate)
Option A is correct because the existing clustered index on OrderID efficiently supports the single-order lookup by primary key. Adding a non-clustered index on (CustomerID, OrderDate) provides a covering index for the range queries filtering by CustomerID and OrderDate, allowing SQL Server to perform an index seek and avoid key lookups, which significantly improves performance.
Key principle: A clustered index defines the physical storage order of data rows.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
A) Keep the clustered index on OrderID and create a non-clustered index on (CustomerID, OrderDate)
Why this is correct
The clustered index on OrderID ensures fast point lookups. The non-clustered index on (CustomerID, OrderDate) covers the range query, allowing SQL Server to perform an index seek without accessing the full table.
Clue confirmation
The clue word "primary" in the question point toward this answer.
Related concept
A clustered index defines the physical storage order of data rows.
- ✗
B) Change the clustered index to (CustomerID, OrderDate) and create a non-clustered index on OrderID
Why it's wrong here
Changing the clustered index to (CustomerID, OrderDate) would improve the range query but degrade point lookups by OrderID because the clustered index would not be on OrderID, requiring a non-clustered index seek plus a key lookup.
- ✗
C) Keep the clustered index on OrderID and create a non-clustered index on (OrderDate, CustomerID)
Why it's wrong here
While this may help, the column order (OrderDate first) is less optimal for the typical query pattern which filters on CustomerID first, then OrderDate. The index would need to scan multiple date ranges for each customer, reducing efficiency.
- ✗
D) Keep the clustered index on OrderID and create two separate non-clustered indexes on CustomerID and OrderDate
Why it's wrong here
Separate indexes can help but the database may need to intersect them or perform a key lookup for each matched row, which is less efficient than a single covering composite index on (CustomerID, OrderDate).
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often think separate indexes on each column are sufficient for composite queries, but they overlook that a single composite index with the correct column order (high selectivity first) avoids costly index intersection and provides direct seek capability.
Detailed technical explanation
How to think about this question
A composite non-clustered index on (CustomerID, OrderDate) enables a single index seek on CustomerID, followed by a range scan on OrderDate within that customer's rows, making it a covering index if all needed columns are included. Under the hood, SQL Server uses the B-tree structure to navigate directly to the first matching row, then sequentially reads the leaf pages for the date range, minimizing I/O. In real-world scenarios with millions of orders, this strategy reduces logical reads from thousands to just a few per query.
KKey Concepts to Remember
- A clustered index defines the physical storage order of data rows.
- A table can have only one clustered index.
- Non-clustered indexes are separate data structures pointing to table data.
- Composite non-clustered indexes optimize queries filtering on multiple columns in specific order.
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
A clustered index defines the physical storage order of data rows.
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. A clustered index defines the physical storage order of data rows. 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.
Review a clustered index defines the physical storage order of data rows., then practise related DP-900 questions on the same topic to reinforce the concept.
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FAQ
Questions learners often ask
What does this DP-900 question test?
Identify considerations for relational data on Azure — This question tests Identify considerations for relational data on Azure — A clustered index defines the physical storage order of data rows..
What is the correct answer to this question?
The correct answer is: A) Keep the clustered index on OrderID and create a non-clustered index on (CustomerID, OrderDate) — Option A is correct because the existing clustered index on OrderID efficiently supports the single-order lookup by primary key. Adding a non-clustered index on (CustomerID, OrderDate) provides a covering index for the range queries filtering by CustomerID and OrderDate, allowing SQL Server to perform an index seek and avoid key lookups, which significantly improves performance.
What should I do if I get this DP-900 question wrong?
Review a clustered index defines the physical storage order of data rows., then practise related DP-900 questions on the same topic to reinforce the concept.
Are there clue words in this question I should notice?
Yes — watch for: "primary". Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.
What is the key concept behind this question?
A clustered index defines the physical storage order of data rows.
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Last reviewed: Jun 11, 2026
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