Quick Answer
The answer is to change the distribution key to hash on OrderDate. This is correct because in an Azure Synapse dedicated SQL pool, hash distribution physically co-locates rows with the same distribution column value on the same distribution node. When queries filter heavily on OrderDate, using it as the distribution key allows the engine to prune entire distributions that don’t match the filter, drastically reducing data movement and improving scan performance. On the DP-203 exam, this scenario tests your understanding of distribution design trade-offs—specifically, aligning the distribution column with the most frequent filter predicate to minimize shuffling. A common trap is to assume that any hash distribution is sufficient, but the key insight is that the distribution column should match the filter column for optimal partition elimination. Memory tip: “Filter first, distribute second”—always choose the column that appears in your WHERE clause most often as the hash distribution key.
This DP-203 practice question tests your understanding of design and implement data 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. 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 uses Azure Synapse Analytics dedicated SQL pool for data warehousing. They notice that queries against a large fact table are slow. The table is hash-distributed on ProductID, but many queries filter on OrderDate. What should the data engineer do to improve query performance?
Change the distribution to round-robin
Why wrong: Does not improve filter performance.
Replicate the table to all distributions
Why wrong: Impractical for large tables.
Create a columnstore index on OrderDate
Why wrong: Does not address distribution; still incurs data movement.
Change the distribution to hash on OrderDate
Aligns distribution with filter column, minimizing data movement.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Change the distribution to hash on OrderDate
Option D is correct because changing the distribution key to OrderDate aligns the physical data layout with the most common query filter predicate. In a dedicated SQL pool, hash distribution distributes rows across distributions based on the hash of the distribution column. When queries filter on OrderDate, a hash on OrderDate enables partition elimination and distribution-level pruning, reducing data movement and improving scan performance.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Change the distribution to round-robin
Why it's wrong here
Does not improve filter performance.
Replicate the table to all distributions
Why it's wrong here
Impractical for large tables.
Create a columnstore index on OrderDate
Why it's wrong here
Does not address distribution; still incurs data movement.
Change the distribution to hash on OrderDate
Why this is correct
Aligns distribution with filter column, minimizing data movement.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates often confuse indexing (columnstore) with distribution strategy, assuming a non-clustered index on the filter column is sufficient, when in fact the distribution key must match the most frequent filter predicate to avoid full distribution scans.
Detailed technical explanation
Hash distribution uses a deterministic hash function (e.g., BINARY_CHECKSUM) on the distribution column to assign rows to one of 60 distributions. When the distribution key matches the filter column, the query optimizer can perform distribution elimination, reading only the relevant distributions. In contrast, a columnstore index on OrderDate would still require scanning all distributions unless the table is also partitioned on OrderDate, but partitioning alone does not eliminate distribution-level data movement.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
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FAQ
Design and implement data storage — This question tests Design and implement data storage — Read the scenario before looking for a memorised answer..
The correct answer is: Change the distribution to hash on OrderDate — Option D is correct because changing the distribution key to OrderDate aligns the physical data layout with the most common query filter predicate. In a dedicated SQL pool, hash distribution distributes rows across distributions based on the hash of the distribution column. When queries filter on OrderDate, a hash on OrderDate enables partition elimination and distribution-level pruning, reducing data movement and improving scan performance.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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