Question 930 of 982

Quick Answer

The answer is to replicate the Product dimension table to all distributions. This is correct because in a Synapse dedicated SQL pool, hash distribution on SaleDate scatters fact table rows across 60 distributions, but joining on ProductID forces data shuffling since that column isn’t the distribution key. Replicating the small dimension table places a full copy on every distribution, allowing the join to execute locally without moving data between nodes. On the DP-900 exam, this scenario tests your understanding of table distribution and replication for join performance—a common trap is thinking you should change the fact table’s distribution column, but replicating the smaller table is more efficient. Remember the memory tip: “Replicate the small, hash the large” to avoid costly shuffles when keys don’t align.

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. 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 to store a large fact table with billions of rows. The table is distributed using hash distribution on the SaleDate column. Queries that join this fact table with a small dimension table (Product) on ProductID are slow because the join requires shuffling data across distributions. Which design change would most improve the performance of these join queries?

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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

Replicate the Product dimension table to all distributions.

Replicating the Product dimension table to all distributions eliminates the need to shuffle data across distributions during the join. In Azure Synapse dedicated SQL pool, hash distribution distributes rows across 60 distributions based on the hash of the distribution column (SaleDate). When joining on ProductID, which is not the distribution column, data must be moved between distributions. Replicating the small dimension table ensures each distribution has a local copy, allowing the join to be performed without data movement, significantly improving performance.

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.

  • Change the distribution of the fact table to round-robin.

    Why it's wrong here

    Round-robin distribution distributes data evenly but without a hash key. All joins will require data shuffling, which does not solve the problem.

  • Replicate the Product dimension table to all distributions.

    Why this is correct

    Correct. Replicating small dimension tables ensures that each distribution has a local copy of the entire table, avoiding data movement during joins.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Partition the fact table by SaleDate.

    Why it's wrong here

    Partitioning primarily helps with partition elimination for queries filtering on the partition key. It does not directly help with join performance.

  • Create a nonclustered index on ProductID in the fact table.

    Why it's wrong here

    In a dedicated SQL pool, nonclustered indexes are not commonly used for performance tuning of joins. The main performance lever is distribution design.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse partitioning with distribution, thinking partitioning on SaleDate will help the join on ProductID, but partitioning only segments data within a distribution and does not reduce cross-distribution data movement for joins on a different column.

Detailed technical explanation

How to think about this question

In Azure Synapse dedicated SQL pool, data movement for joins occurs when the join column is not the distribution column; the engine must redistribute rows so matching keys land on the same distribution. Replication creates a full copy of the dimension table on each of the 60 distributions, stored as a round-robin distributed table with a clustered columnstore index by default. This is ideal for small dimension tables (typically < 2 GB after compression) and avoids the overhead of a distributed join, which can involve shuffling billions of rows across the network.

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

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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 — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Replicate the Product dimension table to all distributions. — Replicating the Product dimension table to all distributions eliminates the need to shuffle data across distributions during the join. In Azure Synapse dedicated SQL pool, hash distribution distributes rows across 60 distributions based on the hash of the distribution column (SaleDate). When joining on ProductID, which is not the distribution column, data must be moved between distributions. Replicating the small dimension table ensures each distribution has a local copy, allowing the join to be performed without data movement, significantly improving performance.

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.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 11, 2026

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