- A
You can use the filepath() function in the query to retrieve the partition column values.
The filepath function returns the partition path values.
- B
Partition elimination is automatically applied when filtering on the partition column in the WHERE clause.
Serverless SQL pool prunes partitions based on the partition column filter.
- C
You must create an external table to query Parquet files; OPENROWSET is not supported.
Why wrong: OPENROWSET is supported and can query Parquet files directly.
- D
You can create indexes on the serverless SQL pool to improve query performance.
Why wrong: Serverless SQL pool does not support index creation.
- E
You can only query a single file at a time; wildcards are not supported.
Why wrong: Wildcards are supported to query multiple files.
Quick Answer
The answer is that partition elimination is automatically applied when filtering on the partition column in the WHERE clause, and the `filepath()` function can extract partition values from the folder structure. This works because serverless SQL pool reads the directory hierarchy—such as `/year=2023/month=01/day=15/`—as virtual columns, allowing the query engine to skip irrelevant partitions automatically when you filter on the partition key. On the DP-203 exam, this concept tests your understanding of how serverless SQL pools leverage the Hive-style partitioning of Parquet files in Azure Data Lake Storage Gen2, often appearing in scenario-based questions where you must choose between automatic partition pruning and manual path parsing. A common trap is assuming you need to use `OPENROWSET` with wildcards to achieve elimination, but the engine handles it natively. Remember the mnemonic “PATH = Partition Auto-Trim with Hive” to recall that the folder structure drives automatic filtering.
DP-203 Develop data processing Practice Question
This DP-203 practice question tests your understanding of develop data processing. 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.
You are designing a data processing solution in Azure Synapse Analytics. The solution must use a serverless SQL pool to query data in Azure Data Lake Storage Gen2. The data is stored as Parquet files partitioned by date. Which TWO of the following statements are true regarding querying this data? (Select TWO.)
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
You can use the filepath() function in the query to retrieve the partition column values.
Option A is correct because the `filepath()` function in a serverless SQL pool query returns the file path of the row being read. When data is partitioned by date in Azure Data Lake Storage Gen2, the partition column values are embedded in the folder structure (e.g., `/year=2023/month=01/day=15/`). Using `filepath(1)`, `filepath(2)`, etc., you can extract these values directly in the query without needing to parse the path manually.
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.
- ✓
You can use the filepath() function in the query to retrieve the partition column values.
Why this is correct
The filepath function returns the partition path values.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Partition elimination is automatically applied when filtering on the partition column in the WHERE clause.
Why this is correct
Serverless SQL pool prunes partitions based on the partition column filter.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
You must create an external table to query Parquet files; OPENROWSET is not supported.
Why it's wrong here
OPENROWSET is supported and can query Parquet files directly.
- ✗
You can create indexes on the serverless SQL pool to improve query performance.
Why it's wrong here
Serverless SQL pool does not support index creation.
- ✗
You can only query a single file at a time; wildcards are not supported.
Why it's wrong here
Wildcards are supported to query multiple files.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume serverless SQL pools behave like dedicated SQL pools, leading them to think indexes are needed or that external tables are mandatory, when in fact serverless pools are schema-on-read and rely on file metadata and statistics for performance.
Detailed technical explanation
How to think about this question
Under the hood, serverless SQL pool uses a distributed query engine that reads Parquet files directly from ADLS Gen2 via the Hadoop FileSystem API. Partition elimination works because the engine pushes down filter predicates on the partition column to the storage layer, skipping entire folders that don’t match. The `filepath()` function leverages the folder hierarchy to expose partition values, which is especially useful when the partition column is not a column in the Parquet schema itself.
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 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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this DP-203 question test?
Develop data processing — This question tests Develop data processing — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: You can use the filepath() function in the query to retrieve the partition column values. — Option A is correct because the `filepath()` function in a serverless SQL pool query returns the file path of the row being read. When data is partitioned by date in Azure Data Lake Storage Gen2, the partition column values are embedded in the folder structure (e.g., `/year=2023/month=01/day=15/`). Using `filepath(1)`, `filepath(2)`, etc., you can extract these values directly in the query without needing to parse the path manually.
What should I do if I get this DP-203 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 24, 2026
This DP-203 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-203 exam.
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