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Databricks-Certified-Data-Engineer-Associate exam is a comprehensive test of an individual's knowledge of Databricks and its related technologies, including Apache Spark, SQL, and Python. It evaluates the ability of candidates to design, build, and maintain data pipelines using Databricks. Databricks Certified Data Engineer Associate Exam certification is ideal for data engineers, data architects, and data scientists who want to showcase their skills and knowledge in working with Databricks.

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The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) certification exam is designed for professionals who want to demonstrate their expertise in building and maintaining data pipelines on the Databricks platform. Databricks-Certified-Data-Engineer-Associate Exam validates the skills and knowledge required to design, build, and maintain data pipelines on Databricks, and is a recognition of the candidate's ability to work with big data technologies and tools.

Databricks Certified Data Engineer Associate Exam Sample Questions (Q224-Q229):

NEW QUESTION # 224
In a Lakeflow Declarative Pipeline (Delta Live Tables), a data engineer must ensure that records with a null order_id are discarded from the silver table while the pipeline continues to run.
Which expectation clause should be used?

Answer: C

Explanation:
ON VIOLATION DROP ROW removes failing records from the target dataset and records the violation in the event log while the pipeline continues. An expectation with no ON VIOLATION clause retains bad records and only reports metrics, and FAIL UPDATE stops the pipeline.


NEW QUESTION # 225
A data engineer is configuring a batch processing job in Databricks to read large Parquet datasets from cloud storage. The engineer wants Spark to automatically distribute computation across multiple worker nodes without manually assigning tasks. Which Spark abstraction enables automatic parallel processing?

Answer: B


NEW QUESTION # 226
When using MERGE INTOin Delta Lake on Databricks, which clause allows you to atomically delete target rows that no longer match any source rows?

Answer: B

Explanation:
The clause that deletes target rows not present in the source is the one that triggers when a target row has no matching source row, enabling atomic removal of outdated records during the merge operation.


NEW QUESTION # 227
A data engineer has been provided a PySpark DataFrame named dfwith columns product and revenue. The data engineer needs to compute complex aggregations to determine each product's total revenue, average revenue, and transaction count. Which code snippet should the data engineer use?

Answer: C

Explanation:
The correct code uses PySpark functions (sum, avg, count) with aliases inside .agg() after grouping by product. This produces total revenue, average revenue, and transaction count for each product.


NEW QUESTION # 228
A data engineer has realized that they made a mistake when making a daily update to a table. They need to use Delta time travel to restore the table to a version that is 3 days old. However, when the data engineer attempts to time travel to the older version, they are unable to restore the data because the data files have been deleted.
Which of the following explains why the data files are no longer present?

Answer: C

Explanation:
Explanation
The VACUUM command in Delta Lake is used to clean up and remove unnecessary data files that are no longer needed for time travel or query purposes. When you run VACUUMwith certain retention settings, it can delete older data files, which might include versions of data that are older than the specified retention period. If the data engineer is unable to restore the table to a version that is 3 days old because the data files have been deleted, it's likely because the VACUUM command was run on the table, removing the older data files as part of data cleanup.


NEW QUESTION # 229
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