DatabricksCertified Data Engineer Professional
Domain 2Objective 1
Design and Implement Data Ingestion Pipelines to Efficiently Ingest a Variety of Data Formats Including Delta Lake, Parquet, ORC, AVRO, JSON, CSV, XML, Text and Binary from Diverse Sources Such as Message Buses and Cloud Storage. DATA-ENGINEER-PROFESSIONAL Practice Questions (Page 1)
Part of the Data Ingestion & Acquisition domain, which accounts for 7% of the DATA-ENGINEER-PROFESSIONAL exam. Databricks does not publish an official question count, but from its 120-minute exam (~50–80 total, ~4–6 in this domain), expect 2–3 from this objective — we provide 34 practice questions to prepare you well beyond it. (estimate)
34questions here
7free pages
15concepts
7%of the exam
Questions 1–5
- 1
A data platform team is designing an ingestion pipeline for a large dataset of user events. The data will be used for both real-time dashboards and historical analytics. The team needs to choose a storage format for the raw ingested data that balances query performance, storage efficiency, and schema evolution support. Which format should they choose?
Select an answer first - 2
Which method is specifically designed to incrementally load data files from cloud storage into a Delta Lake table while automatically handling schema evolution and file discovery?
Select an answer first - 3
When reading Avro files into a Spark DataFrame, what is the default behavior regarding the schema?
Select an answer first - 4
When writing a DataFrame to Parquet files, which Spark option controls the compression codec used for the output?
Select an answer first - 5
Which data format is specifically designed to provide ACID transactions, time travel, and schema enforcement on top of existing Parquet data files?
Select an answer first
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