Databricks-Certified-Data-Engineer-Associate by Databricks Valid Free Exam Practice Test

Question 1

A data engineer wants to create a relational object by pulling data from two tables. The relational object does not need to be used by other data engineers in other sessions. In order to save on storage costs, the data engineer wants to avoid copying and storing physical data.
Which of the following relational objects should the data engineer create?

A. Database B. Delta Table C. View D. Temporary view E. Spark SQL Table

Correct Answer: D

Question 2

Which two components function in the DB platform architecture's control plane? (Choose two.)

A. Serverless Compute B. Virtual Machines C. Compute Orchestration D. Compute E. Unity Catalog

Correct Answer: C,E

Question 3

A data engineer and data analyst are working together on a data pipeline. The data engineer is working on the raw, bronze, and silver layers of the pipeline using Python, and the data analyst is working on the gold layer of the pipeline using SQL. The raw source of the pipeline is a streaming input. They now want to migrate their pipeline to use Delta Live Tables. Which change will need to be made to the pipeline when migrating to Delta Live Tables?

A. The pipeline will need to use a batch source in place of a streaming source. B. The pipeline will need to be written entirely in Python. C. The pipeline will need to be written entirely in SQL. D. The pipeline can have different notebook sources in SQL & Python.

Correct Answer: D

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Question 4

A data provider must share a live Delta table with an external partner who uses an open-source Spark environment outside Databricks, without copying the data.
Which feature should be used?

A. A materialized view exported as Parquet and delivered by SFTP B. A Unity Catalog external location with a storage credential granted to the partner C. A deep clone written to a partner-owned S3 bucket nightly D. Delta Sharing with a recipient and share

Correct Answer: D

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Question 5

A data engineer runs a statement every day to copy the previous day's sales into the table transactions. Each day's sales are in their own file in the location "/transactions/raw".
Today, the data engineer runs the following command to complete this task:

After running the command today, the data engineer notices that the number of records in table transactions has not changed.
Which of the following describes why the statement might not have copied any new records into the table?

A. The previous day's file has already been copied into the table. B. The format of the files to be copied were not included with the FORMAT_OPTIONS keyword. C. The PARQUET file format does not support COPY INTO. D. The names of the files to be copied were not included with the FILES keyword. E. The COPY INTO statement requires the table to be refreshed to view the copied rows.

Correct Answer: A

Question 6

Which of the following must be specified when creating a new Delta Live Tables pipeline?

A. The preferred DBU/hour cost B. A location of a target database for the written data C. At least one notebook library to be executed D. A path to cloud storage location for the written data E. A key-value pair configuration

Correct Answer: C

Question 7

Which of the following can be used to simplify and unify siloed data architectures that are specialized for specific use cases?

A. Data lakehouse B. Data warehouse C. Data lake D. None of these E. All of these

Correct Answer: A

Question 8

A team is using a Databricks workspace and needs to continuously ingest JSON files as they arrive. Which code snippet shows a valid Auto Loader source configuration?

A.

B.

C.

D.

Correct Answer: B

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Question 9

Which of the following benefits is provided by the array functions from Spark SQL?

A. An ability to work with data in a variety of types at once B. An ability to work with time-related data in specified intervals C. An ability to work with data within certain partitions and windows D. An ability to work with complex, nested data ingested from JSON files E. An ability to work with an array of tables for procedural automation

Correct Answer: D

Question 10

Which single Databricks CLI command deploys local bundle assets to the target workspace specified in the configuration file?

A. databricks bundle plan && databricks bundle run B. databricks bundle init && databricks bundle deployment C. databricks bundle deploy D. databricks bundle validate

Correct Answer: C

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Question 11

A data engineer is troubleshooting two different pipeline failures:
- Pipeline A fails with a java.lang.OutOfMemoryError is immediately
thrown after the command display(df.collect()) is called on a 100GB
dataset.
- Pipeline B fails during a wide transformation (a join of two large
tables) with an ExecutorLostFailure error message, indicating executor
memory exhaustion during shuffle.
Which action should the data engineer take to fix these two issues?

A. For both pipelines, enable Adaptive Query Execution (AQE) as it automatically manages memory allocation for both the driver and executors. B. For Pipeline A, switch to a Storage Optimized cluster; for Pipeline B, use a Compute Optimized cluster. C. For Pipeline A, increase the number of executors; for Pipeline B, increase the driver memory. D. For Pipeline A, increase the spark.driver.memory; for Pipeline B, increase the spark.sql.shuffle.partitions or executor memory.

Correct Answer: D

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Question 12

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?

A.

B.

C.

D.

Correct Answer: B

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Question 13

A data engineer is working in a Databricks notebook to design and manage a batch ETL pipeline.
The engineer is writing SQL and Python code to clean data, transform it, and join large datasets from different sources. The engineer wants to organize these steps into a structured process that can be run regularly and scheduled as part of a data pipeline. Which Databricks notebook feature is applicable in the use case?

A. Notebook version control B. Collaborative editing C. Real-time streaming support D. Task workflows and job scheduling

Correct Answer: D

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Question 14

A Databricks workflow fails at the last stage due to an error in a notebook. This workflow runs daily. The data engineer fixes the mistake and wants to rerun the pipeline. This workflow is very costly and time-intensive to run. Which action should the data engineer do in order to minimise downtime and cost?

A. Re-run the entire workflow B. Restart the cluster C. Repair run D. Switch to another cluster

Correct Answer: C

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Databricks Certified Data Engineer Associate - Databricks-Certified-Data-Engineer-Associate Exam Practice Test