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  • Total Questions: 322
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Databricks Databricks-Certified-Data-Engineer-Associate Exam Syllabus Topics:

TopicDetails
Topic 1
  • Production Pipelines: It focuses on identifying the advantages of using multiple tasks in Jobs, a suitable scenario where predecessor task should be set up, CRON as an opportunity for scheduling opportunity, and how an alert can be sent via email. The topic also discusses setting up a predecessor task in Jobs, reviewing a task's execution history, and debugging a failed task. Lastly, it delves into setting up a retry policy in case of failure and creating an alert in the case of a failed task.
Topic 2
  • Incremental Data Processing: In this topic questions about identifying Delta Lake, benefits of ACID transactions, a scenario to use an external table, location of a table, the benefits of Zordering, the kind of files, CTAS as a solution, the impact of ON VIOLATION DROP ROW and ON VIOLATION FAIL UPDATE, and the necessary component to create a new DLT pipeline. Moreover, the topic also discusses directory structure of Delta Lake files, generated column, adding a table comment, and the benefits of the MERGE command.
Topic 3
  • Databricks Lakehouse Platform: This topic covers the relationship between the data lakehouse and the data warehouse, the improvement in data quality, comparing and contrasting silver and gold tables, elements of the Databricks Platform Architecture, and differentiating between all-purpose clusters and jobs clusters. Moreover, it identifies how cluster software is versioned, how clusters can be filtered, how to use multiple languages, how to run one notebook, how notebooks can be shared, Git operations, and limitations in Databricks Notebooks. Lastly, the topic describes how clusters are terminated, how to use multiple languages, and how Databricks Repos enables CI
  • CD workflows.
Topic 4
  • ELT with Apache Spark: It focuses on extracting data, identifying the prefix, creating a view, duplicating rows, creating a new table, utilizing the dot, parsing JSON, and defining a SQL UDF. Moreover, the topic delves into describing the security model, identifying the location of a function, and identifying the PIVOT.
Topic 5
  • Data Governance: It identifies one of the four areas of data governance, Unity Catalog securables, and the cluster security modes. It also discusses how to create a UC-enabled all-purpose cluster and a DBSQL warehouse. The topic explains how to implement data object access control, create a DBSQL warehouse, and e a UC-enabled all-purpose cluster.

Reference: https://www.databricks.com/learn/certification/data-engineer-associate

Databricks Certified Data Engineer Associate Sample Questions:

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. Delta Sharing with a recipient and share
  • B. A Unity Catalog external location with a storage credential granted to the partner
  • C. A materialized view exported as Parquet and delivered by SFTP
  • D. A deep clone written to a partner-owned S3 bucket nightly
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).

A Lakeflow Jobs workflow fails at the last task because of an error in a notebook task. This workflow is scheduled to run daily. The data engineer fixes the notebook and wants to rerun the pipeline. This workflow is very compute-intensive and expensive to run. Which action should the data engineer take in order to minimize downtime and compute cost?

  • A. Repair run
  • B. Switch to another cluster
  • C. Re-run the entire workflow
  • D. Restart the cluster
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).

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. Spark SQL Table
  • B. Database
  • C. Delta Table
  • D. View
  • E. Temporary view
Reveal Solution  Discussion  0

Correct Answer: E  🗳️

A data engineer needs to read files from cloud object storage into a Spark DataFrame in Databricks. The files are stored in CSV format with headers and comma delimiters. Which Spark DataFrame reader option ensures that column names are correctly inferred from the first row?

  • A. header
  • B. delimiter
  • C. mode
  • D. inferSchema
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

A data engineer wants to analyze historical versions of a Delta table to debug a data quality issue. The engineer needs to query the table as it existed two days ago. Which Delta Lake feature allows querying older snapshots of a table?

  • A. Time Travel
  • B. VACUUM
  • C. Z-Ordering
  • D. OPTIMIZE
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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