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Databricks Databricks Certification Databricks-Certified-Data-Engineer-Associate

Databricks-Certified-Data-Engineer-Associate

시험 번호/코드: Databricks-Certified-Data-Engineer-Associate

시험 이름: Databricks Certified Data Engineer Associate Exam

업데이트: 2026-11-08

Q & As: 322문항

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Databricks Databricks-Certified-Data-Engineer-Associate 시험요강:

주제소개
주제 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.
주제 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.
주제 3
  • 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.
주제 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.
주제 5
  • 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.

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

최신 Databricks Certification Databricks-Certified-Data-Engineer-Associate 무료샘플문제

문제 #1
A data engineer investigates a slow stage in the Databricks Spark UI. The engineer scrolls down to the Summary Metrics section for task durations, and they observe for that stage:
25th percentile duration: 40 seconds
Median duration: 45 seconds
75th percentile duration: 50 seconds
Max duration: 80 seconds
What is the interpretation of these metrics?

A. The stage likely suffers from data skew.
B. The cluster is under-provisioned.
C. There is a GC issue.
D. The stage is healthy.


문제 #2
Identify a scenario to use an external table.
A Data Engineer needs to create a parquet bronze table and wants to ensure that it gets stored in a specific path in an external location.
Which table can be created in this scenario?

A. A managed table where the location is pointing to specific path in external location.
B. An external table where the location is pointing to specific path in external location.
C. An external table where the schema has managed location pointing to specific path in external location.
D. A managed table where the catalog has managed location pointing to specific path in external location.


문제 #3
A data engineer creates a view in a Python notebook using
df.createOrReplaceTempView("staging_data") and then attempts to query staging_data from a second notebook attached to the same cluster.
What is the result?

A. The query succeeds but returns an empty result set.
B. The query succeeds because temp views are cluster-scoped.
C. The query succeeds only if the second notebook uses SQL rather than Python.
D. The query fails because the temp view is scoped to the SparkSession of the originating notebook.


문제 #4
A data engineer needs Task C to run ONLY if Task A succeeds AND Task B fails. Which dependency configuration implements this conditional logic?

A. Task C uses two dependency chains: Task A with All succeeded, Task B with at least one failed.
B. Task C depends on Task A (All done) and Task B (All done) with a condition widget.
C. Task C depends on Task A (Success) with Task B listed as a negative dependency.
D. Create a Python task that checks dbutils.jobs.taskValues from Tasks A and B before running Task C.


문제 #5
A data engineer needs to apply custom logic to string column city in table stores for a specific use case. In order to apply this custom logic at scale, the data engineer wants to create a SQL user- defined function (UDF).
Which of the following code blocks creates this SQL UDF?

A.

B.

C.

D.

E.


질문과 대답:

문제 #1
정답: A
문제 #2
정답: B
문제 #3
정답: D
문제 #4
정답: A
문제 #5
정답: D

Databricks-Certified-Data-Engineer-Associate 에 관계 된 시험
Databricks-Certified-Professional-Data-Scientist - Databricks Certified Professional Data Scientist Exam
Databricks-Certified-Data-Engineer-Professional-JPN - Databricks Certified Data Engineer Professional Exam (Databricks-Certified-Data-Engineer-Professional日本語版)
Databricks-Certified-Data-Engineer-Professional - Databricks Certified Data Engineer Professional Exam
Associate-Developer-Apache-Spark-3.5 - Databricks Certified Associate Developer for Apache Spark 3.5 - Python
Databricks-Certified-Professional-Data-Engineer - Databricks Certified Professional Data Engineer Exam
Databricks-Certified-Data-Engineer-Associate - Databricks Certified Data Engineer Associate Exam
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