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GAQM Databricks 인증 데이터 엔지니어 관련 (Databricks Certified Data Engineer Associate) 인증 시험은 데이터 엔지니어링 작업에 데이터 사업을 사용하는 데있어 개인의 지식과 기술을 테스트하도록 설계되었습니다. 이 인증은 업계에서 고도로 인정되고 존중되며 채용 담당자와 고용주가 데이터를 사용한 데이터 엔지니어링에 대한 후보자의 숙련도를 평가할 수있는 벤치 마크로 사용될 수 있습니다.

최신 Databricks Certification Databricks-Certified-Data-Engineer-Associate 무료샘플문제 (Q22-Q27):

질문 # 22
A data engineer needs to apply custom logic to identify employees with more than 5 years of experience in array column employees in table stores. The custom logic should create a new column exp_employees that is an array of all of the employees with more than 5 years of experience for each row. In order to apply this custom logic at scale, the data engineer wants to use the FILTER higher-order function.
Which of the following code blocks successfully completes this task?

A. Option A
B. Option E
C. Option B
D. Option C
E. Option D

정답：A

설명：
Option A is the correct answer because it uses the FILTER higher-order function correctly to filter out employees with more than 5 years of experience from the array column "employees". It applies a lambda function i -> i.years_exp > 5 that checks if the years of experience of each employee in the array is greater than 5. If this condition is met, the employee is included in the new array column "exp_employees".
References: The use of higher-order functions like FILTER can be referenced from Databricks documentation on Higher-Order Functions.

질문 # 23
A data engineer is designing a data pipeline. The source system generates files in a shared directory that is also used by other processes. As a result, the files should be kept as is and will accumulate in the directory. The data engineer needs to identify which files are new since the previous run in the pipeline, and set up the pipeline to only ingest those new files with each run.
Which of the following tools can the data engineer use to solve this problem?

A. Databricks SQL
B. Unity Catalog
C. Auto Loader
D. Delta Lake
E. Data Explorer

정답：C

설명：
Auto Loader is a tool that can incrementally and efficiently process new data files as they arrive in cloud storage without any additional setup. Auto Loader provides a Structured Streaming source called cloudFiles, which automatically detects and processes new files in a given input directory path on the cloud file storage. Auto Loader also tracks the ingestion progress and ensures exactly-once semantics when writing data into Delta Lake. Auto Loader can ingest various file formats, such as JSON, CSV, XML, PARQUET, AVRO, ORC, TEXT, and BINARYFILE. Auto Loader has support for both Python and SQL in Delta Live Tables, which are a declarative way to build production-quality data pipelines with Databricks. Reference: What is Auto Loader?, Get started with Databricks Auto Loader, Auto Loader in Delta Live Tables

질문 # 24
Which of the following describes when to use the CREATE STREAMING LIVE TABLE (formerly CREATE INCREMENTAL LIVE TABLE) syntax over the CREATE LIVE TABLE syntax when creating Delta Live Tables (DLT) tables using SQL?

A. CREATE STREAMING LIVE TABLE should be used when data needs to be processed through complicated aggregations.
B. CREATE STREAMING LIVE TABLE is redundant for DLT and it does not need to be used.
C. CREATE STREAMING LIVE TABLE should be used when the previous step in the DLT pipeline is static.
D. CREATE STREAMING LIVE TABLE should be used when data needs to be processed incrementally.
E. CREATE STREAMING LIVE TABLE should be used when the subsequent step in the DLT pipeline is static.

정답：D

질문 # 25
Which of the following describes a scenario in which a data engineer will want to use a single-node cluster?

A. When they are working interactively with a small amount of data
B. When they are manually running reports with a large amount of data
C. When they are working with SQL within Databricks SQL
D. When they are running automated reports to be refreshed as quickly as possible
E. When they are concerned about the ability to automatically scale with larger data

정답：A

설명：
Explanation
A Single Node cluster is a cluster consisting of an Apache Spark driver and no Spark workers. A Single Node cluster supports Spark jobs and all Spark data sources, including Delta Lake. A Standard cluster requires a minimum of one Spark worker to run Spark jobs.

질문 # 26
In order for Structured Streaming to reliably track the exact progress of the processing so that it can handle any kind of failure by restarting and/or reprocessing, which of the following two approaches is used by Spark to record the offset range of the data being processed in each trigger?

A. Structured Streaming cannot record the offset range of the data being processed in each trigger.
B. Replayable Sources and Idempotent Sinks
C. Checkpointing and Idempotent Sinks
D. Checkpointing and Write-ahead Logs
E. Write-ahead Logs and Idempotent Sinks

정답：D

설명：
Explanation
The engine uses checkpointing and write-ahead logs to record the offset range of the data being processed in each trigger. -- in the link search for "The engine uses " youll find the answer.https://spark.apache.org/docs/latest/structured-streaming-programming-guide.html#:~:text=The%20engin

질문 # 27
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Databricks-Certified-Data-Engineer-Associate최신 시험 최신 덤프자료: https://www.itcertkr.com/Databricks-Certified-Data-Engineer-Associate_exam.html

참고: Itcertkr에서 Google Drive로 공유하는 무료 2025 Databricks Databricks-Certified-Data-Engineer-Associate 시험 문제집이 있습니다: https://drive.google.com/open?id=1LmXgobwgdab2Z7CSgtjpD3tE4b09EUwH

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시험준비에가장좋은Databricks-Certified-Data-Engineer-Associate시험대비최신버전덤프최신버전덤프데모문제

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