- Exam Code: Databricks-Certified-Professional-Data-Engineer-KR
- Exam Name: Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version)
- Updated: Oct 14, 2026
- Q & A: 217 Questions and Answers
Databricks Databricks-Certified-Professional-Data-Engineer Korean Exam : Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version)
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Databricks Databricks-Certified-Professional-Data-Engineer Korean Exam Syllabus Topics:
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Reference: https://www.databricks.com/learn/certification/data-engineer-professional
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Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version) Sample Questions:
Question #1
거의 실시간에 가까운 워크로드를 처리하기 위해 데이터 엔지니어가 Databricks Auto Loader의 스키마 감지 및 진화 기능을 활용하는 헬퍼 함수를 개발하고 있습니다. 이 함수는 소스의 스키마를 자동으로 감지하고, 소스 디렉터리에 JSON 파일이 도착하는 즉시 점진적으로 처리하며, 새 필드가 감지되면 테이블의 스키마를 자동으로 진화시킵니다.
함수는 아래와 같이 공백으로 표시됩니다.
다음 보기 중 주어진 요건을 충족하는 빈칸에 맞는 정답은 무엇입니까?
- A. 옵션 A
- B. 옵션 B
- C. 옵션 C
- D. 옵션 E
- E. 옵션 D
Correct Answer: B 🗳️
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Question #2
데이터 엔지니어링 팀은 Databricks Lakehouse Monitoring을 사용하여 Delta 테이블의 핵심 열에 대한 percent_null 지표를 추적합니다.
프로필 메트릭 테이블(prod_catalog.prod_schema.customer_data_profile_metrics)에는 시간별 percent_null 값이 저장됩니다.
팀의 목표는 다음과 같습니다.
* percent_null의 일일 평균값이 3일 연속 5%를 초과할 경우 알림을 발생시킵니다.
* 문제가 지속되는 동안 알림이 스팸처럼 전송되지 않도록 하십시오.
옵션:
- A. WITH daily_avg AS (
SELECT DATE_TRUNC( ' DAY ' , window.end) AS day,
AVG(percent_null) AS avg_null
FROM prod_catalog.prod_schema.customer_data_profile_metrics
GROUP BY DATE_TRUNC( ' DAY ' , window.end)
)
SELECT day, avg_null
FROM daily_avg
ORDER BY day DESC
LIMIT 3
Alert Condition: ALL avg_null > 5 for the latest 3 rows
Notification Frequency: Just once - B. SELECT AVG(percent_null) AS daily_avg
FROM prod_catalog.prod_schema.customer_data_profile_metrics
WHERE window.end > = CURRENT_TIMESTAMP - INTERVAL ' 3 ' DAY
Alert Condition: daily_avg > 5
Notification Frequency: Each time alert is evaluated - C. SELECT SUM(CASE WHEN percent_null > 5 THEN 1 ELSE 0 END) AS violation_days FROM prod_catalog.prod_schema.customer_data_profile_metrics WHERE window.end > = CURRENT_TIMESTAMP - INTERVAL ' 3 ' DAY Alert Condition: violation_days > = 3 Notification Frequency: Just once
- D. SELECT percent_null
FROM prod_catalog.prod_schema.customer_data_profile_metrics
WHERE window.end > = CURRENT_TIMESTAMP - INTERVAL ' 1 ' DAY
Alert Condition: percent_null > 5
Notification Frequency: At most every 24 hours
Correct Answer: A 🗳️
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Question #3
신입 데이터 엔지니어가 silver_device_recordings라는 Lakehouse 테이블에 대한 로직을 구현하는 작업을 진행하고 있습니다.
원본 데이터는 고도로 중첩된 JSON 구조에 100개의 고유 필드를 포함하고 있습니다.
silver_device_recordings 테이블은 여러 프로덕션 모니터링 대시보드와 프로덕션 모델을 구동하는 데 사용될 예정입니다. 현재 100개 필드 중 45개가 이러한 애플리케이션 중 하나 이상에서 사용되고 있습니다.
데이터 엔지니어는 데이터의 고도로 중첩된 구조와 수많은 필드를 고려하여 스키마 선언을 처리하는 최적의 접근 방식을 찾으려고 노력하고 있습니다.
다음 중 Delta Lake와 Databricks에 대한 정보를 정확하게 제시하여 그들의 의사 결정 과정에 영향을 미칠 수 있는 것은 무엇입니까?
- A. Databricks에서 사용하는 Tungsten 인코딩은 문자열 데이터 저장에 최적화되어 있습니다. JSON 문자열 쿼리에 대한 새로운 네이티브 지원이 추가되어 문자열 유형이 항상 가장 효율적입니다.
- B. .Databricks의 스키마 추론 및 진화는 추론된 유형이 하위 시스템에서 사용되는 데이터 유형과 항상 정확하게 일치하도록 보장합니다.
- C. Databricks는 관찰된 모든 데이터를 처리할 수 있는 유형을 사용하여 스키마를 추론하므로 유형을 수동으로 설정하면 데이터 품질 보장을 강화할 수 있습니다.
- D. 데이터 엔지니어링 워크로드에서 가장 큰 비용은 코드 작성에 투입되는 인력입니다. 따라서 모든 마이그레이션 워크로드에서 테이블 선언 로직 자동화를 최우선 과제로 삼아야 합니다.
- E. Delta Lake는 데이터 저장에 Parquet 형식을 사용하기 때문에 파일 바닥글 정보만 수정하면 데이터 형식을 쉽게 변경할 수 있습니다.
Correct Answer: C 🗳️
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Question #4
아래의 각 구성은 클러스터당 총 400GB의 RAM, 총 160개의 코어, 그리고 VM당 하나의 Executor만 갖는다는 점에서 동일합니다.
하나 이상의 광범위한 변환이 포함된 작업이 주어졌을 때, 다음 클러스터 구성 중 어떤 구성이 최대 성능을 가져올까요?
- A. * Total VMs; 1
* 400 GB per Executor
* 160 Cores / Executor - B. * Total VMs: 8
* 50 GB per Executor
* 20 Cores / Executor - C. * Total VMs:2
* 200 GB per Executor
* 80 Cores / Executor - D. * Total VMs: 4
* 100 GB per Executor
* 40 Cores/Executor
Correct Answer: B 🗳️
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Question #5
데이터 엔지니어링 팀의 한 구성원이 더 큰 데이터 파이프라인의 일부로 실행되도록 예약하려는 간단한 노트북 파일을 제출했습니다. 아래 제공된 명령어를 제시된 대로 실행하면 논리적으로 올바른 결과가 생성된다고 가정합니다.
노트북을 작업으로 예약하기 전에 어떤 명령어를 제거해야 할까요?
- A. 명령 6
- B. 명령 3
- C. 명령 4
- D. 명령 2
- E. 명령 5
Correct Answer: A 🗳️
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