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Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version) : Databricks-Certified-Professional-Data-Engineer Korean
- 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
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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:
레이크하우스 데이터베이스에 있는 customer_churn_params라는 테이블은 머신러닝 팀에서 고객 이탈 예측에 사용됩니다. 이 테이블에는 여러 상위 소스에서 가져온 고객 정보가 포함되어 있습니다. 현재 데이터 엔지니어링 팀은 상위 데이터 소스에서 가져온 최신 유효한 값으로 테이블을 덮어쓰는 방식으로 매일 밤 이 테이블을 업데이트하고 있습니다.
머신러닝 팀에서 사용하는 이탈 예측 모델은 실제 운영 환경에서 상당히 안정적입니다. 해당 팀은 지난 24시간 동안 변경된 기록에 대해서만 예측을 수행하는 데 관심이 있습니다.
어떤 접근 방식이 이러한 변경된 기록을 식별하는 것을 단순화할까요?
- A. 배치 작업을 전체 출력 모드를 사용하는 구조화된 스트리밍 작업으로 변환하고, 구조화된 스트리밍 작업이 customer_churn_params 테이블에서 데이터를 읽어 이탈 모델을 기반으로 점진적으로 예측하도록 구성합니다.
- B. 현재의 덮어쓰기 로직을 변경된 레코드만 수정하는 병합문으로 대체하고, 변경 데이터 피드를 통해 식별된 변경된 레코드에 대한 예측 로직을 작성합니다.
- C. customer_churn_params 테이블의 모든 행에 이탈 예측 모델을 적용하되, 예측값이 변경되지 않은 행은 무시하고 예측 테이블에 업서트하는 로직을 구현하십시오.
- D. 새로운 예측을 하기 전에 고유 고객을 식별하는 키를 기준으로 이전 모델 예측과 현재 고객 이탈 매개변수 간의 차이를 계산합니다. 이전 예측에 포함되지 않은 고객에 대해서만 예측을 수행합니다.
- E. spark.sql.functions 호출을 통해 채워진 필드를 포함하도록 덮어쓰기 로직을 수정합니다.
current_timestamp()는 데이터가 기록되는 동안 생성됩니다. 이 필드를 사용하여 특정 날짜에 기록된 레코드를 식별할 수 있습니다.
Correct Answer: B 🗳️
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데이터 거버넌스 팀은 GDPR 준수를 위해 레코드 삭제에 사용되는 코드를 검토하고 있습니다. 그들은 Delta Lake의 users라는 테이블에서 레코드를 삭제하는 데 다음과 같은 로직이 사용된다는 것을 확인했습니다.
user_id가 고유 식별 키이고 delete_requests에 삭제를 요청한 모든 사용자가 포함되어 있다고 가정할 때, 위의 로직을 성공적으로 실행하면 삭제될 레코드에 더 이상 접근할 수 없다는 것이 보장되는지 여부를 설명하는 문장은 무엇이며, 그 이유는 무엇입니까?
- A. 아니요. Delta Lake의 삭제 명령은 병합 명령과 함께 사용할 때만 ACID 보장을 제공합니다.
- B. 예; Delta Lake의 ACID 보장은 삭제 명령이 완전히 성공적으로 완료되어 해당 레코드가 영구적으로 삭제되었음을 보장합니다.
- C. 아니요. 델타 캐시는 클러스터가 재시작될 때까지 테이블의 이전 버전에서 가져온 레코드를 반환할 수 있습니다.
- D. 예; 델타 캐시는 디스크에 기록된 최신 데이터 파일을 반영하여 즉시 업데이트됩니다.
- E. 아니요; 삭제된 레코드가 포함된 파일은 vacuum 명령을 사용하여 무효화된 데이터 파일을 제거하기 전까지는 타임 트래블을 통해 계속 접근할 수 있습니다.
Correct Answer: E 🗳️
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데이터 엔지니어가 Databricks의 Lakeflow Declarative Pipelines(LDP)를 사용하여 고객 데이터를 수집하는 간단한 데이터 파이프라인을 구축하고 있습니다. 원시 고객 데이터는 클라우드 스토리지에 JSON 형식으로 저장되어 있습니다. 이 작업은 원시 JSON 데이터를 읽어 추가 처리를 위해 Delta 테이블에 쓰는 Lakeflow Declarative Pipelines를 생성하는 것입니다.
어떤 코드 조각이 원시 JSON 데이터를 올바르게 가져와 LDP를 사용하여 델타 테이블을 생성합니까?
- A. import dlt
@dlt.table
def raw_customers():
return spark.read.format( " parquet " ).load( " s3://my-bucket/raw-customers/ " ) - B. import dlt
@dlt.table
def raw_customers():
return spark.read.format( " csv " ).load( " s3://my-bucket/raw-customers/ " ) - C. import dlt
@dlt.table
def raw_customers():
return spark.read.json( " s3://my-bucket/raw-customers/ " ) - D. import dlt
@dlt.view
def raw_customers():
return spark.format.json( " s3://my-bucket/raw-customers/ " )
Correct Answer: C 🗳️
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데이터 엔지니어링 팀은 자동화된 ETL 프로세스의 일부로 테이블에 태깅 시스템을 구현해야 하며, Unity Catalog의 테이블에 프로그래밍 방식으로 태그를 적용해야 합니다.
테이블에 태그를 프로그래밍 방식으로 추가하는 SQL 명령은 무엇입니까?
- A. SET TAGS FOR table_name AS ( ' key1 ' = ' value1 ' , ' key2 ' = ' value2 ' );
- B. COMMENT ON TABLE table_name TAGS ( ' key1 ' = ' value1 ' , ' key2 ' = ' value2 ' );
- C. APPLY TAGS ON table_name VALUES ( ' key1 ' = ' value1 ' , ' key2 ' = ' value2 ' );
- D. ALTER TABLE table_name SET TAGS ( ' key1 ' = ' value1 ' , ' key2 ' = ' value2 ' );
Correct Answer: D 🗳️
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머신러닝 팀은 델타 레이크 레이크의 레이크하우스에 있는 customer_parsams라는 테이블을 고객 이탈 예측에 사용합니다. 이 테이블에는 여러 상위 소스에서 가져온 고객 정보가 포함되어 있습니다.
현재 데이터 엔지니어링 팀은 상위 데이터 소스에서 가져온 최신 유효 값으로 테이블을 덮어쓰는 방식으로 매일 밤 이 테이블을 업데이트합니다.
데이터 엔지니어 팀은 업데이트가 완료되는 즉시 새 버전과 이전 버전 간의 차이점을 확인하고자 합니다.
현재 구현 방식을 고려할 때, 어떤 방법을 사용할 수 있을까요?
- A. DESCRIBE HISTORY customer_churn_params 명령을 실행하여 추가되거나 수정된 모든 레코드의 로그를 포함하여 업데이트에 대한 전체 작업 메트릭을 얻으십시오.
- B. Spark 이벤트 로그를 분석하여 업데이트, 삽입 또는 삭제된 행을 식별합니다.
- C. Delta Lake 트랜잭션 로그를 분석하여 새로 기록된 모든 데이터 파일을 식별합니다.
- D. Delta Lake의 내장 버전 관리 및 타임 트래블 기능을 사용하여 새 버전과 이전 버전 간의 차이를 계산하는 쿼리를 실행합니다.
Correct Answer: D 🗳️
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