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Databricks Databricks-Certified-Professional-Data-Engineer Korean Exam Syllabus Topics:

TopicDetails
Topic 1
  • Testing & Deployment: It discusses adapting notebook dependencies to use Python file dependencies, leveraging Wheels for imports, repairing and rerunning failed jobs, creating jobs based on common use cases, designing systems to control cost and latency SLAs, configuring the Databricks CLI, and using the REST API to clone a job, trigger a run, and export the run output.
Topic 2
  • Data Processing: The topic covers understanding partition hints, partitioning data effectively, controlling part-file sizes, updating records, leveraging Structured Streaming and Delta Lake, implementing stream-static joins and deduplication. Additionally, it delves into utilizing Change Data Capture and addressing performance issues related to small files.
Topic 3
  • Monitoring & Logging: This topic includes understanding the Spark UI, inspecting event timelines and metrics, drawing conclusions from various UIs, designing systems to control cost and latency SLAs for production streaming jobs, and deploying and monitoring both streaming and batch jobs.
Topic 4
  • Databricks Tooling: The Databricks Tooling topic encompasses the various features and functionalities of Delta Lake. This includes understanding the transaction log, Optimistic Concurrency Control, Delta clone, indexing optimizations, and strategies for partitioning data for optimal performance in the Databricks SQL service.

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

Databricks Databricks-Certified-Professional-Data-Engineer Korean Exam Overview:

Certification Vendor:Databricks
Exam Name:Databricks Certified Professional Data Engineer Exam
Exam Number:Databricks-Certified-Professional-Data-Engineer
Certificate Validity Period:2 years
Related Certifications:Databricks Certified Data Analyst Associate
Databricks Certified Associate Developer
Real Exam Qty:60
Exam Price:$200 USD
Exam Format:Multiple Select, Multiple Choice
Exam Duration:90 minutes
Passing Score:70%
Available Languages:English
Sample Questions:Databricks Databricks-Certified-Professional-Data-Engineer Korean Sample Questions
Exam Way:Online proctored exam (Pearson VUE)
Pre Condition:Recommended: 6+ months of hands-on experience with Databricks and data engineering concepts; familiarity with Python or Scala and SQL is strongly recommended
Official Syllabus URL:https://www.databricks.com/learn/certification/professional-data-engineer

Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version) Sample Questions:

Question #1

Databricks를 처음 사용하는 사용자가 작업 중인 파이프라인 로직의 실행 시간이 너무 오래 걸리는 문제를 해결하려고 합니다. 현재 사용자는 display() 호출을 사용하여 코드를 셀 단위로 실행하면서 새로운 변환이 작업에 추가될 때 코드가 논리적으로 올바른 결과를 생성하는지 확인하고 있습니다. 평균 실행 시간을 측정하기 위해 각 셀을 대화형으로 여러 번 실행하고 있습니다.
다음 중 어떤 조정을 하면 실제 운영 환경에서 코드 성능을 더 정확하게 측정할 수 있을까요?

  • A. display()를 호출하면 작업이 강제로 트리거되지만, 많은 변환은 논리적 쿼리 계획에만 추가됩니다. 캐싱으로 인해 동일한 로직이 반복적으로 실행되면 의미 있는 결과를 얻을 수 없습니다.
  • B. 개발 노트북에서 코드 실행 시간을 의미 있게 문제 해결하는 유일한 방법은 프로덕션 규모의 데이터와 프로덕션 규모의 클러스터를 사용하여 "모두 실행" 모드로 실행하는 것입니다.
  • C. Scala는 인터랙티브 노트북을 사용하여 정확하게 테스트할 수 있는 유일한 언어입니다. Scala 코드를 JAR 파일로 컴파일하여 사용할 때 최상의 성능을 얻을 수 있기 때문입니다. 모든 PySpark 및 Spark SQL 로직은 리팩토링해야 합니다.
  • D. Photon은 예약된 작업을 위해 시작된 클러스터에서만 활성화할 수 있으므로, 증분 코드 개발 중에 노트북을 작업으로 실행하고 실행 시간을 추적하려면 Jobs UI를 활용해야 합니다.
  • E. 실제 운영 환경에서의 코드 개발은 반드시 IDE를 사용하여 수행해야 합니다. 오픈 소스 Spark 및 Delta Lake의 로컬 빌드 환경에서 코드를 실행하면 실제 운영 환경에서의 코드 성능을 가장 정확하게 예측할 수 있습니다.
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Correct Answer: A  🗳️

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Question #2

데이터 엔지니어가 늦게 도착하는 중복 레코드를 처리할 가능성이 있는 파이프라인을 구성하고 있습니다.
배치 내에서 레코드 중복을 제거하는 것 외에도, 다음 중 어떤 접근 방식을 사용하면 데이터 엔지니어가 델타 테이블에 데이터를 삽입할 때 이전에 처리된 레코드와 중복된 데이터를 제거할 수 있습니까?

  • A. delta.deduplicate = true로 설정을 지정하세요.
  • B. 고유 키를 기준으로 전체 외부 조인을 수행하고 기존 데이터를 덮어씁니다.
  • C. 중복 레코드를 방지하려면 Delta Lake 스키마 강제 적용 기능을 활용하세요.
  • D. 각 배치 작업이 완료된 후 델타 테이블을 진공 청소하십시오.
  • E. 고유 키를 기준으로 일치 조건을 사용하여 삽입 전용 병합을 수행합니다.
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Correct Answer: E  🗳️

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Question #3

DevOps 팀은 Jobs UI를 사용하여 매일 실행되도록 예약된 노트북 모음으로 프로덕션 워크로드를 구성했습니다. 새로 합류한 데이터 엔지니어가 프로덕션 로직을 검토하기 위해 이러한 노트북 중 하나에 대한 액세스 권한을 요청했습니다.
운영 중인 코드나 데이터가 실수로 변경되는 것을 방지하면서 사용자에게 부여할 수 있는 최대 노트북 권한은 얼마입니까?

  • A. 관리 가능
  • B. 편집 가능
  • C. 권한 없음
  • D. 실행 가능
  • E. 읽을 수 있음
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Correct Answer: E  🗳️

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Question #4

데이터 엔지니어링 팀이 배포 자동화를 설정하고 있습니다. Databricks CLI 명령어를 사용하여 워크스페이스 자산을 원격으로 배포하려면 적절한 인증 설정을 구성해야 합니다.
어떤 인증 방식이 가장 높은 수준의 보안을 제공할까요?

  • A. OAuth 토큰 연동을 사용하는 서비스 주체를 사용합니다.
  • B. 서비스 주체와 해당 개인 액세스 토큰을 사용합니다.
  • C. 공유 사용자 계정과 해당 OAuth 클라이언트 비밀 키를 사용합니다.
  • D. 서비스 주체 ID와 해당 OAuth 클라이언트 비밀 키를 사용합니다.
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Correct Answer: A  🗳️

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Question #5

필요한 모듈을 찾을 때 검색할 디렉터리 목록을 담고 있는 파이썬 변수는 무엇입니까?

  • A. importlib.resource 경로
  • B. pylib.source
  • C. ,sys.path
  • D. os-path
  • E. pypi.path
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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