2026 PassTIP 최신 CCDAK PDF 버전 시험 문제집과 CCDAK 시험 문제 및 답변 무료 공유: https://drive.google.com/open?id=1zB1ffPrPbILbgjPe78AycMWJza5t039o
IT업계에 종사하시는 분은 국제공인 IT인증자격증 취득이 얼마나 힘든지 알고 계실것입니다. 특히 시험이 영어로 되어있어 부담을 느끼시는 분도 계시는데 PassTIP를 알게 된 이상 이런 고민은 버리셔도 됩니다. PassTIP의Confluent CCDAK덤프는 모두 영어버전으로 되어있어Confluent CCDAK시험의 가장 최근 기출문제를 분석하여 정답까지 작성해두었기에 문제와 답만 외우시면 시험합격가능합니다.
| Certification Vendor: | Confluent |
|---|---|
| Exam Name: | Confluent Certified Developer for Apache Kafka (CCDAK) Certification Exam |
| Exam Number: | CCDAK |
| Available Languages: | English |
| Certificate Validity Period: | 3 years |
| Exam Price: | $150 USD |
| Related Certifications: | Confluent Certified Developer for Apache Kafka (CCDAK) Confluent Certified Administrator for Apache Kafka (CCAK) |
| Exam Duration: | 90 minutes |
| Exam Format: | Multiple choice, Multiple select |
| Real Exam Qty: | 60 |
| Passing Score: | 70% |
| Recommended Training: | Apache Kafka Developer Training (Confluent) Kafka Fundamentals Course |
| Exam Registration: | Confluent Training and Exams Confluent Certification Portal |
| Sample Questions: | Confluent CCDAK Sample Questions |
| Exam Way: | Online proctored exam or authorized testing center |
| Pre Condition: | Basic understanding of Java or another JVM language and familiarity with distributed systems concepts is recommended. |
| Official Syllabus URL: | https://www.confluent.io/certification/ |
PassTIP 에서 제공해드리는 Confluent인증CCDAK시험덤프자료를 구입하시면 퍼펙트한 구매후 서비스를 약속드립니다. PassTIP에서 제공해드리는 덤프는 IT업계 유명인사들이 자신들의 노하우와 경험을 토대로 하여 실제 출제되는 시험문제를 연구하여 제작한 최고품질의 덤프자료입니다. Confluent인증CCDAK시험은PassTIP 표Confluent인증CCDAK덤프자료로 시험준비를 하시면 시험패스는 아주 간단하게 할수 있습니다. 구매하기전 PDF버전 무료샘플을 다운받아 공부하세요.
Apache Kafka (CCDAK) 인증 시험의 합류 인증 개발자는 Apache Kafka의 능력을 보여 주려는 개발자를 위해 설계되었습니다. 인증 시험은 Apache Kafka의 제작자 인 Confulation이 제공하며 미션 크리티컬 Kafka 응용 프로그램을 구축하는 데 필요한 지식과 기술을 테스트하도록 설계되었습니다. 시험은 Kafka 아키텍처, 구성, 개발 및 운영을 포함한 다양한 주제를 다룹니다.
질문 # 67
A stream processing application is consuming from a topic with five partitions. You run three instances of the application. Each instance has num.stream.threads=5.
You need to identify the number of stream tasks that will be created and how many will actively consume messages from the input topic.
정답：A
설명：
In Kafka Streams,the number of stream tasks = number of input partitions × num.stream.threads × number of instances,but only as many as the number of partitions can actively consume at once.
However, in this case,Kafka Streams assigns one task per partition, and because there are 5 partitions and
15 threads (3 instances × 5 threads),15 tasks are created, andall 15 can be activedepending on processing topology.
FromKafka Streams Developer Guide:
"Kafka Streams creates one task per input partition. If you increase the number of stream threads, it runs multiple tasks in parallel within a single instance." So,15 stream tasks will be created and 15 will be actively consuming.
Reference:Apache Kafka Streams Documentation > Concepts > Tasks and Threads
질문 # 68
How will you read all the messages from a topic in your KSQL query?
정답：A
설명：
Consumers can set auto.offset.reset property to earliest to start consuming from beginning. For KSQL, SET 'auto.offset.reset'='earliest';
질문 # 69
How does a consumer commit offsets in Kafka?
정답：C
설명：
Consumers do not directly write to the __consumer_offsets topic, they instead interact with a broker that has been elected to manage that topic, which is the Group Coordinator broker
질문 # 70
(A consumer application needs to use an at-most-once delivery semantic.
What is the best consumer configuration and code skeleton to avoid duplicate messages being read?)
정답：C
설명：
According to the official Apache Kafka consumer semantics documentation, at-most-once delivery means that records may be lost but must never be processed more than once. To achieve this guarantee, a consumer must commit offsets before processing records. If the application crashes after committing but before processing, messages are skipped rather than reprocessed, which satisfies at-most-once semantics.
Option B correctly implements this pattern. It disables automatic offset commits (enable.auto.commit=false) and explicitly calls commitAsync() immediately after polling and before processing records. This ensures that offsets are advanced regardless of whether processing succeeds, eliminating the possibility of duplicate processing.
Option C represents at-least-once semantics, because offsets are committed after processing, which can lead to duplicates on failure. Options A and D rely on automatic commits or incorrect ordering and do not provide strict at-most-once guarantees.
The Kafka documentation explicitly states that manual offset management with commits before processing is required for at-most-once delivery.
Therefore, Option B is the best and officially documented configuration and code skeleton to avoid duplicate message processing.
질문 # 71
A consumer application runs once a week and reads from a Kafka topic. The last time the application ran, the last offset processed was 217. The application is configured with auto.offset.reset set to "latest". The current offsets in the topic start at 318 and end at 588.
What offset will the application start reading when it starts up for its next run?
정답：B
질문 # 72
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CCDAK유효한 덤프공부: https://www.passtip.net/CCDAK-pass-exam.html
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