그 외, Pass4Test CCDAK 시험 문제집 일부가 지금은 무료입니다: https://drive.google.com/open?id=1KtNhnIZX-Y_apMG8ThrRFWJP7R-8qUd_
Pass4Test는 유일하게 여러분이 원하는Confluent인증CCDAK시험관련자료를 해결해드릴 수 잇는 사이트입니다. 여러분이 다른 사이트에서도 관련덤프자료를 보셨을경우 페이지 아래를 보면 자료출처는 당연히 Pass4Test 일 것입니다. Pass4Test의 자료만의 제일 전면적이고 또 최신 업데이트일 것입니다.
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Security | 5-10% | - Authentication (SASL, SSL/TLS) - Encryption in Transit - Securing Schema Registry - Authorization (ACLs) |
| Topic 2: Schema Management | 5-10% | - Schema Registration and Retrieval - Schema Registry Architecture - Schema Evolution and Compatibility - Avro Schemas - Protobuf and JSON Schemas |
| Topic 3: Kafka Streams | 20-25% | - State Stores and Processors - Streams Architecture and Topology - Transformation Operations (map, filter, join, aggregate) - Testing Kafka Streams Applications - Windowed Operations (Tumbling, Hopping, Session) - Interactive Queries - Exactly-Once Processing |
| Topic 4: Kafka Fundamentals | 10-15% | - Log Segments and Retention - Producer and Consumer Basics - Topics, Partitions, and Offsets - Brokers and Clusters - Replication Factor and ISR |
| Topic 5: Developing with Kafka Producers | 15-20% | - Producer Interceptors - Partitioning Strategies - Exactly-Once Semantics - Error Handling and Retry Logic - Producer Configuration and Tuning - Idempotent Producers - Serialization (JSON, Avro, Protobuf) |
| Topic 6: Kafka Connect | 10-15% | - Single Message Transformations (SMT) - Connector Configuration - Connect Architecture (Workers, Connectors, Tasks) - Source and Sink Connectors - Converters and Transforms - Offset Management in Connect |
| Topic 7: Installing and Configuring Kafka | 5-10% | - Partition Assignment Strategies - Broker Configuration Parameters - ZooKeeper vs KRaft Mode - Topic Creation and Configuration |
| Topic 8: Monitoring and Operations | 5-10% | - Consumer Lag and Health Checks - Log Compaction - Kafka Metrics and Monitoring - Disaster Recovery - Cross-region Replication |
| Topic 9: Developing with Kafka Consumers | 15-20% | - Consumer Groups and Rebalancing - Offset Management - Consumer Interceptors - Consumer Configuration and Tuning - Commit Strategies (Auto, Manual, Cooperative) - Multi-threaded Consumers - Deserialization |
연구결과에 의하면Confluent인증 CCDAK시험은 너무 어려워 시험패스율이 낮다고 합니다. Pass4Test의 Confluent인증 CCDAK덤프와 만나면Confluent인증 CCDAK시험에 두려움을 느끼지 않으셔도 됩니다. Pass4Test의 Confluent인증 CCDAK덤프는 엘리트한 IT전문가들이 실제시험을 연구하여 정리해둔 퍼펙트한 시험대비 공부자료입니다. 저희 덤프만 공부하시면 시간도 절약하고 가격도 친근하며 시험준비로 인한 여러방면의 스트레스를 적게 받아Confluent인증 CCDAK시험패스가 한결 쉬워집니다.
질문 # 29
(Which configuration determines the maximum number of records a consumer can poll in a single call to poll()?)
정답：B
설명：
The Apache Kafka consumer configuration max.poll.records explicitly controls the maximum number of records returned in a single call to Consumer.poll(). This is clearly documented in the official Kafka consumer configuration reference. It allows developers to limit the size of the batch returned to the application, helping to control processing latency, memory usage, and CPU load.
This setting does not affect how much data the broker sends to the consumer; instead, it limits how many records the consumer returns to the application layer from the fetched data. This makes it especially useful for applications where processing each record is expensive and needs predictable batch sizes.
Option B (max.records.consumer) does not exist in Kafka. Option C (fetch.max.records) is also invalid; Kafka uses fetch.max.bytes and related byte-based configurations, not record-count limits, at the fetch level. Option D (max.poll.records.interval) is not a valid Kafka configuration; the correct related setting is max.poll.interval.
ms, which controls liveness, not batch size.
Thus, max.poll.records is the correct and officially documented configuration.
질문 # 30
You want to perform table lookups against a KTable everytime a new record is received from the KStream.
What is the output of KStream-KTable join?
정답：B
설명：
Here KStream is being processed to create another KStream.
질문 # 31
A bank uses a Kafka cluster for credit card payments. What should be the value of the property unclean.leader.election.enable?
정답：A
설명：
Setting unclean.leader.election.enable to true means we allow out-of-sync replicas to become leaders, we will lose messages when this occurs, effectively losing credit card payments and making our customers very angry.
질문 # 32
You are working on a Kafka cluster with three nodes. You create a topic named orders with:
* replication.factor = 3
* min.insync.replicas = 2
* acks = allWhat exception will be generated if two brokers are down due to network delay?
정답：B
설명：
With acks=all and min.insync.replicas=2, Kafka requiresat least two in-sync replicasto acknowledge a write.
If onlyone broker is alive, the condition fails, andNotEnoughReplicasExceptionis thrown by the producer.
FromKafka Producer Exception Docs:
"NotEnoughReplicasException is thrown when the number of in-sync replicas is insufficient to satisfy acks=all with min.insync.replicas."
* NetworkException is generic and not raised here.
* NotCoordinatorException is related to consumer group coordination.
* NotLeaderForPartitionException is unrelated unless accessing an unassigned leader.
Reference:Kafka Producer Error Handling
질문 # 33
(Your application consumes from a topic configured with a deserializer.
You want the application to be resilient to badly formatted records (poison pills).
You surround the poll() call with a try/catch block for RecordDeserializationException.
You need to log the bad record, skip it, and continue processing other records.
Which action should you take in the catch block?)
정답：A
설명：
The Apache Kafka consumer documentation explains that when a RecordDeserializationException occurs, the consumer cannot continue polling until the problematic offset is skipped. Simply logging the error is insufficient, because the consumer will repeatedly fail on the same record.
The recommended pattern is to log the malformed record, extract its topic, partition, and offset from the exception, and then call consumer.seek() to move the consumer position to the next offset (offset + 1). This allows the application to skip the poison pill and resume processing subsequent records.
Option B is invalid because Kafka does not provide a consumer.skip() API. Option C is unnecessary if the application is designed to tolerate malformed records. Option D results in an infinite failure loop.
Therefore, seeking past the bad record after logging it is the correct and officially documented way to handle poison pill records while maintaining consumer liveness and resilience.
질문 # 34
......
CCDAK는Confluent의 인증시험입니다.CCDAK인증시험을 패스하면Confluent인증과 한 발작 더 내디딘 것입니다. 때문에CCDAK시험의 인기는 날마다 더해갑니다.CCDAK시험에 응시하는 분들도 날마다 더 많아지고 있습니다. 하지만CCDAK시험의 통과 율은 아주 낮습니다.CCDAK인증시험준비중인 여러분은 어떤 자료를 준비하였나요?
CCDAK덤프데모문제 다운: https://www.pass4test.net/CCDAK.html
Pass4Test CCDAK 최신 PDF 버전 시험 문제집을 무료로 Google Drive에서 다운로드하세요: https://drive.google.com/open?id=1KtNhnIZX-Y_apMG8ThrRFWJP7R-8qUd_