さらに、PassTest CCDAKダンプの一部が現在無料で提供されています：https://drive.google.com/open?id=1fSx5RHQdLcmeYkd9tq7VszKUJ7WqEPZ7
PassTestは、他の競合他社とは異なるWebサイトです。すべての受験者に貴重なCCDAK試験問題を提供し、CCDAK試験に合格するのが難しい人を支援することを目的としています。一部のWebサイトのような質の悪いCCDAK試験資料を提供しないだけでなく、一部のWebサイトと同じ高価格もありません。当社のウェブサイトからCCDAK学習問題集を試してみたい場合、それはあなたのお金のための最も効果的な投資でなければなりません。
| Certification Vendor: | Confluent |
|---|---|
| Exam Name: | Confluent Certified Developer for Apache Kafka Certification Examination |
| Exam Number: | CCDAK |
| Exam Duration: | 90 minutes |
| Exam Format: | Matching, Multiple-choice, List order |
| Related Certifications: | Confluent Cloud Certified Operator (CCAC) Confluent Certified Administrator for Apache Kafka (CCAAK) |
| Certificate Validity Period: | 2 years |
| Exam Price: | $150 USD |
| Passing Score: | Pass / Fail |
| Real Exam Qty: | 60 |
| Available Languages: | English |
| Recommended Training: | Confluent Documentation Confluent Developer Training for Apache Kafka |
| Exam Registration: | Confluent Certification Portal |
| Sample Questions: | Confluent CCDAK Sample Questions |
| Exam Way: | Remote proctored online exam; requires webcam, microphone, Google Chrome browser |
| Pre Condition: | No mandatory prerequisites; recommended experience: 6+ months developing applications with Apache Kafka |
| Official Syllabus URL: | https://www.confluent.io/certification/ |
あなたの分野で関連するCCDAK認定を取得することが、Confluentあなたの専門知識とスキルを示す最も強力な方法です。 ただし、大多数の受験者がCCDAK試験に合格するために準備するのは簡単ではありません。もしあなたが今試験を心配している受験者の一人であれば、おめでとうございます、あなたは私たちPassTestのCCDAK試験を受けることができます ツール。 CCDAK試験トレントのガイダンスで、あなたは試験に合格するだけでなく、関連するConfluent Certified Developer for Apache Kafka Certification Examination認定を簡単に取得できることを保証できます。
CCDAK認定を取得することは、Kafkaにおける専門知識を誇示し、業界での認知度を高めるための素晴らしい方法です。認定は2年間有効であり、維持するためには、試験を再受験するか、Confluentが提供するより高度な認定を取得する必要があります。
質問 # 11
When using plain JSON data with Connect, you see the following error messageorg.apache.kafka.connect.errors.DataExceptionJsonDeserializer with schemas.enable requires "schema" and "payload" fields and may not contain additional fields. How will you fix the error?
正解：B
解説：
You will need to set the schemas.enable parameters for the converter to false for plain text with no schema.
質問 # 12
You need to correctly join data from two Kafka topics.
Which two scenarios will allow for co-partitioning?
(Select two.)
正解：B、D
解説：
For Kafka Streams to performjoins, topics must beco-partitioned, meaning:
* They have thesame number of partitions(A), and
* They use thesame partitioning strategy(typically by key) (B)
FromKafka Streams Documentation > Joins:
"Co-partitioning is required for Kafka Streams joins. Topics must have the same number of partitions and use the same key-based partitioner." Value schema (C) and retention time (D) have no bearing on join compatibility.
Reference:Kafka Streams Concepts > Joins and Co-Partitioning
質問 # 13
Which SMTs is used to change the data type?
正解：A
質問 # 14
(You have a Kafka consumer in production actively reading from a critical topic from which multiple other applications are consuming.
You have a new requirement to update the offset of your consumer to start reading from the beginning of the topic.
Which action would you take?)
正解：B
解説：
The Apache Kafka documentation states that consumer offsets are stored per consumer group and must be explicitly reset if an application needs to reprocess data from an earlier position. The officially supported and safest way to reset offsets for an existing consumer group is by using the kafka-consumer-groups CLI tool with the --reset-offsets option and the --to-earliest flag.
Setting auto.offset.reset=earliest (Option D) only applies when no committed offset exists for a partition.
Since this consumer is already running in production, offsets are already committed, making this option ineffective. Option C does not change offsets because Kafka identifies consumers by group ID, not application instance. Option B is extremely dangerous and incorrect, as setting retention.ms=0 deletes data for all consumers and impacts other applications.
Therefore, using the CLI to reset offsets for the specific consumer group ensures controlled, auditable, and targeted offset management without affecting other consumers or the topic itself. This approach is explicitly documented in Kafka's consumer group administration tools.
質問 # 15
Your producer is producing at a very high rate and the batches are completely full each time. How can you improve the producer throughput? (select two)
正解：A、B
解説：
Increase linger.ms
Explanation:
batch.size controls how many bytes of data to collect before sending messages to the Kafka broker. Set this as high as possible, without exceeding available memory. Enabling compression can also help make more compact batches and increase the throughput of your producer. Linger.ms will have no effect as the batches are already full
質問 # 16
......
CCDAK日本語問題集: https://www.passtest.jp/Confluent/CCDAK-shiken.html
2026年PassTestの最新CCDAK PDFダンプおよびCCDAK試験エンジンの無料共有：https://drive.google.com/open?id=1fSx5RHQdLcmeYkd9tq7VszKUJ7WqEPZ7