Skip to main content
ITPrepCerts
Login
Exams Free Samples About Contact
Login Create an account

CCDAK Confluent Certified Developer for Apache Kafka

  • Confluent
  • 152 practice questions
  • Updated Sep 2026
  • 5 free sample questions

About this exam

CCDAK is the Confluent exam Confluent Certified Developer for Apache Kafka. Practice material is available as a PDF, an interactive practice test or a bundle of both.

Exam code
CCDAK
Vendor
Confluent
Practice questions
152
Questions with an explanation
150 of 152
Free sample questions
5
Question bank last updated
19 Sep 2026

Try 2 sample questions

Taken from the free sample set for CCDAK.

Question 1

(Which configuration determines the maximum number of records a consumer can poll in a single call to poll()?)

  1. Option A:

    max.poll.records

  2. Option B:

    max.records.consumer

  3. Option C:

    fetch.max.records

  4. Option D:

    max.poll.records.interval

Show answer and explanation

Correct answer: A

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.

Question 2 (choose 2)

You need to correctly join data from two Kafka topics.

Which two scenarios will allow for co-partitioning?

  1. Option A:

    Both topics have the same number of partitions.

  2. Option B:

    Both topics have the same key and partitioning strategy.

  3. Option C:

    Both topics have the same value schema

  4. Option D:

    Both topics have the same retention time.

Show answer and explanation

Correct answer: A, B

For Kafka Streams to perform joins, topics must be co-partitioned, meaning:

They have the same number of partitions (A), and

They use the same partitioning strategy (typically by key) (B)

From Kafka 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, ============, ]
See all 5 free sample questions