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| Certification Vendor: | Confluent |
|---|---|
| Exam Name: | Confluent Certified Developer for Apache Kafka Certification Examination |
| Exam Number: | CCDAK |
| Available Languages: | English |
| Real Exam Qty: | 60 |
| Exam Duration: | 90 minutes |
| Exam Format: | Multiple Choice (Multiple Answers), Multiple Choice (Single Answer) |
| Passing Score: | Approximately 60% |
| Related Certifications: | Confluent Certified Administrator for Apache Kafka (CCAAK) |
| Exam Price: | $150 USD |
| Certificate Validity Period: | 3 years |
| Sample Questions: | Confluent CCDAK Sample Questions |
| Exam Way: | Online proctored exam (Pearson VUE) or in-person testing center |
| Pre Condition: | Recommended: 6+ months of hands-on experience with Apache Kafka and Confluent Platform. Familiarity with distributed systems concepts is strongly recommended. |
| Official Syllabus URL: | https://www.confluent.io/certification/ |
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The CCDAK exam covers a wide range of topics, including Kafka architecture and components, data modeling and serialization, producer and consumer APIs, Kafka Connect, Kafka Streams, and security. CCDAK exam consists of 60 multiple-choice questions and must be completed within two hours. Candidates who pass the exam will receive a Confluent Certified Developer for Apache Kafka certificate, which is valid for two years. The CCDAK Certification is a rigorous exam that requires a deep understanding of Kafka's architecture and APIs, and passing it is a significant achievement for any developer.
NEW QUESTION # 27
This schema excerpt is an example of which schema format?
package com.mycorp.mynamespace;
message SampleRecord {
int32 Stock = 1;
double Price = 2;
string Product_Name = 3;
}
Answer: B
Explanation:
This syntax is a clear match to Protocol Buffers (Protobuf). It defines a schema with fields, types, and tags, which is a format supported by Kafka when using Protobuf-based schema registry serialization.
From Confluent Schema Registry Docs:
"Kafka supports Protobuf serialization, where schemas are written in .proto files and include fields with tags." int32, double, and string are standard Protobuf types.
Avro uses JSON-style schema.
JSON Schema uses JSON object structure, not .proto.
YAML is unrelated.
Reference: Confluent Schema Registry for Protobuf
NEW QUESTION # 28
(You create a topic with five partitions.
What can you assume about messages read from that topic by a single consumer group?)
Answer: B
Explanation:
The Apache Kafka documentation explains that Kafka's parallelism model is based on topic partitions and consumer groups. Within a single consumer group, each partition can be assigned to at most one consumer at a time. As a result, the maximum level of parallelism for a consumer group is equal to the number of partitions in the topic.
In this scenario, the topic has five partitions, which means that up to five consumers in the same consumer group can actively consume data in parallel. If more than five consumers are added, the extra consumers will remain idle because there are no additional partitions to assign.
Option B is incorrect because Kafka does not enforce equal message consumption across partitions; message distribution depends on producers and partitioning strategy. Option C is false because partitions may be hosted on different brokers, and consumers fetch data from multiple brokers. Option D is incorrect because a single partition cannot be consumed by multiple consumers within the same group simultaneously.
Therefore, the only valid assumption is that a maximum of five consumers can actively consume messages in the same consumer group.
NEW QUESTION # 29
Which configuration determines how many bytes of data are collected before sending messages to the Kafka broker?
Answer: C
Explanation:
The batch.size config sets the maximum number of bytes to batch per partition before sending. This allows Kafka producers to amortize I/O and improve throughput.
From Kafka Producer Configuration Docs:
"batch.size is the maximum amount of data per partition the producer will batch before sending." buffer.memory sets total memory for the producer, not per-batch.
send.buffer.bytes is a TCP socket buffer, not a Kafka config.
max.block.ms controls blocking time, not size.
Reference: Kafka Producer Configs > batch.size
NEW QUESTION # 30
What is true about replicas ?
Answer: B
Explanation:
Replicas are passive - they don't handle produce or consume request. Produce and consume requests get sent to the node hosting partition leader.
NEW QUESTION # 31
You need to configure a sink connector to write records that fail into a dead letter queue topic.
Requirements:
* Topic name: DLQ-Topic
* Headers containing error context must be added to the messagesWhich three configuration parameters are necessary?(Select three.)
Answer: A,C,E
Explanation:
To send failed records to adead letter queue (DLQ), you must configure:
* errors.tolerance=all: Tells the connector tonot failon errors but handle them (e.g., send to DLQ).
* errors.deadletterqueue.topic.name=DLQ-Topic: Specifies the DLQ topic.
* errors.deadletterqueue.context.headers.enable=true: Includes error context in message headers.
FromKafka Connect Error Handling Docs:
"Kafka Connect supports directing problematic records to a separate topic (DLQ) using errors.* configs.
Headers can include failure metadata."
Options D, E, F are related tologging, not DLQ behavior.
Reference:Kafka Connect Configurations > Error Handling
NEW QUESTION # 32
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