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Confluent CCDAK Exam Syllabus Topics:

Section	Objectives
Topic 1: Kafka Ecosystem and Confluent Platform	- Schema Registry 1. Avro, Protobuf, JSON Schema usage - ksqlDB and connectors 1. Kafka Connect basics 2. Stream querying concepts
Topic 2: Kafka Streams and Processing	- Event processing patterns 1. Exactly-once semantics 2. Windowing and aggregation - Kafka Streams API 1. Stateful vs stateless processing 2. Stream processing fundamentals
Topic 3: Kafka Fundamentals	- Kafka architecture and core concepts 1. Brokers, topics, partitions 2. Replication and fault tolerance - Data flow in Kafka 1. Offset management 2. Producer and consumer model
Topic 4: Kafka Producers and Consumers	- Producer API 1. Reliability and acknowledgments 2. Serialization and partitioning strategies - Consumer API 1. Consumer groups 2. Rebalancing and offset commits

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q72-Q77):

NEW QUESTION # 72
I am producing Avro data on my Kafka cluster that is integrated with the Confluent Schema Registry. After a schema change that is incompatible, I know my data will be rejected. Which component will reject the data?

A. The Kafka Broker
B. The Confluent Schema Registry
C. The Kafka Producer itself
D. Zookeeper

Answer: B

Explanation:
The Confluent Schema Registry is your safeguard against incompatible schema changes and will be the component that ensures no breaking schema evolution will be possible. Kafka Brokers do not look at your payload and your payload schema, and therefore will not reject data

NEW QUESTION # 73
Which KSQL queries write to Kafka?

A. COUNT and JOIN
B. SHOW STREAMS and EXPLAIN <query> statements
C. CREATE STREAM AS SELECT and CREATE TABLE AS SELECT
D. CREATE STREAM WITH <topic> and CREATE TABLE WITH <topic>

Answer: C,D

Explanation:
SHOW STREAMS and EXPLAIN <query> statements run against the KSQL server that the KSQL client is connected to. They don't communicate directly with Kafka. CREATE STREAM WITH <topic> and CREATE TABLE WITH <topic> write metadata to the KSQL command topic. Persistent queries based on CREATE STREAM AS SELECT and CREATE TABLE AS SELECT read and write to Kafka topics.
Non-persistent queries based on SELECT that are stateless only read from Kafka topics, for example:
SELECT A FROM foo WHERE A;
Non-persistent queries that are stateful read and write to Kafka, for example, COUNT and JOIN. The data in Kafka is deleted automatically when you terminate the query with CTRL-C.

NEW QUESTION # 74
What is the risk of increasing max.in.flight.requests.per.connection while also enabling retries in a producer?

A. Message order not preserved
B. Less resilient
C. Reduce throughput
D. At least once delivery is not guaranteed

Answer: A

Explanation:
Some messages may require multiple retries. If there are more than 1 requests in flight, it may result in messages received out of order. Note an exception to this rule is if you enable the producer settingenable.idempotence=true which takes care of the out of ordering case on its own. Seehttps://issues.apache.org/jira/browse/KAFKA-5494

NEW QUESTION # 75
is KSQL ANSI SQL compliant?

A. Yes
B. No

Answer: B

Explanation:
KSQL is not ANSI SQL compliant, for now there are no defined standards on streaming SQL languages

NEW QUESTION # 76
A producer just sent a message to the leader broker for a topic partition. The producer used acks=1 and therefore the data has not yet been replicated to followers. Under which conditions will the consumer see the message?

A. When the message has been fully replicated to all replicas
B. When the high watermark has advanced
C. Never, the produce request will fail
D. Right away

Answer: B

Explanation:
The high watermark is an advanced Kafka concept, and is advanced once all the ISR replicates the latest offsets. A consumer can only read up to the value of the High Watermark (which can be less than the highest offset, in the case of acks=1)

NEW QUESTION # 77
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