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Confluent CCDAK Exam Syllabus Topics:

Section	Weight	Objectives
Kafka Connect	10-15%	- Offset Management in Connect - Converters and Transforms - Connect Architecture (Workers, Connectors, Tasks) - Connector Configuration - Source and Sink Connectors - Single Message Transformations (SMT)
Kafka Fundamentals	10-15%	- Producer and Consumer Basics - Replication Factor and ISR - Brokers and Clusters - Log Segments and Retention - Topics, Partitions, and Offsets
Developing with Kafka Consumers	15-20%	- Consumer Interceptors - Consumer Groups and Rebalancing - Commit Strategies (Auto, Manual, Cooperative) - Offset Management - Multi-threaded Consumers - Deserialization - Consumer Configuration and Tuning
Schema Management	5-10%	- Schema Registry Architecture - Protobuf and JSON Schemas - Schema Evolution and Compatibility - Schema Registration and Retrieval - Avro Schemas
Developing with Kafka Producers	15-20%	- Idempotent Producers - Partitioning Strategies - Error Handling and Retry Logic - Producer Interceptors - Producer Configuration and Tuning - Exactly-Once Semantics - Serialization (JSON, Avro, Protobuf)
Security	5-10%	- Authentication (SASL, SSL/TLS) - Securing Schema Registry - Encryption in Transit - Authorization (ACLs)
Kafka Streams	20-25%	- Windowed Operations (Tumbling, Hopping, Session) - Interactive Queries - State Stores and Processors - Exactly-Once Processing - Testing Kafka Streams Applications - Streams Architecture and Topology - Transformation Operations (map, filter, join, aggregate)
Installing and Configuring Kafka	5-10%	- Broker Configuration Parameters - ZooKeeper vs KRaft Mode - Topic Creation and Configuration - Partition Assignment Strategies
Monitoring and Operations	5-10%	- Log Compaction - Disaster Recovery - Consumer Lag and Health Checks - Kafka Metrics and Monitoring - Cross-region Replication

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q80-Q85):

NEW QUESTION # 80
A producer is configured with the default partitioner. It is sending records to a topic that is configured with five partitions. The record does not contain any key.
What is the result of this?

A. An error will be raised and no record will be sent.
B. Records will be sent to partition 0.
C. Records will be sent to the least used partition.
D. Records will be dispatched among the available partitions.

Answer: D

Explanation:
If a key isnot specified, thedefault Kafka partitioner uses round-robinlogic to assign partitions. This leads toeven distributionof messages across all partitions.
FromKafka Producer Design:
"If the key is null, the producer will assign the partition in a round-robin fashion to achieve load balancing." There isno error, and partition 0 isnot alwayschosen in this case.
Reference:Kafka Producer Partitioner Behavior - Official Docs

NEW QUESTION # 81
Your manager would like to have topic availability over consistency. Which setting do you need to change in order to enable that?

A. min.insync.replicas
B. unclean.leader.election.enable
C. compression.type

Answer: B

Explanation:
unclean.leader.election.enable=true allows non ISR replicas to become leader, ensuring availability but losing consistency as data loss will occur

NEW QUESTION # 82
What's is true about Kafka brokers and clients from version 0.10.2 onwards?

A. A newer client can talk to a newer broker, and an older client can talk to a newer broker
B. A newer client can talk to a newer broker, but an older client cannot talk to a newer broker
C. Clients and brokers must have the exact same version to be able to communicate
D. A newer client can't talk to a newer broker, but an older client can talk to a newer broker

Answer: A

Explanation:
Kafka's new bidirectional client compatibility introduced in 0.10.2 allows this. Read more herehttps://www.confluent.io/blog/upgrading-apache-kafka-clients-just-got-easier/

NEW QUESTION # 83
What are three built-in abstractions in the Kafka Streams DSL?
(Select three.)

A. KTable
B. GlobalKStream
C. KStream
D. GlobalKTable
E. StreamTable

Answer: A,C,D

Explanation:
The Kafka Streams DSL provides three primary abstractions:
KStream: Represents an unbounded stream of records (append-only).
KTable: Represents a changelog stream where each key has the latest value (like a materialized view).
GlobalKTable: A fully replicated version of KTable across all stream instances, enabling global joins.
From Kafka Streams Developer Guide:
"Kafka Streams provides three core abstractions: KStream, KTable, and GlobalKTable, each serving different purposes in stream processing and joins." GlobalKStream and StreamTable do not exist in Kafka's API.
Reference: Kafka Streams Concepts > KStream, KTable, GlobalKTable

NEW QUESTION # 84
A consumer starts and has auto.offset.reset=none, and the topic partition currently has data for offsets going from 45 to 2311. The consumer group has committed the offset 10 for the topic before. Where will the consumer read from?

A. offset 10
B. it will crash
C. offset 2311
D. offset 45

Answer: B

Explanation:
auto.offset.reset=none means that the consumer will crash if the offsets it's recovering from have been deleted from Kafka, which is the case here, as 10 < 45

NEW QUESTION # 85
......

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