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Confluent CCDAK Exam Syllabus Topics:

SectionWeightObjectives
Developing with Kafka Consumers15-20%- Commit Strategies (Auto, Manual, Cooperative)
- Consumer Groups and Rebalancing
- Consumer Interceptors
- Consumer Configuration and Tuning
- Multi-threaded Consumers
- Deserialization
- Offset Management
Installing and Configuring Kafka5-10%- Topic Creation and Configuration
- Broker Configuration Parameters
- Partition Assignment Strategies
- ZooKeeper vs KRaft Mode
Monitoring and Operations5-10%- Consumer Lag and Health Checks
- Kafka Metrics and Monitoring
- Disaster Recovery
- Cross-region Replication
- Log Compaction
Kafka Fundamentals10-15%- Log Segments and Retention
- Replication Factor and ISR
- Producer and Consumer Basics
- Brokers and Clusters
- Topics, Partitions, and Offsets
Schema Management5-10%- Avro Schemas
- Schema Registry Architecture
- Protobuf and JSON Schemas
- Schema Evolution and Compatibility
- Schema Registration and Retrieval
Security5-10%- Authentication (SASL, SSL/TLS)
- Authorization (ACLs)
- Encryption in Transit
- Securing Schema Registry
Kafka Streams20-25%- Testing Kafka Streams Applications
- Transformation Operations (map, filter, join, aggregate)
- Exactly-Once Processing
- Interactive Queries
- State Stores and Processors
- Streams Architecture and Topology
- Windowed Operations (Tumbling, Hopping, Session)
Kafka Connect10-15%- Single Message Transformations (SMT)
- Source and Sink Connectors
- Offset Management in Connect
- Connect Architecture (Workers, Connectors, Tasks)
- Converters and Transforms
- Connector Configuration
Developing with Kafka Producers15-20%- Producer Configuration and Tuning
- Producer Interceptors
- Error Handling and Retry Logic
- Serialization (JSON, Avro, Protobuf)
- Partitioning Strategies
- Idempotent Producers
- Exactly-Once Semantics

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q74-Q79):

NEW QUESTION # 74
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?

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 # 75
Match the topic configuration setting with the reason the setting affects topic durability.
(You are given settings like unclean.leader.election.enable=false, replication.factor, min.insync.replicas=2)

Answer:

Explanation:

Explanation:
unclean.leader.election.enable=false # Prevents data loss by only considering in-sync replicas when rebalancing.
replication.factor # Specifies how many redundant copies of partitions are distributed across brokers.
min.insync.replicas=2 # Sets the standard for the number of partition instances that must keep up with the latest committed message.
unclean.leader.election.enable=false ensures that only in-sync replicas can be elected as leaders. If disabled, an out-of-sync replica may become leader, potentially leading to data loss.
replication.factor defines how many brokers will maintain copies of each partition, directly impacting durability and availability.
min.insync.replicas determines how many replicas must acknowledge a write when acks=all is used, enforcing write durability.
Reference: Apache Kafka Topic Configuration Documentation


NEW QUESTION # 76
Using the Confluent Schema Registry, where are Avro schema stored?

Answer: B

Explanation:
The Schema Registry stores all the schemas in the _schemas Kafka topic


NEW QUESTION # 77
In Kafka Streams, by what value are internal topics prefixed by?

Answer: B

Explanation:
In Kafka Streams, the application.id is also the underlying group.id for your consumers, and the prefix for all internal topics (repartition and state)


NEW QUESTION # 78
Which two statements are correct about transactions in Kafka?
(Select two.)

Answer: B,D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
# C. Consumers can consume both committed and uncommitted transactions.By default, Kafka consumers only read committed messages if they are configured with isolation.level=read_committed. However, if configured as read_uncommitted, they can also consume uncommitted (potentially aborted) transactional messages.
From Kafka Documentation:
"The isolation.level setting controls whether the consumer will read only committed messages or all messages, including uncommitted messages from ongoing or aborted transactions."
# D. Information about producers and their transactions is stored in the _transaction_state topic.Kafka uses an internal topic named __transaction_state to maintain metadata about producer transactions. This topic is essential for tracking the transaction lifecycle, fencing, and recovery.
From Kafka Internals:
"Kafka stores the state of active and completed transactions in an internal topic called __transaction_state."


NEW QUESTION # 79
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