Confluent CCDAK證照資訊：Confluent Certified Developer for Apache Kafka Certification Examination和資格考試的領導者

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Confluent CCDAK Exam Syllabus Topics:

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

>> CCDAK證照資訊 <<

Confluent CCDAK考證 - CCDAK認證考試

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最新的 Confluent Certified Developer CCDAK 免費考試真題 (Q64-Q69):

問題 #64
(You need to set alerts on key broker metrics to trigger notifications when a Kafka cluster is unhealthy.
What are three minimum broker metrics to monitor for cluster health?
Select three.)

A. kafka.controller:type=KafkaController,name=LastCommittedRecordOffset
B. kafka.controller:type=KafkaController,name=ActiveControllerCount
C. kafka.controller:type=KafkaController,name=TopicsToDeleteCount
D. kafka.controller:type=KafkaController,name=OfflinePartitionsCount
E. kafka.controller:type=ControllerStats,name=UncleanLeaderElectionsPerSec

答案：B,D,E

解題說明：
The Apache Kafka monitoring and operations documentation highlights several controller-level metrics that are critical indicators of cluster health.
ActiveControllerCount must always be 1 in a healthy cluster. A value of 0 indicates no active controller, while values greater than 1 indicate a serious split-brain condition. This metric is fundamental for cluster stability.
OfflinePartitionsCount is one of the most important health metrics. Any value greater than 0 means that some partitions have no available leader, making them unavailable for producers and consumers. This directly indicates a degraded or unhealthy cluster.
UncleanLeaderElectionsPerSec tracks the rate of unclean leader elections. Unclean elections can cause data loss, and any non-zero value is a strong signal of broker failures or misconfiguration and should immediately trigger alerts.
The remaining options are not minimum health indicators. LastCommittedRecordOffset is not a standard health metric, and TopicsToDeleteCount only indicates pending administrative operations, not cluster instability.
Therefore, the three minimum and officially recommended broker metrics for monitoring Kafka cluster health are UncleanLeaderElectionsPerSec, ActiveControllerCount, and OfflinePartitionsCount.

問題 #65
A consumer has auto.offset.reset=latest, and the topic partition currently has data for offsets going from 45 to
2311. The consumer group never committed offsets for the topic before. Where will the consumer read from?

A. offset 45
B. it will crash
C. offset 2311
D. offset 0

答案：C

解題說明：
Latest means that data retrievals will start from where the offsets currently end

問題 #66
An application is writing AVRO messages using Schema Registry to topic t1. During this process, the Schema Registry becomes unavailable for a few seconds.
What is the expected impact to the application?

A. Since the broker will eventually replicate the message Schema, there will not be an error.
B. The application may not have any impact, unless it is writing messages with a new Schema Definition.
C. All messages within that time will receive an error.
D. Since messages are cached by the producer, the application will only get an error if the producer is sending the batch at that time.

答案：B

問題 #67
Which Kafka CLI should you use to consume from a topic?

A. kafka-console-consumer
B. kafka-topics
C. kafka-console
D. kafka-consumer-groups

答案：A

解題說明：
Examplekafka-console-consumer --bootstrap-server 127.0.0.1:9092 --topic test --from-beginning

問題 #68
You want to perform table lookups against a KTable everytime a new record is received from the KStream. What is the output of KStream-KTable join?

A. KTable
B. GlobalKTable
C. You choose between KStream or KTable
D. Kstream

答案：D

解題說明：
Here KStream is being processed to create another KStream.

問題 #69
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CCDAK考證: https://www.vcesoft.com/CCDAK-pdf.html

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