CCDAK學習資料，通過Confluent Certified Developer for Apache Kafka Certification Examination CCDAK認證考試的不二選擇

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Confluent CCDAK Exam Syllabus Topics:

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

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最新的 Confluent Certified Developer CCDAK 免費考試真題 (Q34-Q39):

問題 #34
You have a Kafka cluster and all the topics have a replication factor of 3. One intern at your company stopped a broker, and accidentally deleted all the data of that broker on the disk. What will happen if the broker is restarted?

答案：C

解題說明：
Kafka replication mechanism makes it resilient to the scenarios where the broker lose data on disk, but can recover from replicating from other brokers. This makes Kafka amazing!


問題 #35
You need to set alerts on key broker metrics to trigger notifications when the cluster is unhealthy.
Which are three minimum broker metrics to monitor?
(Select three.)

答案：A,D,E

解題說明：
These three metrics are critical for cluster health:
* OfflinePartitionsCount: Indicates partitions without active leaders - a sign of broker failure.
* ActiveControllerCount: There should beexactly one active controller. A count # 1 signals controller failure.
* UncleanLeaderElectionsPerSec: Tracks leader elections where out-of-sync replicas were selected - risky for data loss.
FromKafka Monitoring Documentation:
"Offline partitions and unclean leader elections should trigger alerts. Also, ensure a single active controller is running."
* A is about topics pending deletion - not critical.
* E is a per-topic record metric, not broker-level.
Reference:Kafka Monitoring > Key JMX Metrics


問題 #36
There are 3 producers writing to a topic with 5 partitions. There are 10 consumers consuming from the topic as part of the same group. How many consumers will remain idle?

答案：B

解題說明：
One consumer per partition assignment will keep 5 consumers idle.


問題 #37
You are sending messages to a Kafka cluster in JSON format and want to add more information related to each message:
Format of the message payload
Message creation time
A globally unique identifier that allows the message to be traced through the systemWhere should this additional information be set?

答案：D

解題說明：
Kafka message headers are the right place to include metadata such as:
Payload format (e.g., schema version)
Timestamps (custom)
Trace or correlation IDs
From Kafka Producer API Docs:
"Headers are a map of key-value pairs that can be used to include metadata alongside the message, without modifying the message body." Keys determine partitioning and ordering Values are the message payload Brokers do not store arbitrary metadata fields Reference: Kafka ProducerRecord API > Headers


問題 #38
You are sending messages to a Kafka cluster in JSON format and want to add more information related to each message:
* Format of the message payload
* Message creation time
* A globally unique identifier that allows the message to be traced through the systemWhere should this additional information be set?

答案：D

解題說明：
Kafkamessage headersare the right place to includemetadatasuch as:
* Payload format (e.g., schema version)
* Timestamps (custom)
* Trace or correlation IDs
FromKafka Producer API Docs:
"Headers are a map of key-value pairs that can be used to include metadata alongside the message, without modifying the message body."
* Keys determine partitioning and ordering
* Values are the message payload
* Brokers do not store arbitrary metadata fields
Reference:Kafka ProducerRecord API > Headers


問題 #39
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