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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Developing with Kafka Producers | 15-20% | - Producer Interceptors - Exactly-Once Semantics - Producer Configuration and Tuning - Partitioning Strategies - Idempotent Producers - Error Handling and Retry Logic - Serialization (JSON, Avro, Protobuf) |
| Topic 2: Installing and Configuring Kafka | 5-10% | - ZooKeeper vs KRaft Mode - Broker Configuration Parameters - Partition Assignment Strategies - Topic Creation and Configuration |
| Topic 3: Kafka Streams | 20-25% | - Interactive Queries - State Stores and Processors - Windowed Operations (Tumbling, Hopping, Session) - Transformation Operations (map, filter, join, aggregate) - Exactly-Once Processing - Streams Architecture and Topology - Testing Kafka Streams Applications |
| Topic 4: Monitoring and Operations | 5-10% | - Disaster Recovery - Cross-region Replication - Consumer Lag and Health Checks - Kafka Metrics and Monitoring - Log Compaction |
| Topic 5: Schema Management | 5-10% | - Avro Schemas - Protobuf and JSON Schemas - Schema Registry Architecture - Schema Registration and Retrieval - Schema Evolution and Compatibility |
| Topic 6: Kafka Fundamentals | 10-15% | - Replication Factor and ISR - Producer and Consumer Basics - Topics, Partitions, and Offsets - Log Segments and Retention - Brokers and Clusters |
| Topic 7: Kafka Connect | 10-15% | - Single Message Transformations (SMT) - Connect Architecture (Workers, Connectors, Tasks) - Connector Configuration - Source and Sink Connectors - Converters and Transforms - Offset Management in Connect |
| Topic 8: Developing with Kafka Consumers | 15-20% | - Consumer Configuration and Tuning - Consumer Interceptors - Consumer Groups and Rebalancing - Multi-threaded Consumers - Commit Strategies (Auto, Manual, Cooperative) - Offset Management - Deserialization |
| Topic 9: Security | 5-10% | - Securing Schema Registry - Authorization (ACLs) - Encryption in Transit - Authentication (SASL, SSL/TLS) |
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質問 # 86
What is a consequence of increasing the number of partitions in an existing Kafka topic?
正解：C
解説：
Increasing partitions increasesparallelism, but also means:
* Consumers in a group may have to handlemore partitions, especially if the number of consumers is lower than the number of partitions.
* This can result inincreased lag, especially under high load.
FromKafka Topic Management Docs:
"Increasing the number of partitions increases consumer work, and if consumers can't keep up, lag can accumulate."
* A is false:existing data is not redistributed.
* B is false:records with the same key always map to the same partitionbased on hash.
* D is not directly impacted by the partition count.
Reference:Kafka Topic Management > Adding Partitions
質問 # 87
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?
正解：A
質問 # 88
Where are the dynamic configurations for a topic stored?
正解：A
解説：
Dynamic topic configurations are maintained in Zookeeper.
質問 # 89
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?
正解：C
解説：
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
質問 # 90
Match each configuration parameter with the correct deployment step in installing a Kafka connector.
正解：
解説：
Explanation:
* 1st:Place the connector's JAR file in the directory specified by plugin.path
* 2nd:Restart the Kafka Connect cluster
* 3rd:Verify using REST API (/connector-plugins)
* 4th:Configure the connector
* 5th:(Repeat of 4th, duplicate step)
1st # Place the connector's JAR file in the directory specified by the plugin.path configuration.
2nd # Restart the Kafka Connect cluster.
3rd # Verify that the connector is installed by listing all available connectors using the Kafka Connect REST API (/connector-plugins).
4th # Configure the connector using a JSON or properties file with the necessary settings.
5th # Configure the connector using a JSON or properties file with the necessary settings.
Kafka Connect requires that custom connectors be placed in the directory defined by plugin.path. After restarting the cluster, you can use the REST API to confirm availability and then deploy the connector configuration.
FromKafka Connect Documentation:
"After placing the JAR in the plugin.path, you must restart the Connect cluster to pick it up. Use the
/connector-plugins REST endpoint to verify."
The duplication of configuration is an error in the question options and should occur only once.
Reference:Kafka Connect Plugin Installation Guide
質問 # 91
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