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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Schema Management | 5-10% | - Schema Evolution and Compatibility - Schema Registration and Retrieval - Schema Registry Architecture - Avro Schemas - Protobuf and JSON Schemas |
| Topic 2: Kafka Fundamentals | 10-15% | - Replication Factor and ISR - Brokers and Clusters - Producer and Consumer Basics - Log Segments and Retention - Topics, Partitions, and Offsets |
| Topic 3: Kafka Connect | 10-15% | - Connect Architecture (Workers, Connectors, Tasks) - Converters and Transforms - Connector Configuration - Source and Sink Connectors - Offset Management in Connect - Single Message Transformations (SMT) |
| Topic 4: Monitoring and Operations | 5-10% | - Consumer Lag and Health Checks - Log Compaction - Disaster Recovery - Cross-region Replication - Kafka Metrics and Monitoring |
| Topic 5: Developing with Kafka Consumers | 15-20% | - Multi-threaded Consumers - Commit Strategies (Auto, Manual, Cooperative) - Offset Management - Consumer Configuration and Tuning - Deserialization - Consumer Interceptors - Consumer Groups and Rebalancing |
| Topic 6: Installing and Configuring Kafka | 5-10% | - Broker Configuration Parameters - Topic Creation and Configuration - ZooKeeper vs KRaft Mode - Partition Assignment Strategies |
| Topic 7: Security | 5-10% | - Authorization (ACLs) - Authentication (SASL, SSL/TLS) - Securing Schema Registry - Encryption in Transit |
| Topic 8: Kafka Streams | 20-25% | - Testing Kafka Streams Applications - State Stores and Processors - Interactive Queries - Windowed Operations (Tumbling, Hopping, Session) - Exactly-Once Processing - Transformation Operations (map, filter, join, aggregate) - Streams Architecture and Topology |
| Topic 9: Developing with Kafka Producers | 15-20% | - Idempotent Producers - Serialization (JSON, Avro, Protobuf) - Producer Interceptors - Producer Configuration and Tuning - Error Handling and Retry Logic - Exactly-Once Semantics - Partitioning Strategies |
Die echten und originalen Prüfungsfragen und Antworten zu CCDAK Zertifizierung (Confluent Certified Developer for Apache Kafka Certification Examination) bei ZertSoft wurden verfasst von unseren IT-Experten mit den Informationen von CCDAK Prüfungen (Confluent Certified Developer for Apache Kafka Certification Examination) aus dem Testcenter wie PROMETRIC oder VUE.
73. Frage
You have an existing topic t1 with four partitions.
Which statement is correct about changing the number of partitions for this topic?
Antwort: C
74. Frage
(You deploy a Kafka Streams application with five application instances.
Kafka Streams stores application metadata using internal topics.
Auto-topic creation is disabled in the Kafka cluster.
Which statement about this scenario is true?)
Antwort: C
Begründung:
According to the official Apache Kafka Streams documentation, Kafka Streams relies on internal topics (such as changelog topics and repartition topics) to store state, task assignments, and application metadata. These topics are essential for fault tolerance, rebalancing, and state recovery.
When auto-topic creation is disabled, Kafka Streams cannot automatically create the required internal topics unless they already exist. In this situation, the Streams application will fail during startup with a fatal, non- retriable exception, indicating that the necessary internal topics could not be created.
Kafka Streams does not pause or wait for manual topic creation, nor does it operate without storing metadata.
Instead, it explicitly requires these topics to exist or be creatable. While administrators can manually pre- create the required internal topics with the correct configuration, failure to do so causes the application to terminate.
Therefore, the correct and documented behavior is that the Kafka Streams application terminates with a non- retriable exception when auto-topic creation is disabled and required internal topics are missing.
75. Frage
Match each configuration parameter with the correct deployment step in installing a Kafka connector.
Antwort:
Begründung:
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.
From Kafka 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
76. Frage
Which partition assignment minimizes partition movements between two assignments?
Antwort: B
Begründung:
The StickyAssignor tries to minimize partition movement by preserving existing assignments as much as possible while still achieving a balanced assignment. This improves consumer stability and reduces rebalances.
From the Kafka Consumer Assignor Documentation:
"The StickyAssignor attempts to preserve as many existing assignments as possible, which helps minimize partition movement between rebalances." RoundRobinAssignor focuses on even distribution, not stability.
RangeAssignor groups partitions by topic and assigns them consecutively, but can lead to imbalances.
PartitionAssignor is an abstract base class, not an assignor used directly.
Reference: Kafka Consumer Assignor Docs
77. Frage
To import data from external databases, I should use
Antwort: C
Begründung:
Kafka Connect Sink is used to export data from Kafka to external databases and Kafka Connect Source is used to import from external databases into Kafka.
78. Frage
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