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| Section | Weight | Objectives |
|---|---|---|
| Developing with Kafka Consumers | 15-20% | - Offset Management - Consumer Interceptors - Multi-threaded Consumers - Deserialization - Commit Strategies (Auto, Manual, Cooperative) - Consumer Groups and Rebalancing - Consumer Configuration and Tuning |
| Kafka Connect | 10-15% | - Converters and Transforms - Offset Management in Connect - Connector Configuration - Source and Sink Connectors - Single Message Transformations (SMT) - Connect Architecture (Workers, Connectors, Tasks) |
| Kafka Streams | 20-25% | - State Stores and Processors - Windowed Operations (Tumbling, Hopping, Session) - Exactly-Once Processing - Interactive Queries - Streams Architecture and Topology - Testing Kafka Streams Applications - Transformation Operations (map, filter, join, aggregate) |
| Developing with Kafka Producers | 15-20% | - Idempotent Producers - Producer Configuration and Tuning - Serialization (JSON, Avro, Protobuf) - Partitioning Strategies - Producer Interceptors - Error Handling and Retry Logic - Exactly-Once Semantics |
| Security | 5-10% | - Encryption in Transit - Authentication (SASL, SSL/TLS) - Securing Schema Registry - Authorization (ACLs) |
| Schema Management | 5-10% | - Schema Registry Architecture - Schema Evolution and Compatibility - Avro Schemas - Schema Registration and Retrieval - Protobuf and JSON Schemas |
| Monitoring and Operations | 5-10% | - Kafka Metrics and Monitoring - Log Compaction - Cross-region Replication - Disaster Recovery - Consumer Lag and Health Checks |
| Kafka Fundamentals | 10-15% | - Producer and Consumer Basics - Replication Factor and ISR - Log Segments and Retention - Topics, Partitions, and Offsets - Brokers and Clusters |
| Installing and Configuring Kafka | 5-10% | - Topic Creation and Configuration - Partition Assignment Strategies - Broker Configuration Parameters - ZooKeeper vs KRaft Mode |
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NEW QUESTION # 16
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?
Answer: C
Explanation:
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!
NEW QUESTION # 17
When using plain JSON data with Connect, you see the following error messageorg.apache.kafka.connect.errors.DataExceptionJsonDeserializer with schemas.enable requires "schema" and "payload" fields and may not contain additional fields. How will you fix the error?
Answer: D
Explanation:
You will need to set the schemas.enable parameters for the converter to false for plain text with no schema.
NEW QUESTION # 18
Match the testing tool with the type of test it is typically used to perform.
Answer:
Explanation:
Explanation:
* Unit Testing# MockProducer
* Integration Testing# Testcontainers
* Performance Testing# Trogdor
* Mock Data Generation# Connect Datagen
* MockProducer: Simulates a Kafka producer in unit tests (no real broker interaction).
* Testcontainers: Spawns Kafka in Docker forreal environment testing.
* Trogdor: Kafka's built-inperformance load testingframework.
* Connect Datagen: Createssample source recordsfor test and demo purposes.
FromKafka Developer Tools Guide:
"Kafka developers commonly use MockProducer for unit tests, Testcontainers for integration, and Trogdor for performance tests." Reference:Kafka Testing and Tools Overview
NEW QUESTION # 19
Suppose you have 6 brokers and you decide to create a topic with 10 partitions and a replication factor of 3.
The brokers 0 and 1 are on rack A, the brokers 2 and 3 are on rack B, and the brokers 4 and 5 are on rack C.
If the leader for partition 0 is on broker 4, and the first replica is on broker 2, which broker can host the last replica? (select two)
Answer: D,F
Explanation:
When you create a new topic, partitions replicas are spreads across racks to maintain availability. Hence, the Rack A, which currently does not hold the topic partition, will be selected for the last replica
NEW QUESTION # 20
How much should be the heap size of a broker in a production setup on a machine with 256 GB of RAM, in PLAINTEXT mode?
Answer: C
Explanation:
In Kafka, a small heap size is needed, while the rest of the RAM goes automatically to the page cache (managed by the OS). The heap size goes slightly up if you need to enable SSL
NEW QUESTION # 21
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