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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Kafka Connect | 15% | - Source and sink connectors configuration - Connect architecture: workers, connectors, tasks, converters - Data transformation and integration patterns |
| Topic 2: Application Testing | 8% | - Integration testing and test clusters - Mocking and test utilities - Unit testing producers and consumers |
| Topic 3: Apache Kafka Streams | 12% | - Error handling and state management - Windowing and time semantics - Streams API concepts: topology, processors, state stores - Stream processing operations: map, filter, join, aggregation |
| Topic 4: Application Observability | 13% | - Tracing and performance tuning - Error diagnosis and troubleshooting - Logging and monitoring metrics |
| Topic 5: Apache Kafka Application Development | 28% | - Transactional messaging and idempotence - Producer API: configuration, serialization, partitioning, error handling - Schema management: Confluent Schema Registry, compatibility rules, evolution - Consumer API: configuration, offset management, consumer groups, rebalancing |
| Topic 6: Apache Kafka Fundamentals | 23% | - Delivery semantics: at-most-once, at-least-once, exactly-once - Configuration basics and cluster setup - Kafka architecture and data flow - Core concepts: brokers, topics, partitions, replicas, offsets |
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NEW QUESTION # 71
A bank uses a Kafka cluster for credit card payments. What should be the value of the property unclean.leader.
election.enable?
Answer: B
Explanation:
Setting unclean.leader.election.enable to true means we allow out-of-sync replicas to become leaders, we will lose messages when this occurs, effectively losing credit card payments and making our customers very angry.
NEW QUESTION # 72
A kafka topic has a replication factor of 3 and min.insync.replicas setting of 1. What is the maximum number of brokers that can be down so that a producer with acks=all can still produce to the topic?
Answer: C
Explanation:
Two brokers can go down, and one replica will still be able to receive and serve data
NEW QUESTION # 73
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?
Answer: C
Explanation:
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
NEW QUESTION # 74
You are creating a Kafka Streams application to process retail data.
Match the input data streams with the appropriate Kafka Streams object.
Answer:
Explanation:
Explanation:
Table # Product, Customers
Stream # Orders_Placed, Shipment_Of_Orders
Tables represent slowly changing, reference data - e.g., customer profiles, product info.
Streams represent real-time event data - e.g., orders placed, shipments processed.
From Kafka Streams Documentation:
"Use KTable for reference datasets, and KStream for event-based processing such as orders or logs." Reference: Kafka Streams API Concepts
NEW QUESTION # 75
You have a Zookeeper cluster that needs to be able to withstand the loss of 2 servers and still be able to function. What size should your Zookeeper cluster have?
Answer: E
Explanation:
Your Zookeeper cluster needs to have an odd number of servers, and must maintain a majority of servers up to be able to vote. Therefore, a 2N+1 zookeeper cluster can survive to N zookeeper being down, so here the right answer is N=2, 2*N+1=5
NEW QUESTION # 76
......
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