Describe the Apache Kafka Queueing System and Architecture DATA-ENGINEERING-OPTIMIZE Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   In a streaming data pipeline, what is a common role for Kafka?

   • AA machine learning model that predicts future events.
   • BA central message bus that decouples data producers from data consumers.
   • CA data warehouse that stores historical data for reporting.
   • DA scheduling tool that triggers batch jobs.
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2. 7application · medium

   A manufacturing company uses Kafka to collect data from IoT sensors on the factory floor. The data is used for real-time monitoring and also for predictive maintenance. The company wants to ensure that if a sensor sends a reading, it is not lost even if the network temporarily fails. Which Kafka feature should they rely on?

   • AKafka Connect
   • BProducer retries and acks=all
   • CConsumer group rebalancing
   • DKafka's log retention policy
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4. 8foundation · easy

   Which Kafka feature allows the same message to be read by multiple independent applications?

   • AConsumer groups
   • BPublish-subscribe model
   • CPartition replication
   • DMessage queueing
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5. 9application · medium

   A smart-city project deploys thousands of sensors that emit temperature, humidity, and air-quality readings every few seconds. The data is sent to a central Kafka cluster. The city's operations team wants to process this data in real time to trigger alerts, and also wants to store the raw data for later analysis. Which Kafka feature or pattern should they use?

   • AUse Kafka Streams to process the data and write results to a separate topic for alerts, while the raw data remains in the original topic.
   • BConfigure the topic with a very short retention period so that data is automatically deleted after processing.
   • CHave the sensors send data directly to a data warehouse, bypassing Kafka.
   • DUse a single consumer group to both process alerts and store raw data.
   Reveal Solution Discussion Select an answer first
6. 10foundation · easy

   Which delivery semantics in Kafka guarantees that a message is never lost but may be delivered more than once?

   • AExactly-once
   • BBest-effort
   • CAt-least-once
   • DAt-most-once
   Reveal Solution Discussion Select an answer first