Cognitive Class: Simplifying data pipelines with Apache Kafka Exam Answers

Cognitive Class: Simplifying data pipelines with Apache Kafka Exam Answers: ✅✅✅ Learn what Big Data use cases have in common – the use of Apache Kafka somewhere in the mix. Whether the distributed, partitioned, replicated commit log service is being used for messaging, website activity tracking, stream processing or more, there’s no denying it is a hot technology.

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Course NameSimplifying data pipelines with Apache Kafka
TrainerAaron Ritchie
OrganizationCognitive Class
AudienceData Engineers
LevelBeginner
LanguageEnglish
PriceFree
CertificateYes

Cognitive Class – Simplifying data pipelines with Apache Kafka Answers

Cognitive Class: Simplifying data pipelines with Apache Kafka Exam Answers

Simplifying data pipelines with Apache Kafka

Module 1: Introduction to Apache Kafka

1. Which of the following are a Kafka use case?

  1. Messaging
  2. All of the above
  3. Stream Processing
  4. Website Activity Tracking
  5. Log Aggregation

2. A Kafka cluster is comprised of one or more servers which are called “producers”

  1. True
  2. False

3. Kafka requires Apache ZooKeeper

  1. True
  2. False

Module 2: Kafka Command Line

1. There are two ways to create a topic in Kafka, by enabling the auto.create.topics.enable property and by using the kafka-topics.sh script.

  1. True
  2. False

2. Which of the following is NOT returned when –describe is passed to kafka-topics.sh?

  1. Configs
  2. None of the Above
  3. PartitionNumber
  4. ReplicationFactor
  5. Topic

3. Topic deletion is disabled by default.

  1. True
  2. False

Module 3: Kafka Producer Java API

1. The setting of ack that provides the strongest guarantee is ack=1

  1. True
  2. False

2. The KafkaProducer is the client that publishes records to the Kafka cluster.

  1. True
  2. False

3. Which of the following is not a Producer configuration setting?

  1. batch.size
  2. linger.ms
  3. key.serializer
  4. retries
  5. None of the above

Module 4: Kafka Consumer Java API

1. The Kafka consumer handles various things behind the scenes, such as:

  1. Failures of servers in the Kafka cluster
  2. Adapts as partitions of data it fetches migrates within the cluster
  3. Data management and storage into databases
  4. A and B only
  5. All of the Above

2. If enable.auto.commit is set to false, then committing offsets is done manually, which provides gives you more control.

  1. True
  2. False

3. Rebalancing is a process where group of consumer instances within a consumer group, coordinate to own mutally shared sets of partitions of topics that the groups are subscribed to.

  1. True
  2. False

Module 5: Kafka Connect and Spark Streaming

1. Which of the following are Kafka Connect features?

A common framework for Kafka connectors

  1. Automatic offset management
  2. REST interface
  3. Streaming/batch integration
  4. All of the above

2. Kafka Connector has two types of worker nodes called standalone mode and centralized mode cluster

  1. True
  2. False

3. Spark periodically queries Kafka to get the latest offsets in each topic and partition that it is interested in consuming form.

  1. True
  2. False

Simplifying data pipelines with Apache Kafka Final Exam Answers

1. If the auto.create.topics.enable property is set to false and you try to write a topic that doesn’t yet exist, a new topic will be created.

  1. True
  2. False

2. Which of the following is false about Kafka Connect?

  1. Kafka Connect makes building and managing stream data pipelines easier
  2. Kafka Connect simplifies adoption of connectors for stream data integration
  3. It is a framework for small scale, asynchronous stream data integration
  4. None of the above

3. Kafka comes packaged with a command line client that you can use as a producer.

  1. True
  2. False

4. Kafka Connect worker processes work autonomously to distribute work and provide scalability with fault tolerance to the system.

  1. True
  2. False

5. What are the three Spark/Kafka direct approach benefits? (Place the answers in alphabetical order.)

Kafka Consumer is thread safe, as it can give each thread its own consumer instance

  1. True
  2. False

6. What other open source producers can be used to code producer logic?

  1. Java
  2. Python
  3. C++
  4. All of the above

7. If you set acks=1 in a Producer, it means that the leader will write the received message to the local log and respond after waiting for full acknowledgement from all of its followers.

  1. True
  2. False

8. Kafka has a cluster-centric design which offers strong durability and fault-tolerance guarantees.

  1. True
  2. False

9. Which of the following values of ack will not wait for any acknowledgement from the server?

  1. all
  2. 0
  3. 1
  4. -1

10. A Kafka cluster is comprised of one or more servers which are called “Producers”

  1. True
  2. False

11. What are In Sync Replicas?

  1. They are a set of replicas that are not active and are delayed behind the leader
  2. They are a set of replicas that are not active and are fully caught up with the leader
  3. They are a set of replicas that are alive and are fully caught up with the leader
  4. They are a set of replicas that are alive and are delayed behind the leader

12. In many use cases, you see Kafka used to feed streaming data into Spark Streaming

  1. True
  2. False

13. All Kafka Connect sources and sinks map to united streams of records

  1. True
  2. False

14. Which is false about the KafkaProducer send method?

  1. The send method returns a Future for the RecordMetadata that will be assigned to a record
  2. All writes are asynchronous by default
  3. It is not possible to make asynchronous writes
  4. Method returns immediately once record has been stored in buffer of records waiting to be sent

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