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Many Big Data use cases have one thing 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.
In this course, you will learn how Kafka is used in the real world and its architecture and components. You will quickly get up and running, producing and consuming messages using both the command line tools and the Java APIs. You also will get hands on experience connecting Kafka to Spark, and working with Kafka Connect.
Module 1: Introduction to Apache Kafka
Question: Which of the following are a Kafka use case?
Question: A Kafka cluster is comprised of one or more servers which are called “producers”
Question: Kafka requires Apache ZooKeeper
Module 2: Kafka Command Line
Question: 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.
Question: Which of the following is NOT returned when –describe is passed to kafka-topics.sh?
Question: Topic deletion is disabled by default.
Module 3: Kafka Producer Java API
Question: The setting of ack that provides the strongest guarantee is ack=1
Question: The KafkaProducer is the client that publishes records to the Kafka cluster.
Question: Which of the following is not a Producer configuration setting?
Module 4: Kafka Consumer Java API
Question: The Kafka consumer handles various things behind the scenes, such as:
Question: If enable.auto.commit is set to false, then committing offsets is done manually, which provides gives you more control.
Question: 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.
Module 5: Kafka Connect and Spark Streaming
Question: Which of the following are Kafka Connect features?
Question: Kafka Connector has two types of worker nodes called standalone mode and centralized mode cluster
Question: Spark periodically queries Kafka to get the latest offsets in each topic and partition that it is interested in consuming form.
Question: 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.
Question: Which of the following is false about Kafka Connect?
Question: Kafka comes packaged with a command line client that you can use as a producer.
Question: Kafka Connect worker processes work autonomously to distribute work and provide scalability with fault tolerance to the system.
Question: What are the three Spark/Kafka direct approach benefits? (Place the answers in alphabetical order.)
Question: Kafka Consumer is thread safe, as it can give each thread its own consumer instance
Question: What other open source producers can be used to code producer logic?
Question: 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.
Question: Kafka has a cluster-centric design which offers strong durability and fault-tolerance guarantees.
Question: Which of the following values of ack will not wait for any acknowledgement from the server?
Question: A Kafka cluster is comprised of one or more servers which are called “Producers”
Question: What are In Sync Replicas?
Question: In many use cases, you see Kafka used to feed streaming data into Spark Streaming
Question: All Kafka Connect sources and sinks map to united streams of records
Question: Which is false about the KafkaProducer send method?
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