DATABASE FUNDAMENTALS
BASICS OF BIG DATA
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Publish and subscribe to streams of records, similar to a message queue or enterprise messaging system
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Store streams of records in a fault-tolerant durable way
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Process streams of records as they occur
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All of the mentioned
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Detailed explanation-1: -Tasks in Kafka Streams leverage the fault-tolerance capability offered by the Kafka consumer client to handle failures. If a task runs on a machine that fails, Kafka Streams automatically restarts the task in one of the remaining running instances of the application.
Detailed explanation-2: -Apache Kafka is a distributed streaming platform. A streaming platform contains the following three important capabilities: A distributed streaming platform helps us to push records easily. It provides huge storage space and also helps us to store a lot of records without any problem.
Detailed explanation-3: -Every stream task in a Kafka Streams application may embed one or more local state stores that can be accessed via APIs to store and query data required for processing. These state stores can either be a RocksDB database, an in-memory hash map, or another convenient data structure.
Detailed explanation-4: -Fault tolerance in Kafka is done by copying the partition data to other brokers which are known as replicas. There is a configuration that specifies how many copies of the partition you need. Its called a replication factor. Each broker will hold one or more partitions.