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Lessons
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The term "streaming data" refers to data that is produced continuously by tens of thousands of data sources. A data stream consists of a series of data elements ordered in time.
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Real-time data streaming analytics has become critically important in today's business world due to several significant factors that influence how organizations operate and make decisions.
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Real-time data streaming refers to the process of transmitting and processing data continuously and without delay, as it is generated or ingested.
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Real-time data streaming has a wide range of applications across various industries and domains. Here are some common use cases for real-time data streaming.
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An asynchronous messaging system is a communication pattern used in software architecture to enable different components, applications, or services to exchange information without requiring them to be actively waiting for each other's responses.
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Apache Kafka is an open-source, distributed streaming platform that is designed to handle real-time data feeds and high-throughput, fault-tolerant, scalable data streaming.
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Apache Kafka is a widely used open-source stream-processing platform and messaging system. It was originally developed by LinkedIn and later open-sourced as part of the Apache Software Foundation.
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Apache Kafka is designed around several key fundamentals that enable its high-throughput, fault-tolerant, and scalable capabilities.
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A data pipeline, to put it simply, is a set of actions that transfer unprocessed data from a source to a destination.
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In this document, we are going to explain how we can use a single-node Apache Kafka cluster for development and learning purposes.
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-Open the terminal by CTRL+ALT+T
- Go to the folder where zookeeper tar ball is copied by using the following commands.
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(Extract Kafka) Go to the location of Kafka and extract the tar ball.
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Now type on a new terminal cd /user/local/ kafka /bin
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Several tools/scripts are included in the bin directory of the Apache Kafka binary installation, which we will learn in detail in the Apache Kafka Advance Course.
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Publishing dummy messages using built-in producer scripts
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Consuming message from Kafka Topic using built-in consumer scripts
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Lets use the scripts to stop publisher & consumer using below steps.
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Go to /usr /local/zookeeper/bin on the terminal and press enter
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To produce a message into an Apache Kafka topic using Java, you'll need to use the Kafka Producer API provided by the Apache Kafka library.
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To consume messages from an Apache Kafka topic using Java, you'll need to use the Kafka Consumer API provided by the Apache Kafka library.
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Apache Kafka's broker properties are configuration settings that control the behavior and functionality of individual Kafka brokers within a Kafka cluster.
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Apache Kafka's producer properties are configuration settings that control the behavior and functionality of Kafka producers. These properties are specified when configuring a Kafka producer in your application.
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Apache Kafka's consumer properties are configuration settings that control the behavior and functionality of Kafka consumers.
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In Apache Kafka, a consumer group is a high-level abstraction that represents a group of consumers working together to consume messages from one or more Kafka topics.
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