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Comparative analysis of real-time messages in big data pipeline architecture

机译:大数据管道架构中实时消息的比较分析

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摘要

Nowadays, real-time messaging system is the essential thing in enabling time-critical decision making in many applications where it is important to deal with real-time requirements and reliability requirements simultaneously. For dependability reasons, we intend to maximise the reliability requirement of the real-time messaging system. To develop a real-time messaging system, we create real-time big data pipeline by using Apache Kafka and Apache Storm. This paper focuses on analysing the performance of producer and consumer in Apache Kafka processing. Apache Kafka is the most popular framework used to ingest the data streams into the processing platforms. The comparative analysis of Kafka processing is more efficient to get reliable data on the pipeline architecture. Then, the experiment will be conducted the processing time in the performance of the producer and consumer on various partitions and many servers. The performance analysis of Kafka can impact on messaging systems in real-time big data pipeline architecture.
机译:如今,实时消息系统是在许多应用中启用时间关键决策的必要事项,在那里同时处理实时要求和可靠性要求很重要。有关可靠性原因,我们打算最大限度地提高实时消息系统的可靠性要求。要开发实时消息系统,我们使用Apache Kafka和Apache Storm创建实时大数据管道。本文侧重于分析生产者和消费者在Apache Kafka处理中的表现。 Apache Kafka是最受欢迎的框架,用于将数据流摄入处理平台。 KAFKA处理的比较分析更有效地在管道架构上获得可靠的数据。然后,实验将在各种分区和许多服务器上进行生产者和消费者的处理时间。 Kafka的性能分析可能会影响实时大数据管道架构中的消息系统。

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