Manufacturing companies increasingly become “smarter” as a result of the Industry 4.0
revolution. Multiple sensors are used for industrial monitoring of machines and workers in …

Financial institutions face many challenges in managing modern financial transactions and
vast data volumes. To overcome these challenges, they are increasingly harnessing …

Sensor networks have dynamically expanded our ability to monitor and study the world.
Their presence and need keep increasing, and new hardware configurations expand the …

In contemporary distributed systems, logs are produced at an astounding rate, generating
terabytes of data within mere seconds. These logs, containing pivotal details like system …

A recommender system based on offline batch processing has the benefit of being precise in
its computation and having a high level of fault tolerance. However, because of the huge …

In general, predicting Stock Market is quite a demanding task, and targeting very high
accuracy is not exactly going to work. Nonetheless, few techniques in machine learning …

Stream Processing is a technology widely used in fetching continuous streams of data within
a very short period of time. In the internet era, data is not limited to a small set of producers …

In contemporary distributed systems, logs are produced at an astounding rate, generating
terabytes of data within mere seconds. These logs, containing pivotal details like system …

This paper conducts Kafka and Spark Streaming to enrich the data ingestion rate through
the pipeline with high throughput. This paper aims to investigate the features, functionality …

Apache Kafka is a widely used, distributed, open-source event streaming platform, which is
available as a basic reference architecture for IoT use cases of the Autonomous Systems …