Integrating Apache Spark with OpenStack for Scalable Cloud and IoT Data Processing
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V1I2P102Keywords:
Apache Spark, OpenStack, Big Data, Cloud Computing, Distributed Computing, Resource Management, Data Processing, Scalability, Fault Tolerance, Machine LearningAbstract
The integration of Apache Spark with OpenStack is a promising approach to address the challenges of scalable data processing in cloud and Internet of Things (IoT) environments. This paper explores the synergies between these two powerful technologies, highlighting their individual strengths and the benefits of their integration. We present a comprehensive framework for integrating Apache Spark with OpenStack, discuss the technical challenges, and propose solutions to optimize performance and scalability. Through a series of experiments, we demonstrate the effectiveness of our integrated system in handling large-scale data processing tasks. The results show significant improvements in processing speed, resource utilization, and overall system efficiency. This work aims to provide a robust foundation for researchers and practitioners looking to leverage the combined power of Apache Spark and OpenStack in their dataintensive applications
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