Failure recovery model in big data using the checkpoint approach

Authors

  • Sonika Chorey G. H. Raisoni University, Amravati
  • Neeraj Sahu G. H. Raisoni University, Amravati

Keywords:

Big data, Distributed Stream Processing (DSP), fault tolerance, Checkpoint, Deep learning

Abstract

Distributed Stream Processing systems are becoming an increasingly crucial aspect of Big Data processing platforms as customers grow ever more reliant on their capacity to deliver fast access to fresh findings. As a result, the ability of a system to tolerate failure is necessary for making prompt judgments based on these data. By using checkpoint, these systems typically achieve fault tolerance and the capacity to automatically recover from partial failures. An innovative method for automatic runtime optimization of fault detection and tolerance methods have been developed and used in this work.

URN:NBN:sciencein.jist.2023.v11.564

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fault finding in big data

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Published

2023-04-17

Issue

Section

Computer Sciences and Mathematics

URN

How to Cite

Failure recovery model in big data using the checkpoint approach. (2023). Journal of Integrated Science and Technology, 11(4), 564. https://pubs.thesciencein.org/journal/index.php/jist/article/view/a564

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