Stream processing in Big Data for e-health care

Stream processing in Big Data for e-health care

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In this chapter, we will present the stream processing and batch processing. Besides, we will conduct a qualitative comparison of the most popular data processing systems, namely Storm and Spark streaming. We will describe their respective underlying bases and the functionalities they provide and discuss how they can be introduced into e-health care analysis programs.

Chapter Contents:

  • 11.1 Introduction
  • 11.2 Stream processing for low-latency analytics
  • 11.2.1 Batch processing vs. stream processing
  • 11.2.2 Challenges of stream processing
  • 11.3 Real-time processors
  • 11.3.1 Storm platform
  • 11.3.2 Samza platform
  • Samza architecture
  • 11.3.3 Spark platform
  • Spark use cases
  • 11.4 Stream processing in e-health care
  • 11.5 Conclusion
  • References

Inspec keywords: medical administrative data processing; data analysis; Big Data; health care; batch processing (computers)

Other keywords: Big Data; stream processing; Spark; e-health care analysis programs; batch processing; Storm

Subjects: Medical administration; Data handling techniques; Operating systems

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