A distributed big data library extending Java 8

  • Authors

    • MD. A R Quadri
    • B. Sruthi
    • A. D. SriRam
    • B. Lavanya
    2017-12-21
    https://doi.org/10.14419/ijet.v7i1.1.9476
  • Big Data, Distributed Computing, Java, Streams.
  • Java is one of the finest language for big data because of its write once and run anywhere nature. The new release of java 8 introduced few strategies like lambda expressions and streams which are helpful for parallel computing. Though these new strategies helps in extracting, sorting and filtering data from collections and arrays, still there are problems with it. Streams cannot properly process with the large data sets like big data. Also, there are few problems associated while executing in distributed environment. The new streams introduced in java are restricted to computations inside the single system there is no method for distributed computing over multiple systems. And streams store data in their memory and therefore cannot support huge data sets. Now, this paper cope with java 8 behalf of massive data and deed in distributed environment by providing extensions to the Programming model with distributed streams. The distributed computing of large data programming models may be consummated by introducing distributed stream frameworks.

  • References

    1. [1] Cho JH, Chang SA, Kwon HS, Choi YH, KoSH, Moon SD, Yoo SJ, Song KH, Son HS, Kim HS, Lee WC, Cha BY, Son HY & Yoon KH (2006), Long-term effect of the internet-based glucose monitoring system on HbA1c Reduction and glucose stability: a 30-month follow-up study for diabetes management with a ubiquitous medical care system. Diabetes Care 29, 2625–2631. https://doi.org/10.2337/dc05-2371.

      [2] Fauci AS, Braunwald E, Kasper DL & Hauser SL (2008), Principles of Harrison’s Internal Medicine, Vol. 9, 17thedn. McGraw-Hill, New York, NY, pp.2275–2304.

      [3] Kim HS & Jeong HS (2007), A nurse short message service by cellular phone in type-2 diabetic patients for six months. Journal of Clinical Nursing 16, 1082–1087. https://doi.org/10.1111/j.1365-2702.2007.01698.x.

      [4] Lee JR, Kim SA, Yoo JW & Kang YK (2007), The present status of diabetes education and the role recognition as a diabetes educator of nurses in korea. Diabetes Research and Clinical Practice 77, 199–204. https://doi.org/10.1016/j.diabres.2007.01.057.

      [5] McMahon GT, Gomes HE, Hohne SH, Hu TM, Levine BA & Conlin PR (2005), Web-based care management in patients with poorly controlled diabetes. Diabetes Care 28, 1624–1629. https://doi.org/10.2337/diacare.28.7.1624.

      [6] Thakurdesai PA, Kole PL & Pareek RP (2004), Evaluation of the quality and contents of diabetes mellitus patient education on Internet. Patient Education and Counseling 53, 309–313. https://doi.org/10.1016/j.pec.2003.04.001.

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  • How to Cite

    A R Quadri, M., Sruthi, B., SriRam, A. D., & Lavanya, B. (2017). A distributed big data library extending Java 8. International Journal of Engineering & Technology, 7(1.1), 237-239. https://doi.org/10.14419/ijet.v7i1.1.9476