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Parametric Analysis of Cloud Data Partitioning Techniques: Review Paper

Kiranjit Kaur1 , Vijay Laxmi2

Section:Review Paper, Product Type: Journal Paper
Volume-6 , Issue-9 , Page no. 881-884, Sep-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i9.881884

Online published on Sep 30, 2018

Copyright © Kiranjit Kaur, Vijay Laxmi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Kiranjit Kaur, Vijay Laxmi, “Parametric Analysis of Cloud Data Partitioning Techniques: Review Paper,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.881-884, 2018.

MLA Style Citation: Kiranjit Kaur, Vijay Laxmi "Parametric Analysis of Cloud Data Partitioning Techniques: Review Paper." International Journal of Computer Sciences and Engineering 6.9 (2018): 881-884.

APA Style Citation: Kiranjit Kaur, Vijay Laxmi, (2018). Parametric Analysis of Cloud Data Partitioning Techniques: Review Paper. International Journal of Computer Sciences and Engineering, 6(9), 881-884.

BibTex Style Citation:
@article{Kaur_2018,
author = {Kiranjit Kaur, Vijay Laxmi},
title = {Parametric Analysis of Cloud Data Partitioning Techniques: Review Paper},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2018},
volume = {6},
Issue = {9},
month = {9},
year = {2018},
issn = {2347-2693},
pages = {881-884},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2959},
doi = {https://doi.org/10.26438/ijcse/v6i9.881884}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i9.881884}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2959
TI - Parametric Analysis of Cloud Data Partitioning Techniques: Review Paper
T2 - International Journal of Computer Sciences and Engineering
AU - Kiranjit Kaur, Vijay Laxmi
PY - 2018
DA - 2018/09/30
PB - IJCSE, Indore, INDIA
SP - 881-884
IS - 9
VL - 6
SN - 2347-2693
ER -

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Abstract

Technology makes life easier but at the same time generating bundles of data which is difficult to manage in traditional data stores. To manage this huge data, new data stores called NoSQL came into existence, they resolve the problem of data management by using partitioning. This paper discusses different partitioning techniques named horizontal, Vertical and Workload Driven Partitioning. Focus of this paper is to compare these partitioning techniques on the bases of important parameters named communication cost, complexity of search, quality and scalability. It provides the result on the basis of analysis which helps to choose the relevant partitioning technique.

Key-Words / Index Term

Horizontal partitioning, Vertical partitioning, Workload Driven partitioning, Communication cost, Complexity of search, Quality, Scalibility

References

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