CFP last date
20 January 2025
Reseach Article

Shredding JSON Data into Relational Environment

by Dušan Petković, Ali Piriyaie
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 174 - Number 17
Year of Publication: 2021
Authors: Dušan Petković, Ali Piriyaie
10.5120/ijca2021921058

Dušan Petković, Ali Piriyaie . Shredding JSON Data into Relational Environment. International Journal of Computer Applications. 174, 17 ( Feb 2021), 25-29. DOI=10.5120/ijca2021921058

@article{ 10.5120/ijca2021921058,
author = { Dušan Petković, Ali Piriyaie },
title = { Shredding JSON Data into Relational Environment },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2021 },
volume = { 174 },
number = { 17 },
month = { Feb },
year = { 2021 },
issn = { 0975-8887 },
pages = { 25-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume174/number17/31770-2021921058/ },
doi = { 10.5120/ijca2021921058 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:22:23.548434+05:30
%A Dušan Petković
%A Ali Piriyaie
%T Shredding JSON Data into Relational Environment
%J International Journal of Computer Applications
%@ 0975-8887
%V 174
%N 17
%P 25-29
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The use of JSON (JavaScript Object Notation) as a data format has expanded significantly in the last couple of years. The reason for this expansion is that JSON can represent structured as well as semi-structured data in a simple way. Storing JSON documents into relational tables is an obvious next step, because that way features of RDBMSs, such as transaction processing and recovery mechanisms, can be used. In this paper we compare representatives of two groups of mapping techniques: the family of Argo algorithms and the family of XML-to-Relational storage algorithms, which can be used to store JSON documents, too. Our results show that the former outperforms the latter in relation to time efficiency, while the XML-to-Relational storage algorithm needs less disk memory to load JSON data.

References
  1. Information technology — Database languages — SQL — Part 14: XML-Related Specifications (SQL/XML), https://www.iso.org/standard/38647.html, last accessed 2020/12/09.
  2. Agraval, R., Somani,A. and Xu, Y. 2000. Storage and Querying of e-commerce Data, Proc of the 27th VLDB Conference.
  3. Chausser, C. 2013. – Enabling JSON Document Stores in Relational Systems, WebDB.
  4. Tahara, D., Diamond, T. and Abadi, D.J. 2014. Sinew: A new SQL System for Multi-Structured data, SIGMOD Conf..
  5. Liu, Z,H., Hammerschmidt, B. and McMahon, D. 2014.JSON Data management – Supporting Schema-Less Development in RDBMS, SIGMOD/PODS’14.
  6. Liu Z.H., Hammerschmidt B., McMahon D., Liu Y. and Chang H.J. 2016.Closing the Functional and Performance Gap between SQL and NoSQL. In: Proc. of the 2016 Int. Conf. on Management of Data.
  7. Piech, M. andMarcjan, R. 2018 A New Approach to Storing Dynamic Data in Relational Databases Using JSON, Computer Science 19(1).
  8. Bahta, R. andAtay, M. 2019. Translating JSON Data into Relational Data Using Schema-Oblivious Approaches, The 2019 ACM Southeast Conference.
  9. Florescu, D. andKossmann, D. 1999. Storing and Querying XML Data using an RDBMS, IEEE Data Eng. Bull.
  10. ISO/IEC TR 19075-6:2017 Information technology -- Database languages -- SQL Technical Reports -- Part 6: SQL support for JavaScript Object Notation (JSON), http://standards.iso.org/ittf/PubliclyAvailableStandards/index.html, (last accessed 2020/11/31).
  11. Petković, D. 2017. SQL/JSON Standard: Properties and Deficiencies, Datenbank Spektrum, 17(3).
  12. Petković,D. 2017. JSON Integration in Relational Database Systems, Int. Journal of Computer Applications, 168(5): 14-19, https://doi.org/10.5120/ijca/2017914389.
  13. Zip Code Data Sample, https://catalog.data.gov/dataset/cadastral-plss-stan15dardized-data-plssspecialsurvey-se-version-1-1, last accessed 2020/12/02.
Index Terms

Computer Science
Information Sciences

Keywords

JSON RDBMSs Argo STDM algorithm space efficiency time efficiency