Performance Evaluation of Google Spreadsheet over RDBMS through Cloud Scripting Algorithms

التفاصيل البيبلوغرافية
العنوان: Performance Evaluation of Google Spreadsheet over RDBMS through Cloud Scripting Algorithms
المؤلفون: Lahiru J. Ekanayake, Sachith.P. Abyesundara, Deepthi Ihalage
المصدر: 2021 International Conference on Computer Communication and Informatics (ICCCI).
بيانات النشر: IEEE, 2021.
سنة النشر: 2021
مصطلحات موضوعية: SQL, business.industry, Relational database, Computer science, Cloud computing, computer.software_genre, Query language, Relational database management system, Scripting language, The Internet, business, Database connection, Algorithm, computer, computer.programming_language
الوصف: Google Apps Script (GAS) is a scripting platform developed by Google for light-weight application development in the G Suite platform. It offers built-in APIs for almost all the services offered by GSuite. When developing systems using Google Apps Script, Developers can configure external Relational database management system (RDBMS) connections or Spreadsheets as a database. The main objective of this study is to evaluate the performance of Google Spreadsheet as a database over RDBMS and compare the performance of different algorithms when reading and writing data into Spreadsheets and RDBMS. Seven experiments were carried out by using multiple algorithms to compare the reading performance such as, retrieving all values within a specified range and processing them, retrieving data using query formula, SELECT statement in Structured Query Language (SQL), Google Query Language, and joining multiple tables in the spreadsheet. Execution times were calculated by changing different parameters such as the number of records, database connection time, and array processing time. A REST API endpoint has been implemented using GAS to evaluate the reliability of writing data into databases and executed it with Apache JMeter concurrent users. Results revealed that processing inside the array, and the query formula, for around 10k - 15k records could be done in Spreadsheets reading. When the number of records was increased the above methods did not work efficiently. The method FetchUrlApp had significant improvement in Spreadsheets when retrieving data using multiple algorithms. Adding a write lock for a long period provided a reliable output when concurrent users tried to write into a Spreadsheet. A slight reduction of reliability is identified while writing data into RDBMS with concurrent users. Such reliability issues and findings of the study will help users to consider the GAS platform when implementing databases and algorithms. The above-mentioned reliability issue and increasing columns and their effect on the performance of GAS are key areas to carry out future work.
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::f63ae0666af51371556800ca351beceeTest
https://doi.org/10.1109/iccci50826.2021.9402432Test
رقم الانضمام: edsair.doi...........f63ae0666af51371556800ca351becee
قاعدة البيانات: OpenAIRE