SQL Interface Development for Spatial Data Retrieval on Document-Based Databases Using Caching Mechanisms

EasyChair Preprint no. 10678

Abstract

Over the years, there has been a growing trend towards the increased adoption of NoSQL data, gradually replacing SQL data due to its numerous advantages. However, NoSQL data also has its drawbacks, and one of these is the limited features or functions for processing spatial data. Currently, some researchers have developed a SQL interface capable of processing spatial data in document-based NoSQL databases. However, the SQL interface still has weaknesses in terms of performance and handling big data. Therefore, in this paper, SQL interface is further improved to address these weaknesses. The approach used to enhance performance by utilizing Redis to store cached data. Secondary storage and batch data retrieval methods are used for handling big data. The SQL interface system was tested by employing diverse queries with various variations. The success parameters of the testing include the performance of the SQL interface system and the accuracy of the obtained data. Based on the evaluation results, the developed system has achieved optimal performance, as evidenced by reduced query times. Big data handling has also been addressed, as all data can be processed efficiently without encountering memory issues like heap out of memory.

Keyphrases: Big Data, NoSQL, Redis, spatial, SQL

@Booklet{EasyChair:10678,
  author = {Kadek Dwi Bagus Ananta Udayana and Tricya Esterina Widagdo},
  title = {SQL Interface Development for Spatial Data Retrieval on Document-Based Databases Using Caching Mechanisms},
  howpublished = {EasyChair Preprint no. 10678},

  year = {EasyChair, 2023}}