UTILIZATION OF POSTGIS EXTENSION FOR SPATIAL DATA PROCESSING ON DOCUMENT-ORIENTED DATABASES

With the development of internet in all over the world, spatial data processing is increasingly needed. In addition, the use of relational data is replaced by NoSQL data in last decades. This makes the need for handling spatial data in NoSQL databases increasingly important. However, the NoSQL...

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Bibliographic Details
Main Author: Hanif Adzkiya, Muhammad
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/56343
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:With the development of internet in all over the world, spatial data processing is increasingly needed. In addition, the use of relational data is replaced by NoSQL data in last decades. This makes the need for handling spatial data in NoSQL databases increasingly important. However, the NoSQL Database Management System (DBMS) does not yet provide many spatial operations. Pradipta (2020) proposes to process spatial data stored in MongoDB using PostgreSQL/PostGIS spatial functions. However, this solution still has some drawbacks such as slow queries, and only implemented on MongoDB. These two drawbacks can be solved by optimizing the number of data taken from documentoriented databases so that query execution can run faster. The method used in this final project is to utilize projection query and optimize selection operations during data retrieval in documentoriented databases. Optimizing the selection operation is done by utilizing the Abstract Syntax Tree (AST) so that more condition operations can be executed on a document-oriented databases. In addition, abstraction can be done on the system architecture so that it can be used in other document-oriented databases easily. Evaluation is carried out on the functionality and performance of the system developed by this final project. In terms of function, the system can handle various kinds of queries that contain spatial operations. In addition, there are improvements in system performance. This can be seen from the query execution time which is faster than the previous system. Based on the evaluation results, it can be concluded that the system has succeeded in optimizing the handling of selection and projection operations and supports other types of document-oriented databases