Implementation of the fast table grid user interface element for working with large database tables

TL;DR

This paper presents a novel fast table grid UI element that efficiently handles large database tables by using index lookups and statistical methods to enable quick scrolling and positioning without loading all data into memory.

Contribution

The paper introduces a new method for implementing a table grid UI that achieves O(Log(N)) performance for scrolling and positioning in large databases, reducing load on RDBMS.

Findings

Achieves O(Log(N)) performance for scrolling and positioning

Uses index lookups and hypergeometric distribution for record prediction

Reduces database load compared to traditional methods

Abstract

Table grid user interface element with a vertical scrollbar is a standard way of working with database table records. There are two basic operations each grid should support: scrolling records with vertical scrollbar and positioning to a record with a given primary key. This paper addresses the case when the number of records is so large that it is not feasible to load them all into memory, and database functions like "select..offset" work insufficiently fast and put undue load on RDBMS. Our main idea is to use only queries that involve index lookup (a O(Log(N)-fast operation) and to use statistic properties of hypergeometric distribution to "guess" primary keys of records given their ordinal numbers. The proposed method allows us to implement a grid with O(Log(N))-fast scrolling and positioning performance.