forked from sheetjs/docs.sheetjs.com
		
	
		
			
	
	
		
			29 lines
		
	
	
		
			1.3 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
		
		
			
		
	
	
			29 lines
		
	
	
		
			1.3 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
|  | --- | ||
|  | title: Big Data | ||
|  | pagination_prev: demos/extensions/index | ||
|  | pagination_next: demos/engines/index | ||
|  | --- | ||
|  | 
 | ||
|  | import DocCardList from '@theme/DocCardList'; | ||
|  | import {useCurrentSidebarCategory} from '@docusaurus/theme-common'; | ||
|  | 
 | ||
|  | SheetJS demonstrated the value of processing large datasets in the web browser | ||
|  | and other JavaScript environments. SheetJS libraries have pushed the limits of | ||
|  | data processing in the web browser, and some innovations and discoveries have | ||
|  | been integrated into the ReactJS framework and other foundational JS libraries. | ||
|  | 
 | ||
|  | JS Engines have improved over the years, but there are some hard limits to | ||
|  | browser support using traditional methods of data processing.  Vendors have | ||
|  | introduced APIs and techniques for representing and processing very large binary | ||
|  | and textual files. Since many of the techniques only work in a few engines, they | ||
|  | are recommended only when the traditional approaches falter: | ||
|  | 
 | ||
|  | <ul>{useCurrentSidebarCategory().items.map((item, index) => { | ||
|  |   const listyle = (item.customProps?.icon) ? { | ||
|  |     listStyleImage: `url("${item.customProps.icon}")` | ||
|  |   } : {}; | ||
|  |   return (<li style={listyle} {...(item.customProps?.class ? {className: item.customProps.class}: {})}> | ||
|  |     <a href={item.href}>{item.label}</a>{item.customProps?.summary && (" - " + item.customProps.summary)} | ||
|  |   </li>); | ||
|  | })}</ul> |