Big Data in HTML5

Backend Optimisation Options in SAS


  • Separation of front / backend
  • Presummarisation
  • Paging
  • Intelligent caching

Front vs Back

Separation of front and backend is non-negotiable!

  • Scalability
  • Forward compatibility (SAS 9 -> Viya)
  • Speed of development (workflow)
  • Differing skillsets
  • Documentation of API
  • Maintainability


Send only the data you need to send!

  • Browsers often have restricted memory on corporate devices
  • SAS is fast and extremely powerful for data management
  • Well defined interfaces minimise the need for client side rendering and large IO volumes
  • Avoid 'stateful' services (eg STP sessions) as they can impact load balancing


Avoid browser-freeze!  When showing tables of data, divide into 'pages' that can be stepped over.

  • To keep browsers responsive, they shouldn't be dealing with more than 1-2 mb of data at a time 
  • Prefetching nearby pages will further improve responsiveness
  • Requires STATE - this can be in a filesystem or database but involves cleanup


Browsers automatically cache JS / CSS / Image files etc.  Server side data caching significantly improves the responsiveness for large queries - simply store under a hash of the input query and use that as a lookup.

  • Requires a cache management system (lookup tables)
  • Proactive cache generation avoids the 'initial query' cost 
  • Be sure to remove stale caches when source data is refreshed

Big Data in HTML5

By Allan Bowe

Big Data in HTML5

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