With the dawning of “Big Data” and Analytics, we as Software Engineers and Developers need to, more than ever, efficiently utilize all computing resources, both hardware and software, in order for our applications to optimally harvest and process such data.
This XPages Insights into Big Data OpenNTF project contains a “Phase 1” sample application that demonstrates two things:
– A simple data partitioning pattern to enable “Big Data” scalability (potentially TeraBytes ++). Achieved via a Managed Bean routing layer within a data-less XPages “dashboard” application.
– Multi-database parallel searching across a large data-set. When a search is requested within the UI, a multi-threaded concurrent search is carried out across twenty-six different databases before providing a seamless search result back to the end-user.
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Follow the XPages Masterclass Video Series throughout 2013 where four series will be published covering various topic areas vital to building robust, performant XPages applications.
In this first XPages Masterclass video series, you will gain insight into the XPages Request Processing Lifecycle – this is the “center of gravity” for every XPages request and response and you will learn why it is important for you as an XPages Developer to understand it.
Series 1 uses a sample application (lifecycle.nsf) to introduce and explain key aspects of the XPages Request Processing Lifecycle. The XPages Toolbox is also used to further highlight the importance of becoming proficient in understanding the XPages Request Processing Lifecycle in order to be able to profile and tune your XPages applications. Series 1 – Video 4 completes the first series by explaining and demonstrating four main characteristics of the XPages Request Processing Lifecycle before undertaking a detailed examination of the Greenwell Helpdesk application where some day-to-day use cases turn up surprising results that are then optimized to produce a truly performant and robust application.
Series 1 includes four video’s – an introduction video, plus three extensive deep-dive videos:
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