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Tag Archives: Lucene

Advanced GemFire + Lucene + Spring Data for Text Searching

In this article, we’ll talk about how to integrate the Lucene text searching solution using Spring Data and GemFire to provide a flexible, parallel fast search engine. By combining the two independent products we can leverage each product to its fullest capability. The end result provides an elastic search capability with the in memory data speeds of a distributed cache platform and high availability.

Motivation—Why Combine These?

The motivation of the project was to provide an alternative search capability for GemFire while providing users a natural method to define searchable domain object attributes. Performance was also a key driver to ensure constant search performance irrespective of scale. The solution outlined below provides a baseline approach for developers to build upon. Continue reading

ROBLOX: RabbitMQ, Hybrid Clouds, and 1 Billion Page Views/Month

Online video games have amazing software architectures, particularly when they support millions or billions of transactions.

One of the most interesting companies in this growing industry is ROBLOX.

If you haven’t heard of ROBLOX, they allow users develop their own games – creating players, 3D worlds, and objects from first-person shooters to genres like military and sci-fi. They are able to share these games with others, and, of course, play them. The ROBLOX application also has a built in advertising system, social network, and virtual economy with currencies. According to their website, they generate:

  • Over one billion page views, 29 million in-game hours, and 10 million unique visitors per month.
  • Players created 5.4 million games and spent over 250 million hours of game-play in 2011

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4 Key Architecture Considerations for Big Data Analytics

Everyone seems to be talking about “Big Data” these days. We’re bombarded with information in online and print media about the explosion of machine generated data, the petabytes of data that companies like Facebook and Twitter generate, and the billions of dollars of opportunities awaiting all businesses through the use of big data. We also hear about what seems an alphabet soup of new technologies to process and analyze big data: Hadoop for distributed data processing, R for analytics, Lucene for text indexing and search, Mahout for machine learning…the list goes on and on.

If you’re a business user, you’re thinking that big data could give you an edge over your competition. If you’re a developer, you’re excited about the many new technologies you can learn about. If you’re an architect, you’re trying to figure out how all these big data technologies fit within your existing and future infrastructure.

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