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How to Fast Load Large Datasets into Apache Ignite by Using a Key-Value API

Now, in-memory cache technology is becoming popular, motivating companies to experiment with distributed systems. The technology is advertised to be fast, and data-load speed is often critical for building a successful solution prototype. This blog post provides a technical tutorial on how to populate a distributed Apache Ignite cluster with values that originate from large relational tables. All the code in the tutorial is available from the FastDataLoad repository at the GitHub.
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Previous Entries

As member of IBM PartnerWorld program GridGain complete validation for "Ready for IBM Grid Computing" seal. We were surprised by the level of attention we were given and breadth of the partner programs that IBM provides for its partners, even to small startups like us.IBM offers plenty of specially designed solutions for partners to run and validate their software on practically any IBM hardware…
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GridGain 1.6 Released!

GridGain team just released GridGain 1.6. This release is about stability, documentation and... JUnit integration! We are very excited that GridGain 1.6 is the first grid product with natural and elegant integration for JUnit. Few lines of code to change or simply add annotation - and your JUnits are running on the grid saving you time on your build - great feature and a great use case supporting…
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Social networks have been lately in a spotlight. The concept is clear and it works: provide web-tools for ad-hoc networking between individuals or group of individuals.Some time ago I noticed that there is some similarity between the basic concept of social networks and the grid computing product we are currently pushing to release. In fact, social networks are based on capability of ad-hoc…
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Look at this article: http://hardware.silicon.com/servers/0,39024647,39159214,00.htmThe overriding theme of this article (and it is based off the same IT research in UK) is that Grid Computing is: too expensive too complex too ambiguous in its valueNot surprising these are the same pain factors we attempts to address in our upcoming product: it will be licensed under LGPL and its runtime will be…
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Grid Computing and AOP

One of the unique features of our upcoming GridGain 1.0 product is AOP-based integration.Since the beginning, the integration part of Grid Computing products was a sore point. APIs are complex, non-intuitive and vendor generally assumed that people writing grid-enabled software would be willing to spend a significant time on grid-enabling process (changing their applications, learning complex…
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When thinking about how Grid Computing software can be architected there are many angles one can look from. One such angle that is rarely seen is whether to consider the software architecture from the "Resource" point of view, or from the "Task" point of view.As much as abstract it sounds this question is rather very fundamental to how your Grid Computing software will be used. Let me explain by…
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The usual answer is - Google it... Oh, you did? Well, the odds are that you are not any closer to the answer - and you are not alone.Working on Grid Computing for the last 5 years I've accumulated my own share of strange looks on people faces when trying to describe to them the grid computing idea. What is fascinating is that the actual concepts behind Grid Computing are very familiar, simple and…
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