Blog post

Experience and Lessons Learned for Large-Scale Graph Analysis using GraphX

While GraphX provides nice abstractions and dataflow optimizations for parallel graph processing on top of Apache Spark*, there are still many challenges in app

Authored by Mike P. (Intel) Last updated on 06/14/2017 - 15:44
Blog post

The JITter Conundrum - Just in Time for Your Traffic Jam

In interpreted languages, it just takes longer to get stuff done - I earlier gave the example where the Python source code a = b + c would result in a BINARY_ADD byte code which takes 78 machine instructions to do the add, but it's a single native ADD instruction if run in compiled language like C or C++. How can we speed this up? Or as the performance expert would say, how do I decrease...
Authored by David S. (Blackbelt) Last updated on 07/04/2019 - 20:00
Blog post

Getting Started with Tachyon by Use Cases

In-memory computing has become an irreversible trend in big data technology, for which the wide popularity of Spark provides a good evidence. Meanwhile, memory storage and management for large data sets are still posing challenges. Out of numerous solutions, Tachyon, a memory-centric distributed storage, well solves the problems faced by many application scenarios. For example, it avoids severe...
Authored by Last updated on 06/07/2019 - 16:01
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按照使用案例开始使用 Tachyon

In-memory computing has become an irreversible trend in big data technology, for which the wide popularity of Spark provides a good evidence. Meanwhile, memory storage and management for large data sets are still posing challenges. Out of numerous solutions, Tachyon, a memory-centric distributed storage, well solves the problems faced by many application scenarios. For example, it avoids severe...
Authored by Last updated on 06/07/2019 - 16:00