A key feature is that being architecture agnostic, BDS allows users to code, test and debug big data analysis pipelines on different systems than the ones intended for full-scale data processing.
From that necessity ERMA was born, one of the first large scale data processing machines for business.
Most recently, Amazon added a web-scale data processing engine with Amazon Elastic MapReduce.
MapReduce-like frameworks have achieved tremendous success for large-scale data processing in data centers.
Clearly, MapReduce is the most prominent model for problems of large-scale data processing.
There have been a lot of large-scale data processing frameworks in the scientific research area.
Full-scale data on the dynamic properties of buildings in Japan have been collected and analyzed.
A comparison between the full-scale data and wind tunnel predictions is conducted.
There are no full-scale data on iceberg towing in ice.
Their implementation made automatization and large-scale handling of data processing possible.
The potential of huge amounts of already collected full-scale processing data and its related performance history have however so far been under-employed in the production optimization efforts.
