Sentence examples for large scale data processing from inspiring English sources

The emerging Internet of Things and Smart Cities scenarios also confirm the requirement for real time, large scale data processing.

From that necessity ERMA was born, one of the first large scale data processing machines for business.

MapReduce [1] is considered one of the most prominent programming models for problems of large scale data processing of which the cluster analysis.

Although there is a variety of parallel programming models, the MapReduce paradigm is considered as the most prominent model for problems of large scale data processing of which the clustering.

Examples include using a distributed network of video game players to assist in solving protein folding problems (Markoff 2010), and leveraging Amazon's Mechanical Turk crowdsourcing marketplace platform to assist with large scale data processing and coding functions that cannot be automated (Conley & Tosti-Kharas 2010; Chen et al. 2011).

A trend of huge amount of data with characteristics of large scale, complex types, and wide area distribution produced by smart substation makes the traditional relational database more and more difficult to adapt to the requirements of large scale data processing from power enterprises [3, 4].

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.

MapReduce-like frameworks have achieved tremendous success for large-scale data processing in data centers.

These considerations led us to use cloud computing to meet large-scale data processing requirements.

In the past years, many distributed computing frameworks [1 6] have been developed to perform large-scale data processing.