Historical Google research papers (2006):

MapReduce is a programming model for distributed data processing and execution environment that runs on large clusters of commodity machines. A MapReduce job usually splits the input data-set into independent chunks which are processed by the map tasks in a completely parallel manner. The framework sorts the outputs of the maps, which are then input to the reduce tasks. The framework takes care of scheduling tasks, monitoring them and re-executes the failed tasks. MapReduce originated from Google research papers in 2004 and since then become the heart of Hadoop.

Google Research Papers - Research at Google

Extracting the numbers from the images is a complex task, but Google research papers it has developed a deep neural network system that can be trained to identify numbers of up to five digits long.


Discontinuous Seam Carving for Video: Google Research Paper

infrastructure future looks like, my advice would be to read the Google research papers that are coming out right now.

In 2009, the web giant started replacing GFS and MapReduce , and Mike Olson will tell you that these technologies are where the world is going. “If you want to know what the large-scale, high-performance data processing infrastructure of the future looks like, my advice would be to read the Google research papers that are coming out right now,” Olson said during a alongside Wired.


Like the rest of Google's much admired back-end infrastructure, Chubby is decidedly closed source, so men and built their own. Although they didn't have source code, they did have one of those secret-spilling Google research papers. And they had Go, Google's open source programming language for building systems like Google's.