S Babu - Proceedings of the 1st ACM symposium on Cloud …, 2010 - dl.acm.org
Timely and cost-effective processing of large datasets has become a critical ingredient for the success of many academic, government, and industrial organizations. The combination …
R Lämmel - Science of computer programming, 2008 - Elsevier
Google's MapReduce programming model serves for processing large data sets in a massively parallel manner. We deliver the first rigorous description of the model including its …
The MapReduce distributed programming framework has become popular, despite evidence that current implementations are inefficient, requiring far more hardware than a …
J Dean, S Ghemawat - Communications of the ACM, 2008 - dl.acm.org
MapReduce is a programming model and an associated implementation for processing and generating large datasets that is amenable to a broad variety of real-world tasks. Users …
Until now, design patterns for the MapReduce framework have been scattered among various research papers, blogs, and books. This handy guide brings together a unique …
H Herodotou, S Babu - Proceedings of the VLDB Endowment, 2011 - dl.acm.org
MapReduce has emerged as a viable competitor to database systems in big data analytics. MapReduce programs are being written for a wide variety of application domains including …
MapReduce [5] is a well-known programming model, developed within Google, for processing large amounts of raw data such as crawled documents or web request logs on a …
L Chen, X Huo, G Agrawal - SC'12: Proceedings of the …, 2012 - ieeexplore.ieee.org
The work presented here is driven by two observations. First, heterogeneous architectures that integrate a CPU and a GPU on the same chip are emerging, and hold much promise for …
G Wang, AR Butt, P Pandey, K Gupta - … of the 1st ACM workshop on …, 2009 - dl.acm.org
Recently, there has been a huge growth in the amount of data processed by enterprises and the scientific computing community. Two promising trends ensure that applications will be …