Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Data Mining and Knowledge Discovery
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Dryad: distributed data-parallel programs from sequential building blocks
Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
Estimating the output cardinality of partial preaggregation with a measure of clusteredness
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Distributed aggregation for data-parallel computing: interfaces and implementations
Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles
All-Pairs: An Abstraction for Data-Intensive Computing on Campus Grids
IEEE Transactions on Parallel and Distributed Systems
DryadLINQ for Scientific Analyses
E-SCIENCE '09 Proceedings of the 2009 Fifth IEEE International Conference on e-Science
Pregel: a system for large-scale graph processing
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Performance of Windows Multicore Systems on Threading and MPI
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Twister: a runtime for iterative MapReduce
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
OSDI'08 Proceedings of the 8th USENIX conference on Operating systems design and implementation
Performance comparison under failures of MPI and MapReduce: An analytical approach
Future Generation Computer Systems
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The design and implementation of higher level data flow programming language interfaces are becoming increasingly important for data intensive computation. DryadLINQ is a declarative, data-centric language that enables programmers to address the Big Data issue in the Windows Platform. DryadLINQ has been successfully used in a wide range of applications for the last five years. The latest release of DryadLINQ was published as a Community Technology Preview (CTP) in December 2010 and contains new features and interfaces that can be customized in order to achieve better performances within applications and in regard to usability for developers. This paper presents three design patterns in DryadLINQ CTP that are applicable to a large class of scientific applications, exemplified by SW-G, Matrix-Matrix Multiplication and PageRank with real data.