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Distributed Data-Parallel Computing Using a High-Level Programming Language

Summary: Dryad and DryadLINQ offer a general-purpose, data-parallel engine with a strongly typed .NET object model. It auto-translates LINQ programs into distributed execution plans on Dryad, enabling scalable data processing beyond SQL/MapReduce. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4190
Venue
SIGMOD
Year
2009
Pagerank
0.00010762918
Overall Rank
1,721 | 88.03%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank Citing Paper Year Venue Pagerank
66 Spark SQL: Relational Data Processing in Spark 2015 SIGMOD 0.00061639801
542 Shark: SQL and Rich Analytics at Scale 2013 SIGMOD 0.00020595648
1,800 epiC: an Extensible and Scalable System for Processing Big Data 2014 VLDB 0.00010512649
2,867 StatusQuo: Making Familiar Abstractions Perform Using Program Analysis 2013 CIDR 7.9831651e-05
5,294 GLADE: Big Data Analytics Made Easy 2012 SIGMOD 5.5810654e-05
8,464 Piranha: Optimizing Short Jobs in Hadoop 2013 VLDB 4.5052127e-05
9,083 AT-GIS: Highly Parallel Spatial Query Processing with Associative Transducers 2016 SIGMOD 4.399861e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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