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100912 |
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|a dc
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|a Jindal, Alekh
|e author
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|a Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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|a Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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|a Jindal, Alekh
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|a Rawlani, Praynaa
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|a Wu, Eugene
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|a Madden, Samuel R.
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|a Stonebraker, Michael
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|a Rawlani, Praynaa
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|a Wu, Eugene
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|a Deshpande, Amol
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|a Madden, Samuel R.
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|a Stonebraker, Michael
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|a Vertexica: your relational friend for graph analytics!
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|b Association for Computing Machinery (ACM),
|c 2016-01-19T02:04:41Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/100912
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|a In this paper, we present Vertexica, a graph analytics tools on top of a relational database, which is user friendly and yet highly efficient. Instead of constraining programmers to SQL, Vertexica offers a popular vertex-centric query interface, which is more natural for analysts to express many graph queries. The programmers simply provide their vertex-compute functions and Vertexica takes care of efficiently executing them in the standard SQL engine. The advantage of using Vertexica is its ability to leverage the relational features and enable much more sophisticated graph analysis. These include expressing graph algorithms which are difficult in vertex-centric but straightforward in SQL and the ability to compose end-to-end data processing pipelines, including pre- and post- processing of graphs as well as combining multiple algorithms for deeper insights. Vertexica has a graphical user interface and we outline several demonstration scenarios including, interactive graph analysis, complex graph analysis, and continuous and time series analysis.
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|a en_US
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|a Article
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|t Proceedings of the VLDB Endowment
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