Padmashree Ravindra

Works (5)

Updated: July 5th, 2023 15:44

2014 journal article

Algebraic optimization of RDF graph pattern queries on MapReduce

Large Scale and Big Data: Processing and Management, 183–227.

By: K. Anyanwu, P. Ravindra & H. Kim

Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018

2014 journal article

Nesting Strategies for Enabling Nimble MapReduce Dataflows for Large RDF Data

INTERNATIONAL JOURNAL ON SEMANTIC WEB AND INFORMATION SYSTEMS, 10(1), 1–26.

By: P. Ravindra n & K. Anyanwu  n

author keywords: Hadoop; MapReduce; Multi-Valued Properties; RDF Graph Pattern Queries; Semantic Web; SPARQL; Unnesting Strategies
TL;DR: This paper argues for the use of a nested data model for representing intermediate data concisely using nesting-aware dataflow operators that allow for lazy and partial unnesting strategies and confirms their superiority over relational-style MapReduce systems such as Apache Pig and Hive. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2014 conference paper

Towards optimization of RDF analytical queries on MapReduce

2014 IEEE 30th International Conference on Data Engineering Workshops (ICDEW), 335–339.

By: P. Ravindra

Source: NC State University Libraries
Added: August 6, 2018

2012 journal article

Algebraic Optimization for Processing Graph Pattern Queries in the Cloud

IEEE INTERNET COMPUTING, 17(2), 52–61.

By: K. Anyanwu  n, H. Kim n & P. Ravindra n

TL;DR: An algebraic optimization approach based on a Nested TripleGroup Data Model and Algebra (NTGA) that minimizes overall processing costs by reducing the number of MapReduce cycles is presented. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2009 conference paper

RAPID: Enabling scalable ad-hoc analytics on the semantic web

Semantic web - iswc 2009, proceedings, 5823, 715–730.

By: R. Sridhar n, P. Ravindra n & K. Anyanwu  n

TL;DR: A language, RAPID, for scalable ad-hoc analytical processing of RDF data on Map-Reduce frameworks is presented, builds on Yahoo's Pig Latin by introducing primitives based on a specialized join operator, the MD-join, for expressing analytical tasks in a manner that is more amenable to parallel processing. (via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries, ORCID
Added: August 6, 2018

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