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AN APPROACH FOR RDF INDEXING AND QUERY PROCESSING February 21, 2014 Rajesh Kannan - 16164021 Prudhvi Nalluri - 16163411 Kranthi Reddy - 12366438 V.Y.V. Akhilesh - 16165666 Overview RDF (Resource Description Framework) is used for describing the resources on the web. It provides structured, machine – understandable metadata for the web. The statements on resources are formed in the form of subject-predicate-object (triples), which can be represented as labeled graphs. SPARQL is the query language for RDF. It provides the standard format and rules for writing and processing queries on RDF data set and the results can be results sets or RDF graphs. The Objective We are provided with the large RDF dataset and will be given a collection of SPARQL queries to fire on the dataset. Our aim is to implement a new approach for query processing and get the results same like getting the result through standard SPARQL query processor. Jena is a framework for java used for semantic web and it’s open source. Main use of Jena is to write the data to and read the data from RDF graph. The main purpose of this project is to design and implement a RDF storage mechanism to store data with good performance and scalability. The Opportunity Many approaches have been proposed to retrieve the data from NoSQL database such as vertical partitioning approach, RDF-3X, Matrix Bit, Bit Mat, etc. We will use vertical partitioning approach because of its performance technique and it was proved to be effective in variety of applications like biomedical data, data warehousing and for taxonomic data. We have lot of NoSQL databases to use such as MongoDB, Cassandra, Hbase, Couchbase, Etc. We are going with Cassandra, which is an open source database and there will be ... ...thms are not mandatory for this approach. Cassandra Pros †¢ Cassandra has all the advantages of the NoSQL. It does not use the relational model, which is required to maintain complex relationships as seen with current relational database systems. †¢ Cassandra is designed to be distributed and scalable, So Cassandra can support massive amount of data spread across multiple servers and also Cassandra is an open source. †¢ Cassandra is decentralized system and also works well in clustered and cloud environment. Bibliography †¢ http://blog.datagraph.org/2010/04/transmuting-ntriples †¢ http://docs.mongodb.org/manual/tutorial/install-mongodb-on-windows/ †¢ http://www.codeproject.com/Articles/279947/Migration-of-Relational-Data-structure-to-Cassandr †¢ http://answers.semanticweb.com/questions/716/storing-rdf-data-into-hbase †¢ http://cs-www.cs.yale.edu/homes/dna/abadirdf.pdf