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AN APPROACH FOR RDF INDEXING AND QUERY PROCESSINGFebruary 21, 2014Rajesh Kannan - 16164021Prudhvi Nalluri - 16163411Kranthi Reddy - 12366438V.Y.V. Akhilesh - 16165666OverviewRDF (Resource Description Framework) is used for describing the resources on the web. It provides structured, machine understandable meta entropy for the web. The statements on resources are organize 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 info set and the results can be results sets or RDF graphs.The ObjectiveWe are provided with the large RDF dataset and will be given a collection of SPARQL queries to fire on the dataset. Our determination 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 its open source. Main use of Jena is to write the data to and read the data from RDF graph. The main mean of this project is to design and implement a RDF storage mechanism to store data with good performance and scalability.The OpportunityMany 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 turn up 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, etcetera We are going with Cassandra, which is an open source database and there will be ... ...thms are not mandatory for this approach. Cassandra ProsCassandra 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 rela tional database systems.Cassandra is designed to be distributed and scalable, So Cassandra can support massive amount of data spread crosswise 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-ntripleshttp//docs.mongodb.org/manual/tutorial/install-mongodb-on-windows/http//www.codeproject.com/Articles/279947/Migration-of-Relational-Data-structure-to-Cassandrhttp//answers.semanticweb.com/questions/716/storing-rdf-data-into-hbasehttp//cs-www.cs.yale.edu/homes/dna/abadirdf.pdf