Massive RDF Data Complicated Query Optimization Based on MapReduce

AbstractProcessing massive RDF data complicated query efficiently is a matter of concern for a long time in semantic web research. This paper proposes a MapReduce framework which could be a fast scalable solution. In this framework, the first step is doing the data preprocessing using a method called PredicateLead. Next the JobPartitioner algorithm partitions the query into several MapReduce jobs. The output of previous two operations should be the input of the last step——processing query in MapReduce. A case study on emergency decision demonstrates the efficiency and scalability of this framework