Query Processing for Streaming RDF Data

Nowadays enormous amount of data is generated due to growing use of sensor technologies in various real-time application domains like social network, weather, transportation and healthcare. This data is mostly in the form of continuous streams. To process such streams RDF Stream Processing technology is used in which streams are represented in RDF format. The goal of this paper is to develop the Query Processing Architecture for Streaming RDF Data and evaluate the performance of model by analyzing the output metrics (execution time and memory consumption) for the queries with different complexities (Select, Aggregation, Joins). We identify the input parameters (window size, type of window, aggregation functions, number of joins, and number of triples) that directly impact the output metrics. Finally, we analyze and discuss the type of window algorithm which can be used for different types of queries based on the output metrics.