Database Query Optimization in Crowdsourcing System

Data is placed at different web or data servers in a crowdsourcing system. It is difficult to answer queries by machine. Processing such queries requires human input for providing information that is missing from the database, for performing computationally difficult functions, and for matching, ranking, or aggregating. In crowdsourcing system optimization of query is the major challenge. In proposed system, the user submits SQL query which is optimized based on cost constraints. An execution plan is generated and output is produced to the user. This system can be used for answering queries posed over stored relational data together with data obtained on demand from the crowd. This system considers a cost-based query optimization which also considers the latency that generates best possible and suitable query execution plan. The proposed system uses efficient algorithms for optimizing three types of query evaluation i.e. select, join, and complex-join query.