Abstract: Top-k Skyline query combines the features of Top-k query and Skyline,which can find the best object in the datasets.However,the available methods can not fit to large datasets well.An efficient Top-k Skyline query method called DFTS was proposed,which can perform well for large datasets.DFTS involves three steps.Firstly,the degreescore function is used to rank the dataset,and a large quantity of objects with low ranking will be filtered out.Secondly,DFTS makes a Skyline query upon the candidates and generates a Skyline subset.Finally,top-k objects with high ran-king will be selected from the Skyline subset as the final result.Through these steps,DFTS can significantly reduce the time cost.It is proved that the results of DFTS satisfy the demand of Top-k Skyline query.Extensive experimental results show that DFTS can achieve much better performance for large datasets than state-of-the-art methods.

Key words: Apache Spark, Skyline, Top-k