Skyline Evaluation Within Join Operation, Block Nested Loop Join Implementation
نویسنده
چکیده
Skyline Join approach in its Naïve age work as it computes join first and then apply skyline computation to find corresponding skyline objects. Considering increase in cardinality and dimensionality of join table the cost of computing skyline in a non-reductive join relation is costlier than that of on single table. Most of the existing work on skyline queries for databases mainly discusses the computation efficiency in single relational table. In proposed work we investigate the evaluation of skylines over disparate sources via joins in efficient manner. The basic idea of our approach is that without computing skyline in the entire joined table, we can process the joined skyline only based on the property of being skyline to quickly identify the skyline object for the joined tuple. We propose an algorithm to build on top of the traditional relational Block Nested-Loop join algorithms, which fuses the computation of the join and the skyline in order to outputs the correct skyline without computing the full join. Our Experimental results demonstrate the applicability of interweaving join and skyline together.
منابع مشابه
Gorder: An Efficient Method for KNN Join Processing
An important but very expensive primitive operation of high-dimensional databases is the KNearest Neighbor (KNN) similarity join. The operation combines each point of one dataset with its KNNs in the other dataset and it provides more meaningful query results than the range similarity join. Such an operation is useful for data mining and similarity search. In this paper, we propose a novel KNN-...
متن کاملDiag-Join: An Opportunistic Join Algorithm for 1:N Relationships
Time of creation is one of the predominant (often implicit) clustering strategies found not only in Data Warehouse systems: line items are created together with their corresponding order, objects are created together with their subparts and so on. The newly created data is then appended to the existing data. We present a new join algorithm, called DiagJoin, which exploits time-of-creation clust...
متن کاملAn End-Around Approach for Efficient Join Query Processing
This paper introduced a method for producing immediate and result in multi-join query, in homogeneous and heterogeneous environment. In recent years Adaptive or Non Blocking join algorithms have attracted a lot of attention in streaming applications, where data is provided from autonomous data sources in heterogeneous network environments. This algorithms are better as compared to traditional a...
متن کاملDistributed Approach to Continuous Queries with kNN Join Processing in Spatial Telemetric Data Warehouse
This chapter describes realization of distributed approach to continuous queries with kNN join processing in the spatial telemetric data warehouse. Due to dispersion of the developed system, new structural members were distinguished: the mobile object simulator, the kNN join processing service, and the query manager. Distributed tasks communicate using JAVA RMI methods. The kNN queries (k Neare...
متن کاملThe Complete Story of Joins (in HyPer)
SQL has evolved into an (almost) fully orthogonal query language that allows (arbitrarily deeply) nested subqueries in nearly all parts of the query. In order to avoid recursive evaluation strategies which incur unbearable O(n2) runtime we need an extended relational algebra to translate such subqueries into non-standard join operators. This paper concentrates on the non-standard join operators...
متن کامل