By Stanislaw Kozielski, Dariusz Mrozek, Pawel Kasprowski, Bożena Malysiak-Mrozek, Daniel Kostrzewa
This ebook constitutes the refereed complaints of the tenth IEEE overseas convention past Databases, Architectures, and buildings, BDAS 2014, held in Ustron, Poland, in may well 2014. This e-book comprises fifty six rigorously revised chosen papers which are assigned to eleven thematic teams: question languages, transactions and question optimization; info warehousing and large info; ontologies and semantic net; computational intelligence and information mining; collective intelligence, scheduling, and parallel processing; bioinformatics and organic facts research; photo research and multimedia mining; defense of database platforms; spatial information research; functions of database platforms; internet and XML in database systems.
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Extra info for Beyond Databases, Architectures, and Structures: 10th International Conference, BDAS 2014, Ustron, Poland, May 27-30, 2014. Proceedings
Stencel Fig. 2. The partial order of metagranules Metagranules represent the aggregates used by the application. Some of them are chosen to be actually materialized. We call them proper metagranules. In Figure 2 their symbols have double border. e. the maximal metagranule smaller or equal to the desired metagranule. A smaller metagranule contains more records. Thus the query based on a smaller metagranule will ﬁnish later. For some metagranules there could be more than one metagranule that satisﬁes the abovementioned conditions.
Thus the query based on a smaller metagranule will ﬁnish later. For some metagranules there could be more than one metagranule that satisﬁes the abovementioned conditions. The metagranule d has two such proper metagranules: i and pd. Eventually, the algorithm chooses the one with smaller number of records. In  we performed experiments on a database instance of size 100 GiB. They conﬁrmed the validity of this approach. This idea can be converted into an algorithm as presented in section 5. The choice of the best set of proper metagranules constitutes another interesting problem.
In such a case, the query engine 32 M. Gawarkiewicz, P. Wi´sniewski, and K. Stencel Fig. 1. 1. The query to ﬁnd twenty best customers SELECT c u s t . c i d , SUM( i n l . p r i c e ∗ i n l . q ty ) FROM c u s t JOIN i n v USING ( c i d ) JOIN i n l USING ( i n v i d ) GROUP BY c u s t . c i d ORDER BY SUM( i n l . p r i c e ∗ i n l . q ty ) DESC LIMIT 2 0 ; simply collects twenty tail entries from this index (provided it is stored in the ascending order). The algorithms presented in this paper can automatically detect such an optimisation opportunity and suggest creating the corresponding materialized aggregate and its index.