Titlebook: Data Warehousing and Knowledge Discovery; 13th International C Alfredo Cuzzocrea,Umeshwar Dayal Conference proceedings 2011 Springer-Verlag

lactic

Main Concepts of the Graphical Kernel Systemiciently processing different types of dimensions. The paper describes the integration of ETLMR with a MapReduce framework and evaluates its performance on large realistic data sets. The experimental results show that ETLMR achieves very good scalability and compares favourably with other MapReduce

過(guò)份艷麗

Computer Graphics and Geometric Modelingvides very fast query processing. In our work we show how it is possible to use this massive data ordering/sorting in order to optimize queries for high speed, even without the use of data compression (therefore also avoiding compression/decompression overheads). We dedicate our attention to sort co

Ethics

Computer Graphics for Artists IIion results prove that our vertical splitting scheme can reduce retrieval I/O cost, while expanding the required logical address space to store large scale multidimensional datasets. Our method far outperforms PostgreSQL and is fairly better than UB tree in retrieval time. The splitting causes incre

accessory

Computer Graphics for Artists IIhe page type is represented by the tag. While the classic MapReduce can handle this class of queries, it requires effort and possibly advanced programming skills for efficient implementations. For example, should the tag form a compound object with the key or the value? Our formalism makes it simple

明確

ONE: A Predictable and Scalable DW Modelalled ONE) that physically stores the whole star schema into a single relation, providing a predictable and scalable alternative to the star schema model. We use the TPC-H benchmark to evaluate ONE and the star schema model, assessing both the required storage size and query execution time.

Canvas

OLAP Formulations for Supporting Complex Spatial Objects in Data Warehouses employs them as first class citizens in the data cube. Further, new OLAP constructs to help define, manipulate, query and analyze spatial data have also been presented. Overall, the aim of this paper is to leverage support for spatial data in OLAP cubes and pave the way for the development of a use

一夫一妻制

Bouquet

Contend

VarDB: High-Performance Warehouse Processing with Massive Ordering and Binary Searchvides very fast query processing. In our work we show how it is possible to use this massive data ordering/sorting in order to optimize queries for high speed, even without the use of data compression (therefore also avoiding compression/decompression overheads). We dedicate our attention to sort co

Choreography

Implementing Vertical Splitting for Large Scale Multidimensional Datasets and Its Evaluationsion results prove that our vertical splitting scheme can reduce retrieval I/O cost, while expanding the required logical address space to store large scale multidimensional datasets. Our method far outperforms PostgreSQL and is fairly better than UB tree in retrieval time. The splitting causes incre