An array-based algorithm for simultaneous multidimensional aggregates
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Allocating Storage for Extendible Arrays
Journal of the ACM (JACM)
Multidimensional Database Technology
Computer
Efficient Aggregation Algorithms for Compressed Data Warehouses
IEEE Transactions on Knowledge and Data Engineering
Efficient Organization of Large Multidimensional Arrays
Proceedings of the Tenth International Conference on Data Engineering
Modeling Multidimensional Databases, Cubes and Cube Operations
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
On Improving the Performance of Sparse Matrix-Vector Multiplication
HIPC '97 Proceedings of the Fourth International Conference on High-Performance Computing
IEEE Transactions on Computers
Flexibly Resizable Multidimensional Arrays
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
An extendible multidimensional array system for MOLAP
Proceedings of the 2006 ACM symposium on Applied computing
Exploiting versions for on-line data warehouse maintenance in MOLAP servers
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
An efficient implementation for MOLAP basic data structure and its evaluation
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Index structures for data warehouses
Index structures for data warehouses
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Multidimensional arrays are becoming important data structure for handling large scale multidimensional data; e.g., in scientific databases or MOLAP databases. Due to the increasing size of the data warehouses and high degree of sparsity, it becomes necessity to develop a suitable scheme to compress the multidimensional array in an efficient way so that it takes comparatively low memory storage. In this paper, we propose a new compression scheme namely extendible array based Compressed Row Storage (EaCRS), for large multidimensional sparse array. The main idea of this scheme is to compress the subarrays found from the existing extendible array using CRS method. To evaluate the proposed scheme, we compare it to the CRS on Traditional multidimensional array (TMA). Both analytical analysis and experimental test were conducted. In the analytical analysis, we analyze the CRS and EaCRS schemes in terms of the space requirement and the maximum range of usable data density for practical applications. The analytical analysis and experimental results show that the EaCRS scheme is superior to the CRS scheme for all the evaluated criteria.