An Efficient Encoding Scheme to Handle the Address Space Overflow for Large Multidimensional Arrays

We present a new implementation scheme of multidimensional array for handling large scale high dimensional datasets that grows incrementally. The scheme implements a dynamic multidimensional extendible array employing a set of two dimensional extendible arrays. The multidimensional arrays provide many advantages but it has some problems as well. The Traditional Multidimensional array is not dynamic extendible. Again, if the length of dimension and number of dimension of a multidimensional array is large then the address space for the array overflows quickly. In this paper, we propose a solution against the essential problem of address space overflow for handling large scale multidimensional datasets using our implementation model. We also propose a record encoding scheme based on our model for representing relational tables using multidimensional array. We evaluate our proposed scheme by comparing with Traditional Multidimensional Array (TMA) for different operations and find a reasonable delay of address space overflow with no retrieval penalty. We also compare the encoded scheme with traditional scheme and find that proposed encoded scheme performs better on range retrieval for sparse array. Index Terms Multidimensional Array, Extendible Array, Address space overflow, Karnaugh Map, MOLAP, Dynamic Extension and Sparse Array.