Abstract: An improved database data structure and datatype is disclosed for storing, manipulating and accessing multidimensional spatial data in a database. Binary helical hyperspatial code (HH CODE) is used to represent data of N dimensions. The binary HH CODE data structure maintains the dimensional organization of multidimensional data within the data itself. Spatial data is stored using BH code which is modeled as a N-tree structure derived using recursive decomposition. A high water mark is set as the upper limit for data volume which may be stored in any one partition. As data stored in a partition exceeds the high water mark, the data is decomposed into child partitions such that no partition data stores exceed the high water mark. If the high water mark is exceeded, additional child partitions are automatically created and the parent table is not retained. A data structure is defined which represents the partitioned tables and BH code values.

Abstract: A method and mechanism for performing a spatial join between two sets of objects employs a two-pass primary filter. The objects are decomposed into variable-sized cells no larger than a predetermined cell size and stored in respective spatial indexes. The spatial indexes include a code for the variable-size cells of the object and a code for the fixed-size supercell of the variable-size cells. The first pass can be implemented as an equijoin filtering operation using the fixed-size cell codes corresponding to the predetermined cell size, and the second pass as a join operation using the variable-size cell codes at smaller cell sizes.