Abstract: A computer implemented method and apparatus for enhancing access to a file and communicating a file over a communications network using an indirect link. An indirect link is a logical hyperlink identifying a file to be retrieved, not by its electronic address, but by a logical representation. The link may denote the server on which the file exists, but does not identify the file's full address. Rather, the server or a proxy machine uses a look-up table which relates a logical link to an actual electronic address. This system helps minimize broken links, since a file can still be located on the server and accessed even if it has been relocated on the server since the link was established.

Abstract: The present invention provides various methods and apparatus for providing accurate estimates for point and range queries over two-dimensional rectangular data. However, the techniques of the present invention for rectangular data can be applied to data of other shapes, point data, or linear data. The present invention provides several grouping techniques for the approximating of spatial data. A method is disclosed for grouping a plurality of spatial inputs into a plurality of buckets. In one form of the present invention the plurality of spatial inputs, is grouped based on an equi-area partitioning technique. The equi-area partitioning technique can use the longest dimension of a bucket or bounding polygon as the criteria for splitting into further buckets or bounding polygons. An equi-count technique can also be used wherein the buckets are split using the highest projected spatial input count along a dimension as a splitting criteria. The bounding polygons may be minimum bounding rectangles.

Abstract: A method of using an algorithm to partition a multi-dimensional data set into a minimum number of rectangular-shaped partitions that can be processed more quickly than the non-partitioned data set while satisfying certain specified performance constraints.

Abstract: A novel and unique method of approximating the data cube and summarizing database data in order to provide quick and approximate answers to aggregate queries by precomputing a summary of the data cube using histograms and answering queries using the substantially smaller summary. A unique method according to the present invention provides for identifying accurate histogram classes and distributing the space among the histograms on various sub-cubes such that the errors are minimized, while at the same time computer resources are maximized.

Abstract: A novel and unique method, apparatus and programmed storage medium for approximating large data distributions of a database in order to allow a user to accurately analyze the entire data distribution using a limited amount of memory space in a reasonable amount of time. The approximation is based on partitioning the data domain into a number of regions, approximating each region using any well-known technique, and composing the errors of approximation to optimize suitable criteria for approximating the entire data distribution.

Abstract: A computer method, apparatus and programmed medium for optimizing the number of buckets, and thus minimizing the necessary amount of memory space, needed to construct a histogram of a data distribution contained within a computer database with a cumulative error bounded by a specified threshold. The method according to the present invention allows a user to determine the near-minimal memory space necessary to store an approximation of a database with a maximum error measure at most three times that specified by the user to allow the user to maximize computer resources.

Abstract: Techniques for maintaining a random sample of a relation in a database in the presence of updates to the relation. The random sample of the relation is referred to as a "backing sample," and it is maintained in the presence of insert, modify and delete operations involving the relation. When a new tuple is inserted into the relation, a sample of the given tuple is added to the backing sample if the size of the backing sample is below an upper bound. Otherwise, a randomly-selected tuple of the backing sample is replaced with the new tuple if a sample of the new tuple must be inserted into the backing sample to maintain randomness or another characteristic. When a tuple in the relation is the subject of a modify operation, the backing sample is left unchanged if the modify operation does not affect an attribute of interest to an application which uses the backing sample. Otherwise, a value field in a sample of the tuple in the backing sample is updated.

Abstract: Techniques for maintaining an approximate histogram of a relation in a database, in the presence of updates to the relation. The histogram includes a number of subsets, or "buckets," each representing at least one possible value of an attribute of the relation. Each of the subsets has a count associated therewith indicative of the frequency of occurrence of the corresponding value of the attribute. After an update to the relation, the counts associated with the subsets are compared to a threshold. If the count associated with a given subset exceeds the threshold, the given subset is separated at its median into two separate subsets. After the separation operation, the two subsets with the lowest counts are combined such that a constant number of subsets are maintained in the histogram, if the total combined count of the subsets does not exceed the threshold. If no two subsets have a total combined count which does not exceed the threshold, the histogram is recomputed from a random sample of the relation.