Abstract:
An optimized method of processing queries requesting a description of a spatial relationship between a test geometry and a query geometry, such as points, lines, polygons, and collections thereof, is disclosed. A first part of the method finds a first spatial relationship between a minimum bounding rectangle (MBR) of the test geometry and an In-Memory R-tree (IMR-tree) built to describe the query geometry. If the first relationship does not specify the requested description, then a second part of the method uses the IMR-tree of the query geometry to find a second spatial relationship between the test geometry itself and the query geometry. Optimizations are applied to the first part and to the second part. Optimizations in the second part depend on the test geometry.
Abstract:
An optimized method of processing queries requesting a description of a spatial relationship between a test geometry and a query geometry, such as points, lines, polygons, and collections thereof, is disclosed. A first part of the method finds a first spatial relationship between a minimum bounding rectangle (MBR) of the test geometry and an In-Memory R-tree (IMR-tree) built to describe the query geometry. If the first relationship does not specify the requested description, then a second part of the method uses the IMR-tree of the query geometry to find a second spatial relationship between the test geometry itself and the query geometry. Optimizations are applied to the first part and to the second part. Optimizations in the second part depend on the test geometry.
Abstract:
Techniques are described for memory-efficient spatial histogram construction. A hierarchical spatial index has leaf nodes and non-leaf nodes, each leaf node representing a bounding region containing a spatial object, each non-leaf node representing a bounding region at least partially containing one or more spatial objects. A plurality of selected nodes is selected from the plurality of non-leaf nodes. The plurality of selected nodes includes an ancestor of each leaf node. For each particular node in the plurality of selected nodes, a weight is determined. The weight is based on the number of spatial objects contained within the bounding region of the particular node. A spatial partitioning of the plurality of selected nodes is determined. A spatial histogram is generated based on the spatial partitioning of the weights of the plurality of selected nodes.
Abstract:
Techniques and systems for processing within-distance queries are provided. A query for geometry objects within a query distance of a query geometry is received. An in-memory R-tree (IMR-tree) is generated for the query geometry. The IMR-tree includes nodes corresponding to edges of the query geometry. An R-tree index for a plurality of candidate geometries is accessed. At least one node of the R-tree index is processed by: generating an expanded bounding geometry based on the query distance, and using the IMR-tree to determine a topological relationship between the expanded bounding geometry and the query geometry. When the expanded bounding geometry intersects the query geometry, if at least one within-distance test is satisfied, the candidate geometries associated with the selected node are added to a result set. Otherwise, if the selected node is a non-leaf node of the R-tree index, child nodes of the selected node are processed.
Abstract:
Techniques and systems for processing within-distance queries are provided. A query for geometry objects within a query distance of a query geometry is received. An in-memory R-tree (IMR-tree) is generated for the query geometry. The IMR-tree includes nodes corresponding to edges of the query geometry. An R-tree index for a plurality of candidate geometries is accessed. At least one node of the R-tree index is processed by: generating an expanded bounding geometry based on the query distance, and using the IMR-tree to determine a topological relationship between the expanded bounding geometry and the query geometry. When the expanded bounding geometry intersects the query geometry, if at least one within-distance test is satisfied, the candidate geometries associated with the selected node are added to a result set. Otherwise, if the selected node is a non-leaf node of the R-tree index, child nodes of the selected node are processed.
Abstract:
A method and apparatus for querying a database table containing point spatial data and without indexes is provided. A request for point spatial data in the table includes a query window provided by the user and describing an area of interest in which the user desires the point spatial data contained therein. The query window is tiled to create interior tiles and boundary tiles. A first query is formed to determine the point spatial data contained in the interior tiles. A second query is formed to determine the point spatial data contained within the boundary tiles and also within the query window. The second query includes a function that tests to determine whether the point spatial data within a boundary tile also lies within the query window. The first and second queries are executed in part on an enhanced data storage device and the results joined and returned to the user in answer to the request.
Abstract:
Techniques are described for memory-efficient spatial histogram construction. A hierarchical spatial index has leaf nodes and non-leaf nodes, each leaf node representing a bounding region containing a spatial object, each non-leaf node representing a bounding region at least partially containing one or more spatial objects. A plurality of selected nodes is selected from the plurality of non-leaf nodes. The plurality of selected nodes includes an ancestor of each leaf node. For each particular node in the plurality of selected nodes, a weight is determined. The weight is based on the number of spatial objects contained within the bounding region of the particular node. A spatial partitioning of the plurality of selected nodes is determined. A spatial histogram is generated based on the spatial partitioning of the weights of the plurality of selected nodes.
Abstract:
An optimized method of processing queries requesting a description of a spatial relationship between a test geometry and a query geometry, such as points, lines, polygons, and collections thereof, is disclosed. A first part of the method finds a first spatial relationship between a minimum bounding rectangle (MBR) of the test geometry and an In-Memory R-tree (IMR-tree) built to describe the query geometry. If the first relationship does not specify the requested description, then a second part of the method uses the IMR-tree of the query geometry to find a second spatial relationship between the test geometry itself and the query geometry. Optimizations are applied to the first part and to the second part. Optimizations in the second part depend on the test geometry.
Abstract:
A method and apparatus for querying a database table containing point spatial data and without indexes is provided. A request for point spatial data in the table includes a query window provided by the user and describing an area of interest in which the user desires the point spatial data contained therein. The query window is tiled to create interior tiles and boundary tiles. A first query is formed to determine the point spatial data contained in the interior tiles. A second query is formed to determine the point spatial data contained within the boundary tiles and also within the query window. The second query includes a function that tests to determine whether the point spatial data within a boundary tile also lies within the query window. The first and second queries are executed in part on an enhanced data storage device and the results joined and returned to the user in answer to the request.
Abstract:
An optimized method of processing queries requesting a description of a spatial relationship between a test geometry and a query geometry, such as points, lines, polygons, and collections thereof, is disclosed. A first part of the method finds a first spatial relationship between a minimum bounding rectangle (MBR) of the test geometry and an In-Memory R-tree (IMR-tree) built to describe the query geometry. If the first relationship does not specify the requested description, then a second part of the method uses the IMR-tree of the query geometry to find a second spatial relationship between the test geometry itself and the query geometry. Optimizations are applied to the first part and to the second part. Optimizations in the second part depend on the test geometry.