Oracle International Corporation

Richard James Anderson, Jr

Siva Ravada

Ying Hu

Richard L Frank

Gopalan Arun

Stephen Klein

Bhuvan Bamba

William Havinden Bridge, Jr

William Alan Wright

Daniel Geringer

Barbara A Benton

Mahesh Baburao Girkar

Joydip Kundu

Parthiban Thilagar

Patrick H Fry

Steve Lee

Raymond Lawrence Pfau

Joseph Edward Errede

Rabah Mediouni

Gopolan Arun

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.

Methods for processing within-distance queries

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.

Methods for query processing of topological relationships among complex spatial objects

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.

LIDAR model with hybrid-columnar format and no indexes for spatial searches

Systems, methods, and other embodiments associated with index-based optimization of geometric figured-related queries are described. In one embodiment, a method includes receiving two points selected from a corpus of spatial data. A hierarchical index on the data is accessed to choose candidate nodes. The index is a hierarchical arrangement of nodes arranged in paths from root node entries to leaf node entries such that each node is contained in all nodes in a path leading to the node. The method includes determining a spatial relationship between the two points and the candidate nodes in the index. The candidate nodes are a proper subset of the nodes in the index, such that the spatial relationship is not determined between the two points and some non-candidate nodes. A candidate node is selected based on the determined angles for processing related to construction of a geometric figure describing the spatial data.

Index-based optimization of convex hull and minimum bounding circle queries

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.

Memory-efficient spatial histogram construction

Techniques are described for generating histograms for a multidimensional space. In the presence of large spatial objects, fuzzy splitting techniques are utilized to recursively divide the multidimensional space into partitions, where a single spatial object may belong to multiple partitions. Large spatial objects are essentially broken down into smaller objects that may allow for more efficient partitioning of the multidimensional space. A count of spatial objects in each partition yields a spatial histogram. A spatial object that belongs to multiple partitions may have a weighted count for each of the multiple partitions, based on the extent to which the spatial object overlaps with each partition. Thus, an object that is split among a handful of partitions will only contribute a fraction of a count to each partition. Small partitions having relatively few objects are avoided by refusing to subdivide a partition whose members drop below a threshold number.

Constructing multidimensional histograms for complex spatial geometry objects

Systems, methods, and other embodiments associated with shared error searching for web resource requests are described. A web resource request that includes one or more request strings is received and a error detection directive that identifies a first type of error to be located in a specified request string component is accessed. At least a portion of a first request string that corresponds to the specified request string component is searched, in a single pass, for the first type of error and other types of errors. Results with respect to the first error type are returned while occurrences of the first and other types of errors for are recorded for responding to subsequent error detection directives. Thus, a subsequent error detection directive for the other types of errors in the first request string component may be processed without re-searching the portion of the first request string already searched with respect to the first error detection directive.

Shared error searching

A data recovery methodology with bound transaction data loss is described in which a database operator is allowed to set a bound that limits the number of transactions that can be lost. Transactions are placed in a buffer to be sent asynchronously to the standby system and synchronized based on the predetermined bound and on the number of transactions currently in the buffer.

Disaster recovery with bounded data loss

A method for providing data integrity of a database system. A standby database is selected to replace a failed primary database. At least one redo log file having at least one data transaction is selected to be applied to the selected standby database. The selected standby database is updated with the data transaction from the selected redo log file if an identification code in the redo log file matches an identification code in the standby database.

Reliable standby database failover

A method for selectively caching data in a computer network. Initially, data objects which are anticipated as being accessed only once or seldomly accessed are designated as being exempt from being cached. When a read request is generated, the cache controller reads the requested data object from the cache memory if it currently resides in the cache memory. However, if the requested data object cannot be found in the cache memory, it is read from a mass storage device. Thereupon, the cache controller determines whether the requested data object is to be cached or is exempt from being cached. If the data object is exempt from being cached, it is loaded directly into a local memory and is not stored in the cache. This provides improved cache utilization because only objects that are used multiple times are entered in the cache. Furthermore, processing overhead is minimized by reducing unnecessary cache insertion and purging operations. In addition, I/O operations are minimized by increasing the likelihood that hot objects are retained in the cache longer at the expense of infrequently used objects.

Method and apparatus for selective data caching implemented with

A method for performing a checkpointing operation in a client/server computer system for safeguarding data in case of a failure. The records of a database are stored in a mass storage device, such as a hard disk drive array. A separate disk drive is dedicated for use only in conjunction with checkpointing. Periodically, when a checkpoint process is initiated, the server writes a number of its modified records to checkpoint files which are stored by the dedicated checkpoint disk drive. The write operation is performed through one or more sequential I/O operations. Thus, the modified records are stored in consecutive sectors of the hard disk drive. If the server becomes disabled, the data can be recovered by reading the contents of the most recent checkpoint files and loading the contents sequentially back to the server's main memory.

High-speed database checkpointing through sequential I/O to disk

In a relational database management system (RDBMS), a method of issuing input/output tasks (I/Os) which store record information from a buffer to an after image journal (AIJ) file of a durable disk (the AIJ device) where a group commit size is dynamically adapted to the workload of the AIJ device and to the character and volume of data written to the AIJ file. Record information contains data records (including roll back records) and/or commit records that together form database transactions. A commit record written to the AIJ file indicates that data modifications and/or additions embodied in data records associated with the commit record are durable in the RDBMS in that they are stored in a durable media and are recoverable. Rather than issuing I/Os to the disk based on a fixed timer or a fixed record count, the system writes to the AIJ file based on three workload characteristics: 1) the character of the record information received (data or commit record); 2) the AIJ file throughput, measured based on the buffer contents; and 3) the workload of the I/O device (busy or idle). The present invention avoids making a data dependent server process wait unnecessarily if the AIJ device is not busy, thereby improving response time without overloading the AIJ, and minimizes AIJ I/O in heavy workload situations by making the group commit size as large as possible without idling the AIJ device. The system adapts to a changing workload to provide improved response time and throughput.

Method and system for workload based group committing for improved

In a client/server computer system, a method for writing modified data in a cache memory back to a database residing in a hard disk drive. Rather than writing back all of the modified data as part of a checkpointing operation, the present invention designates an amount of the cache memory that is to be cleared for a pre-determined time interval. The amount of cache memory to be cleared is based on an estimate of how much new data is anticipated to be cached. Thereby, just enough memory is cleared and made available so as to accommodate the storage of new data. For the modified data which are to be written back to the database, a lazy writeback operation is utilized.

Growing community of inventors

Nashua, NH, United States of America

Richard James Anderson, Jr