Abstract: A method, information processing system, and computer program storage product for compressing sorted values is disclosed. At least a first prefix and a second prefix in a plurality of prefixes are compared. Each prefix comprises at least a portion of a plurality of sorted values. A respective prefix comprises a set of consecutive characters including at least a first character of a respective sorted value. The respective sorted value further comprising a respective suffix comprising consecutive characters of the respective sorted value that are after the respective prefix. At least a respective first character of the first prefix and a respective first character of the second prefix are determined to be substantially identical. The first prefix is merged with the second prefix into a single prefix comprising the first character. A set of suffixes associated with the first prefix is updated to reflect an association with the second prefix.

Abstract: A method and system utilizes a hierarchical bitmap structure to represent deleted data sets. Each level in the hierarchical bitmap structure may have progressively larger size and represent finer granularity of number of data blocks than its parent level. A method in one aspect may comprise allocating a first level bitmap having size equal to a register on a processor, each bit in the first level bitmap representing a plurality of blocks of data in a database, and allocating one or more pointers corresponding to said plurality of bits in the first level bitmap, said one or more pointers being allocated to point to a sub bitmap generated after a data block is deleted but before the index corresponding to the data block is cleaned.

Abstract: A computer implemented method, apparatus, and computer usable program code for deleting rows in a multidimensional clustering database. A multidimensional clustering processor receives a request to delete a set of multidimensionally clustered data. The multidimensional clustering processor determines whether all multidimensionally clustered data is located in a block. Responsive to all multidimensionally clustered data qualifying for deletion, the multidimensional clustering processor deletes all data in the block to delete the set of multidimensionally clustered data.

Abstract: A method, information processing system, and computer readable storage product estimate a compression factor. A set of key values within an index are analyzed. Each key value is associated with a record identifier (“RID”) list comprising a set of RIDs. The index is in an uncompressed format and includes a total byte length. A number of RIDs associated with each key value is estimated for each key value in the set of key values. A total byte length for all RID deltas between each at least two consecutive RIDs within a RID list is estimated for each RID list based on the number of RIDs that have been determined. The total byte length estimated for each RID list is accumulated. A compression factor associated with the index is determined by dividing the total byte length that has been accumulated by the byte length of the index.

Abstract: Techniques are disclosed for encoding a variable length structure such that it facilitates forward and reverse scans of a list of such structures as needed. While the techniques are applicable to a wide variety of applications, they are particularly well-suited for use with structures such as those found in compressed database indexes. For example, a computer-implemented method for processing one or more variable length data structures includes the following steps. Each variable length data structure is obtained. Each variable length structure comprises one or more data block. A variable length encoding process is applied to the one or more blocks of each variable length data structure which comprises setting a continuation data value in each block to a first value or a second value, wherein the setting of the continuation data values enables bi-directional scanning of each variable length structure.

Abstract: Techniques are disclosed for selecting a delete-safe compression method for a plurality of delta encoded data values (e.g., delta encoded integers or deltas). For example, a computer-implemented method for selecting an optimal delete-safe compression algorithm from among two or more compression algorithms for use on a plurality of delta encoded data values includes the following steps. The maximum number of data values eliminated by each of the two or more compression algorithms is computed. For the plurality of delta encoded data values to be compressed, the minimum size of the plurality of delta encoded data values before compression thereof is computed. A delete-safe threshold value is computed based on the minimum size of the plurality of delta encoded data values. Then, the compression algorithm is selected from the two or more compression algorithms that achieves the delete-safe threshold value.

Abstract: A computer implemented method, apparatus, and computer usable program code for detecting monotonicity. A determination is made as to whether a function that is assumed to be monotonic will remain monotonic after performing an operation in response to receiving the operation. The operation is allowed to be performed in response to a determination that the function will remain monotonic after performing the operation.

Abstract: A method for accelerating range queries using periodic monotonic properties of non-monotonic functions including mapping a base column x to an existing index on a column y that is correlated with column x through a periodic piecewise monotonic function F(x), rewriting an index construction statement to force the existing index on column y to track a periodic piecewise monotonic property by assigning identical values of F(x) to different periods to different ranges to create an annotated index, and rewriting range queries over the annotated index on F(x) by modifying a derived predicate.

Abstract: Disclosed is a data processing system implemented method, a data processing system and an article of manufacture for improving execution efficiency of a database workload to be executed against a database. The database includes database tables, and the database workload identifies at least one of the database tables. The data processing system includes an identification module for identifying candidate database tables being identifiable in the database workload, the identified candidate database tables being eligible for organization under a clustering schema, a selection module for selecting the identified candidate tables according to whether execution of the database workload is improved if the selected identified candidate table is organized according to the clustering scheme, and an organization module for organizing the clustering schema of the selected organized identified candidate tables prior to the database workload being execution against the database.

Abstract: An embodiment of the present invention provides a computer system including a first memory and a second memory, where the first memory is substantially faster than the second memory. A method includes steps of: inspecting a request queue for block requests from a plurality of concurrent calling processes, the request queue including a plurality of block requests not yet processed by any of the plurality of concurrent calling processes; retrieving one of the plurality of block requests, wherein each block is accessed at most once by each calling process; determining whether the retrieved block request can be fulfilled from the first memory; and returning the retrieved block to the calling process whose state indicates that the block is needed if the retrieved block request can be fulfilled from the first memory.

Abstract: An index scan processor and method to perform concurrent scans of stored indexed data. An indexed data scanner performs a first scan of stored data by sequentially scanning through an index data structure and maintains, over a duration of the first scan, a first scan current scan location within the index data structure that indicates a currently accessed record within the stored data structure for the first scan. A scan manager accepts a request for a second scan of the stored data, determines, during the performing the first scan, a starting index scan location within the index data structure for the second scan that is sufficiently near the first scan current index scan location to cause records indicated by the starting location index to be stored within a buffer due to the performing the first scan, and starts the second scan at the starting location and proceeding to the second end key.

Abstract: A method and processor to determine distances between multiple index driven scan operations. A first anchor index entry is identified during a first index scan and stored. A first number of index entries between the first anchor index entry and a first index scan location being processed by a first index scan is determined based on information maintained external to an index structure. A determination is made of second number of index entries between the first anchor index entry and a second index scan location being processed by a second index scan executing concurrently with the first index scan based on information maintained external to the index structure. A distance between the first index scan location and the second index scan location is calculated as equal to a difference between the first number of index entries and the second number of index entries.

Abstract: Disclosed is a data processing system implemented method, a data processing system and an article of manufacture for improving execution efficiency of a database workload to be executed against a database. The database includes database tables, and the database workload identifies at least one of the database tables. The data processing system includes an identification module for identifying candidate database tables being identifiable in the database workload, the identified candidate database tables being eligible for organization under a clustering schema, a selection module for selecting the identified candidate tables according to whether execution of the database workload is improved if the selected identified candidate table is organized according to the clustering scheme, and an organization module for organizing the clustering schema of the selected organized identified candidate tables prior to the database workload being execution against the database.

Abstract: Key performance indicator (KPI) expressions are rewritten using metric hierarchies. A node label is associated with each node in the metric hierarchies, the metric hierarchies arranged in arbitrary trees. Node labels associated with each term in a KPI expression are retrieved, and the terms in the KPI expression are sorted according to the node labels. The terms are grouped according to the node labels, and a collection of groups that covers all the terms in the KPI expression is found. Overlaps in the covering groups may be minimized.

Abstract: A computer implemented method, apparatus, and computer usable program code for deleting rows in a multidimensional clustering database. A multidimensional clustering processor receives a request to delete a set of multidimensionally clustered data. The multidimensional clustering processor determines whether all multidimensionally clustered data is located in a block. Responsive to all multidimensionally clustered data qualifying for deletion, the multidimensional clustering processor deletes all data in the block to delete the set of multidimensionally clustered data.

Abstract: Shared sub-structures are found within a collection of multiple hierarchies. A label is associated with each node in the collection of hierarchies, and an inverted index mapping node labels to lists of hierarchies is created. Each pair of hierarchies in each hierarchy list is iterated over in a certain order, and a shared substructure is found between a pair of hierarchies using the node labels. When more than one shared substructure is found, the substructures are merged into a shared subtree.

Abstract: A method and system utilizes a hierarchical bitmap structure to represent deleted data sets. Each level in the hierarchical bitmap structure may have progressively larger size and represent finer granularity of number of data blocks than its parent level. A method in one aspect may comprise allocating a first level bitmap having size equal to a register on a processor, each bit in the first level bitmap representing a plurality of blocks of data in a database, and allocating one or more pointers corresponding to said plurality of bits in the first level bitmap, said one or more pointers being allocated to point to a sub bitmap generated after a data block is deleted but before the index corresponding to the data block is cleaned.

Abstract: A computer implemented method, apparatus, and computer usable program code for detecting monotonicity. A determination is made as to whether a function that is assumed to be monotonic will remain monotonic after performing an operation in response to receiving the operation. The operation is allowed to be performed in response to a determination that the function will remain monotonic after performing the operation.

Abstract: A device for limiting access to data in a database includes an input for receiving a request to access data in a database and a processor that is communicatively coupled to the input and allows access to the data in the database. A data counter for counting an instantaneous rate of data flow and/or a volume of data accessed and a comparator for determining if the data flow and/or the volume of data accessed in the database exceeds a previously specified value is also included, wherein the processor disallows access to the data in the database in response to the instantaneous rate and/or the volume of data exceeding the previously specified value.

Abstract: Disclosed are a method, information processing system, and computer readable medium for managing table scan processes. The method includes monitoring a plurality of storage medium table scan processes. Each storage medium table scan process in the plurality of storage medium table scan processes is placed into a plurality of scan groups based on storage medium pages to be scanned by each of the storage medium table scan processes. Each storage medium table scan process in a scan group can share data within a storage medium page.