Abstract: Methods that boot a secondary operating system (O/S) kernel with reclaimed primary kernel memory are disclosed herein. One method includes booting, via a processor performing a boot algorithm, a secondary kernel for an O/S in response to a primary kernel for the O/S going offline, in which the secondary kernel is configured to be loaded to a reserved memory area. The method further includes reclaiming memory space from the primary kernel for use in booting the secondary kernel in response to a determination that the reserved memory area includes insufficient memory space for completing the boot algorithm. Also disclosed herein are apparatus, systems, and computer program products that can include, perform, and/or implement the methods for providing a secondary kernel that includes a reserved area in memory.

Abstract: Embodiments of the present disclosure facilitate handling corrected memory errors on kernel text. An example computer-implemented method includes identifying a correctable error (CE) in an error memory location of a memory and a kernel function impacted by the CE. The kernel function includes a plurality of instructions including a first instruction of the kernel function at a first physical location in a first region of the memory. The first region includes the error memory location. The plurality of instruction is loaded to a second region of the memory. The loading includes storing the first instruction of the kernel function at a second physical location in the second region of the memory. The first physical location in the first region of the memory is updated to include an instruction to branch to the second physical location in the second region of the memory.

Abstract: Methods that boot a secondary operating system (O/S) kernel with reclaimed primary kernel memory are disclosed herein. One method includes booting, via a processor performing a boot algorithm, a secondary kernel for an O/S in response to a primary kernel for the O/S going offline, in which the secondary kernel is configured to be loaded to a reserved memory area. The method further includes reclaiming memory space from the primary kernel for use in booting the secondary kernel in response to a determination that the reserved memory area includes insufficient memory space for completing the boot algorithm. Also disclosed herein are apparatus, systems, and computer program products that can include, perform, and/or implement the methods for providing a secondary kernel that includes a reserved area in memory.

Abstract: Embodiments of the present disclosure facilitate handling corrected memory errors on kernel text. An example computer-implemented method includes identifying a correctable error (CE) in an error memory location of a memory and a kernel function impacted by the CE. The kernel function includes a plurality of instructions including a first instruction of the kernel function at a first physical location in a first region of the memory. The first region includes the error memory location. The plurality of instruction is loaded to a second region of the memory. The loading includes storing the first instruction of the kernel function at a second physical location in the second region of the memory. The first physical location in the first region of the memory is updated to include an instruction to branch to the second physical location in the second region of the memory.

Abstract: A computer-implemented method of creating a data mining model in a database management system comprises accepting a database language statement at the database management system, the database language statement indicating a dataset and a data mining model to be created from the dataset, and creating, in the database management system, the indicated data mining model using the indicated dataset, wherein creation and application of the data mining model does not require moving data to a separate data mining engine.

Abstract: Binning of predictor values used for generating a data mining model provides useful reduction in memory footprint and computation during the computationally dominant decision tree build phase, but reduces the information loss of the model and reduces the introduction of false information artifacts. A method of binning data in a database for data mining modeling in a database system, the data stored in a database table in the database system, the data mining modeling having selected at least one predictor and one target for the data, the data including a plurality of values of the predictor and a plurality of values of the target, the method comprises constructing a binary tree for the predictor that splits the values of the predictor into a plurality of portions, pruning the binary tree, and defining as bins of the predictor leaves of the tree that remain after pruning, each leaf of the tree representing a portion of the values of the predictor.

Abstract: A computer-implemented method of creating a data mining model in a database management system comprises accepting a database language statement at the database management system, the database language statement indicating a dataset and a data mining model to be created from the dataset, and creating, in the database management system, the indicated data mining model using the indicated dataset, wherein creation and application of the data mining model does not require moving data to a separate data mining engine.

Abstract: Decision trees are efficiently represented in a relational database. A computer-implemented method of representing a decision tree model in relational form comprises providing a directed acyclic graph comprising a plurality of nodes and a plurality of links, each link connecting a plurality of nodes, encoding a tree structure by including in each node a parent-child relationship of the node with other nodes, encoding in each node information relating to a split represented by the node, the split information including a splitting predictor and a split value, and encoding in each node a target histogram.

Abstract: A method, system, and computer program product for counting predictor-target pairs for a decision tree model provides the capability to generate count tables that is quicker and more efficient than previous techniques. A method of counting predictor-target pairs for a decision tree model, the decision tree model based on data stored in a database, the data comprising a plurality of rows of data, at least one predictor and at least one target, comprises generating a bitmap for each split node of data stored in a database system by intersecting a parent node bitmap and a bitmap of a predictor that satisfies a condition of the node, intersecting each split node bitmap with each predictor bitmap and with each target bitmap to form intersected bitmaps, and counting bits of each intersected bitmap to generate a count of predictor-target pairs.

Abstract: A method, system, and computer program product for counting predictor-target pairs for a decision tree model provides the capability to generate count tables that is quicker and more efficient than previous techniques. A method of counting predictor-target pairs for a decision tree model, the decision tree model based on data stored in a database, the data comprising a plurality of rows of data, at least one predictor and at least one target, comprises generating a bitmap for each split node of data stored in a database system by intersecting a parent node bitmap and a bitmap of a predictor that satisfies a condition of the node, intersecting each split node bitmap with each predictor bitmap and with each target bitmap to form intersected bitmaps, and counting bits of each intersected bitmap to generate a count of predictor-target pairs.

Abstract: Binning of predictor values used for generating a data mining model provides useful reduction in memory footprint and computation during the computationally dominant decision tree build phase, but reduces the information loss of the model and reduces the introduction of false information artifacts. A method of binning data in a database for data mining modeling in a database system, the data stored in a database table in the database system, the data mining modeling having selected at least one predictor and one target for the data, the data including a plurality of values of the predictor and a plurality of values of the target, the method comprises constructing a binary tree for the predictor that splits the values of the predictor into a plurality of portions, pruning the binary tree, and defining as bins of the predictor leaves of the tree that remain after pruning, each leaf of the tree representing a portion of the values of the predictor.

Abstract: Decision trees are efficiently represented in a relational database. A computer-implemented method of representing a decision tree model in relational form comprises providing a directed acyclic graph comprising a plurality of nodes and a plurality of links, each link connecting a plurality of nodes, encoding a tree structure by including in each node a parent-child relationship of the node with other nodes, encoding in each node information relating to a split represented by the node, the split information including a splitting predictor and a split value, and encoding in each node a target histogram.

Abstract: An implementation of NMF functionality integrated into a relational database management system provides the capability to apply NMF to relational datasets and to sparse datasets. A database management system comprises a multi-dimensional data table operable to store data and a processing unit operable to perform non-negative matrix factorization on data stored in the multi-dimensional data table and to generate a plurality of data tables, each data table being smaller than the multi-dimensional data table and having reduced dimensionality relative to the multi-dimensional data table. The multi-dimensional data table may be a relational data table.

Abstract: An integrated solution in which BLAST functionality is integrated into a DBMS provides improved performance and scalability over the conventional approach, in addition to reducing the required hardware resources and reducing the cost of the system. In a database management system, a system for sequence matching and alignment comprises a database table storing sequence information comprising target sequences, a query sequence, a table function operable to accept the query sequence and match the query sequence with at least one target sequence stored in the database table, and a structured query language query referencing a database table storing sequence information comprising target sequences, a query sequence, and a table function, the structured query language query evaluatable by the database management system.

Abstract: A mapping mechanism for a primary B+tree in a database management system. The primary B+tree includes a plurality of rows. The mapping mechanism includes introducing a mapping table that includes a plurality of rows, including a row for each row of the primary B+tree, and that stores the logical identifier of the corresponding primary B+tree row. In addition, reverse mapping is provided by augmenting a primary B+tree to include in each primary B+tree row a physical row identifier of the corresponding mapping table row. An auxiliary structure created on a primary B+tree can make use of the proposed mapping mechanism. Specifically, the auxiliary structures refers to primary B+tree rows indirectly by storing the physical row identifier of the corresponding mapping table row.