Abstract: A method for performing row qualification in database table retrieval and join operations. This method, referred to as bulk qualification, evaluates conditions on multiple rows in a database table at the same time, providing more efficient utilization of memory bandwidth and CPU throughput.

Abstract: One or a soft correlation of a database can be adjusted (e.g., modified, replaced, overwritten) for use with respect to one or more record(s) of the database associated with the soft correlation, by considering at least one or more violations of the soft correlations in the one or more of records database records associated with the soft correlation. In addition, an adjusted soft correlation can be stored and used for optimizations of database queries pertaining to one or more records associated with the adjusted soft correlation. Typically, the adjusted soft correlation is adjusted by at least considering the violations of an original soft correlation in the one or more records relating to the database queries.

Abstract: A relational database management system (RDBMS) accepts a workload comprised of one or more queries against a relational database. The RDBMS evolves a default cost profile into a plurality of cost profiles using fixed or dynamic evolution, wherein each of the cost profiles captures one or more cost parameters for the workload. The cost profiles are represented by a multi-dimensional matrix that has one or more dimensions, and each of the dimensions represents one of the cost parameters. The RDBMS dynamically determines which of the cost profiles is an optimal cost profile for the workload by mapping the cost profiles to the workload using a random walk scoring algorithm or a biased walk scoring algorithm that searches the multi-dimensional matrix to identify the optimal cost profile. The RDBMS selects and performs one or more query execution plans for the workload based on the optimal cost profile for the workload.

Abstract: A data store system may include an array of persistent storage devices configured to store a plurality of data store tables. The data store system may further include a processor in communication with the storage device. The processor may receive a query containing a non-equality join condition on a first column from a first data store table and a second column on a second data store table. The processor may generate a bitmap based on the join condition. The bitmap indicate respective matches between the first column and second column in accordance with the non-equality join condition. The bitmap may also be used each time the non-equality join condition is present in another received query. A method and computer-readable medium may also be implemented.

Abstract: A system and method for determining optimal query plans within a distributed processing system. The system includes a query optimizer for receiving a query and generating a query plan for execution by the distributed processing system; a repository including statistics related to prior executed query plans; a plan execution engine for receiving and executing the query plan, collecting statistics corresponding to the query plan, and storing the statistics and optimizer usage metadata corresponding to the query plan and prior executed query plans in the repository. The system further includes a statistics advisory tool for mining the metadata to generate a collection of histogram statistics and storing said histogram statistics in the repository. When generating a query plan, the query optimizer searches the statistics repository for statistics, including histogram statistics, useful to the generation of the current query plan and uses selected statistics from the repository to generate the query plan.

Abstract: A method of operating a data store system may include identifying a non-responsive processing node from a plurality of processing nodes. The method may further include generating a new registration key in response to identifying the non-responsive processing node. The method may further include providing the new registration key to the other processing nodes of the plurality of processing nodes excluding the identified non-responsive node. Each processing node provided the new registration key may be authorized to access a plurality of storage devices of a storage array in communication with the plurality of processing nodes. A system and computer-readable medium may also be implemented.

Abstract: A computer running a database system receives one or more queries, each query comprised of parallel threads of execution working towards the common goal of completing a user request. These threads are grouped into a schedulable object called a task group. The task groups are placed within a specific multiple tier hierarchy, and database system resources and service level goals (SLGs) allocated to the task groups according to their placement within the hierarchy. The execution of requests/tasks is monitored, and resource allocations temporarily increased to critical requests that are unlikely to meet execution goals (SLGs).

Abstract: A database query to be run against a database is received by a processor. The query includes a query predicate. The query predicate includes a condition. The condition applies to a single database table. The condition is parsed to create an input vector. The input vector is submitted to a neural network. The neural network is trained to calculate the selectivity, a number of unique values (NUV) of results of applying predicates to the single database table, and a high mode frequency (HMF) of results of applying predicates to the single database table. The neural network determines the selectivity of the query predicate, an NUV for each column in the result of applying the query predicate to the single database table, and an HMF for each column in the result of applying the query predicate to the single database table.

Abstract: A table reconfiguration command is received. A READ lock is placed on the table while original table data for the table is moved from a first network location to a second network location into a temporary table according to a new map for the table. An EXCLUSIVE lock on the table is obtained, a data dictionary is modified with the new map for the table, the original table data at the first network location is deleted, and the temporary table is renamed to be the table at the second network location; then, the EXCLUSIVE lock is released.

Abstract: An apparatus, method and computer program product for query optimization in a Relational Database Management System (RDBMS), wherein an optimizer accesses a query expression repository (QER), so that the optimizer learns from previous versions of the queries to improve current and subsequent versions of the queries. The QER stores planning and execution information for QEs from the previous versions of the queries, wherein the QEs comprise table relations, intermediate results and/or final results of operations in the previous versions of the queries. The optimizer searches the QER for QEs from the query execution plans, and uses information from the QEs stored in the QER when optimizing the current and subsequent versions of the queries. The optimizer may also reuses results from the QEs stored in the QER.

Abstract: An apparatus, method and computer program product for physical database design and tuning in relational database management systems. A relational database management system executes in a computer system, wherein the relational database management system manages a relational database comprised of one or more tables storing data. A Deep Reinforcement Learning based feedback loop process also executes in the computer system for recommending one or more tuning actions for the physical database design and tuning of the relational database management system, wherein the Deep Reinforcement Learning based feedback loop process uses a neural network framework to select the tuning actions based on one or more query workloads performed by the relational database management system.

Abstract: Search spaces for obtaining query execution plans for a query are identified. The search spaces are subdivided into sub-search spaces. Searches are initiated within the sub search spaces and plan costs for competing query execution plans are noted along with search costs associated with continuing to search the sub-search spaces. A decision is made based on the plan costs and search costs for utilizing search resources as to when to terminate the searching and to select the then-existing lowest cost query execution plan as an optimal query execution plan for executing the query.

Abstract: A method is provided for predicting workload group metrics of a workload management system of a database system. The method comprises predicting a future workload group metric for a plurality of workload groups based upon historical user-load patterns. Each workload group has a priority that is different from priority of other workload groups.

Abstract: Improved techniques for performing Spatial Joins multi-processing computing systems and environments are disclosed. One or more intersection of bounds (or limits) of data sets is determined as a join bounding space. The join bounding space is in a space (Global space or Global universe) where a spatial join between (or for) the data can be performed. The determined join bounding space can be partitioned into sub-partitions of the join bounding space. The sub-partitions of the join bounding space can assigned respectively to multiple processing unit for processing in parallel in. In addition, distribution cost information associated with the cost of distribution of the datasets (and/or their components) to the processing units of a multi-processing system can be provided and/or used to effectively distribute and/or redistribute processing of the Spatial Join between the processing units of a multi-processing system.

Abstract: An apparatus is provided for facilitating a local database system to execute a query function at a foreign database system. The apparatus comprises a processor of the local database system and a storage device communicatively coupled with the processor.

Abstract: A determination is made that a database system is resource bound resulting in a resource bound condition. Signals for the resources being bound in the database system are identified. Events associated with the signals are extracted. Events are correlated temporally to identify a time interval for which an arrival rate meter (ARM) is helpful. Database system segments are selected that effect key performance indicators associated with the identified time interval. Parameters for the selected database system segments to be deferred by the database system are estimated. The estimated parameters are incorporated into an arrival rate meter (ARM). The ARM is put into effect.

Abstract: A system may include a storage device configured to store a plurality of database tables. The system may further include a processor in communication with the storage device. The processor may receive a request to transmit a database table from the plurality of database tables. The database table may have a plurality of rows. The processor may determine if contents of each column row of each row of the database table are eligible to be compressed. For each column row that contains eligible contents, the processor may generate compressed data representative of the contents of a respective column row. The processor may remove the contents of the respective column row from the associated row. The processor may transmit the compressed data and the database table without content of the column rows represented by the compressed data. A method and computer-readable medium may also be implemented.

Abstract: A database table is defined as a load isolated table (LDI table) that supports a current table version number, multiple row versions, and special load protocols. An isolated loading statement on the LDI table is identified in a Data Manipulation Language (DML), causing the table to be placed in an isolated loading state associated with an incremented new value of the table's current version number. A designated group of DML operations in one or more sessions are then used to load/modify rows in the table, and affected rows are marked with the uncommitted new version. Read-committed queries supported for LDIs ignore the uncommitted rows during an isolated load, seeing only previously committed versions of the rows. When an end isolated loading on the table is identified, the table's version is updated to the new incremented value, causing the newly loaded/modified rows to be recognized as committed by subsequent read-committed queries.

Abstract: Embodiments of the present invention provide a hardware accelerator that assists a host database system in processing its queries. The hardware accelerator comprises special purpose processing elements that are capable of receiving database query/operation tasks in the form of machine code database instructions, execute them in hardware without software, and return the query/operation result back to the host system.

Abstract: Database values and their associated indicators can be arranged in multiple “buckets.” Adjacent buckets can be combined into a single bucket successively based one or more criteria associated with the indicators to effectively reduce the number of buckets until a desired number is reached.