Abstract: A database system comprises a processing module, and a storage device communicatively coupled with the processing module and allocated thereto. The storage device stores a base table allocated to the processing module. The processing module receives a database query from a client computer system, and generates a spool based upon a number of columns of a table, and partitions at least one column of the spool based upon the database query received from the client computer system.

Abstract: Streaming data is populated to an in-memory data table and a continuous query is executed against an in-memory data table using a database interface to perform analytical operations on the populated in-memory data table. Results from the analytical operations performed are streamed to consuming applications.

Abstract: A system and method for compressing data. The system and method employ a static compression dictionary, or look-up table, containing a predetermined number of uncompressed data values and corresponding compressed code values for replacing uncompressed data values with their corresponding compressed code values to reduce data storage requirements. The system and method further employ a dynamic compression dictionary, to which uncompressed data values and corresponding compressed code values are added as required to compress uncompressed data values not contained within the static compression dictionary.

Abstract: Apparatus, systems, and methods may operate to receive a request to move at least a portion of a database table stored on a tangible medium from a current partition to a history partition, wherein the database table is partitioned into physical partitions according to a selected mapping update frequency. In response to receiving the request, activities may include modifying a logical partitioning of the database table by updating a mapping of the physical partitions to logical partitions. Other apparatus, systems, and methods are disclosed.

Abstract: The number of iterations or self joins required to execute a recursive database query can be estimated. It will be appreciated that this estimation can be used to plan the execution of the recursive query and can be made in various ways and for various applications. By way of example, an estimated number of iterations or self joins required to execute a recursive database query (e.g., 12) can be used as a basis to determine or plan an optimal execution plan. For example, given an estimated twelve (12) iterations, an execution plan can be determined for executing at least the first three (3) iterations or for executing every three (3) iterations, whereas for an estimated twenty (21) iterations required to complete a recursive database query, an execution plan can be determined for the first five (5) or six (6) iterations, and so on.

Abstract: Based on one or more predicated results (e.g., estimations of the actual results) associated with one or more iterations and/or sub-queries of an iterative or recursive database query, it can be determined whether to use an execution plan (e.g., a current execution plan used to execute one or more iterations) to execute one or more other iterations and/or sub-queries of the iterative or recursive database query. Consequently, use of the execution plan to execute the one or more other iterations and/or sub-queries of the iterative or recursive database query can be disallowed. As a result, the iterative or recursive database query can be executed more efficiently. The determination of whether to use an execution plan can, for example, be performed by determining whether an actual result obtained by executing one or more iterations differs or diverges more than a determined value from an estimated result of the same iteration(s).

Abstract: Demographics for data are determined. A compression ratio (“CR”) is determined for each of a plurality of compression techniques. CR is a size of the data before compression divided into a predicted size of the data after compression. The predicted size of the data after compression is determined as a function of the determined demographics. An access efficiency of each of the compression techniques is determined as a function of the determined demographics. The compression techniques are ranked by CR and access efficiency. A compression technique is selected based on the ranking. The data is compressed using the selected compression technique. The compressed data is stored.

Abstract: A database system may implement resource management for redistribution of stored database information in additional database resources. Resource management may include detection of the presence of additional database resources, such as storage and processing resources. Based on conditions associated with the additional resources and database information selected for potential redistribution, resource management may include a determination as to whether or not redistribution of the database information is to be performed. Resource management may include a cost-benefit analysis to determine if redistribution of database information is to be performed. The cost-benefit analysis may be based on factors related to both the additional resources and the database information being considered for redistribution.

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: Techniques for guided access to an external distributed file system (DFS) from a database management system (DBMS) are provided. A user access a graphical user interface (GUI) to interactively define a search on an external DFS. The search and any filtering conditions are processed on the external DFS and results are imported to the DBMS and mapped to a table in the DBMS for manipulation and access by the user within the DBMS.

Abstract: A system, method, and computer-readable medium that facilitate the optimization of frequently executed queries via automated index creation are provided. Standard optimizer strategies for dynamic index creation are utilized with query frequency information taken from a system's request cache. The described mechanisms provide a process of determining what indexes would be beneficial to query performance based on decisions and information from the optimizer that is ultimately responsible for the choice of index usage. Further, the plan cache is utilized in a manner that provides reliable information about the historical and anticipated frequency of specific queries.

Abstract: A system and method for managing one or more database systems, wherein the database systems perform database queries to retrieve data stored by the database systems. One or more regulators are used for managing the database systems, wherein the regulators monitor workload priority influenced data temperature in order to allocate resources for the systems. The data temperature is a measure of physical accesses to logical data, and the workload priority is used to further define data temperature, in order to optimize data storage placement and data access decisions.

Abstract: A database system may process multiple column-oriented tasks in parallel for a database being stored according to a row-partitioning protocol. The database system may determine when the query should process the column-oriented task serially or in parallel. For parallel processing, the database system may generate processing tasks for each unique column-oriented task contained in the query used to retrieve column data and to process the column data according to the column-oriented tasks requested. A method of operating the database system may determine that multiple column-oriented tasks included in a query are to be processed in parallel. The method may further include generating a processing task for each unique column-oriented task included in the query. The method may further include performing the column-oriented tasks in parallel based on the processing threads. The method may implement various considerations in determining to process to the column-oriented tasks in parallel.

Abstract: A virtual regulator implemented to provide closed-loop system management (CLSM) functionality to a database system and without a need to substantially adapt a given CLSM technology to account for specific nuances and requirements of an operating system. For example, the regulator may be implemented with either or both of process model operating systems and thread model operating systems. Common examples of these include UNIX, LINUX, MP-RAS, MS WINDOWS or WINDOWS NT.

Abstract: A method, system, apparatus, and article of manufacture provide the ability to maintain multiple versions of structured views of data in a computer system. A relational database management system (RDBMS) is executed that stores master data in the computer system in master RDBMS tables. The master data is hierarchical in nature and hierarchy metadata for the master data is stored in the RDBMS tables. As part of a process and framework, a series of business rules and process workflows are maintained to manage the master data. Version tables are created in the RDBMS that correspond to each of the master RDBMS tables. Each of the version tables includes an attribute denoting version information. Versions of the master data are defined by replicating the master data and hierarchy metadata into the corresponding version tables. The version tables are used to graphically visualize, manage, and manipulate the versions of the master data.

Abstract: A combination of non-persistent-based and persistent-based schemes are used to effectively manage volatile storages which are conventionally managed solely by using non-persistent schemes (e.g., LRU schemes in cache memory). Generally, the persistent-based schemes can be based on persistent information associated with a non-volatile storage environment (e.g., persistent data temperatures associated with data stored in non-volatile storages). In this context, a persistent-based scheme can, for example, be effectively used in addition or combination with a conventional scheme provided for volatile memory. By way of example, a LRU scheme can be combined with a scheme based on persistent data temperatures in order to more effectively manage cache memory provided to enhance the performance of a system. As another example, a LRU, a LFU aging schemes can be combined with a scheme based on persistent data temperatures.

Abstract: Techniques for management of data in multi-storage systems allow managing storage of data in one of the multiple storages (e.g., a HDD) based on the information associated with the storage and/or access of data (e.g., logical hits of data in a cache memory) in another one of the storages (e.g., a cache memory) of the multi-storage system. In one aspect, information associated with storage and/or access of data in a volatile (or non-persistent) storage environment is provided for managing the storage of data in a non-volatile (or persistent) storage environment. By way of example, data access information associated with a volatile storage environment (e.g., logical hits of data in a cache) can be effectively communicated to a non-volatile storage environment, for example, as information that can be indicative of data temperatures. Moreover, the information obtained from a non-volatile storage environment can be persistently stored for and/or in the non-volatile environment (e.g.

Abstract: A method and apparatus are provided for facilitating performance monitoring of a large database system. The apparatus comprises a processor and a storage device communicatively coupled with the processor. The processor is programmed to (i) retrieve resource usage data points, (ii) calculate an outlier threshold value based upon values of data points, and (iii) determine if the value of each data point is outside of the threshold value. The processor is further programmed to (iv) plot the value of the data point in histogram with a first color when the data point value is determined to be outside of the threshold value, (v) plot the data point value in histogram with a second color when the data point value is determined to be not outside of the threshold value, and (vi) display the histogram containing plotted data point values of the first color and plotted data point values of the second color to enable a user to quickly and easily identify a potential skew condition.

Abstract: Techniques for management of data in multi-storage systems allow managing storage of data in a first storage of multiple storages in a multi-storage system based on the temperature of the data (or data temperature) obtained for a second storage of the multiple storages in a multi-storage system. For example, in a multi-storage system that includes at least one non-volatile storage (e.g., one or more HDDs) and at least one volatile storage (e.g., a cache memory device), the storage of a particular data portion (e.g., a storage unit of data) for the at least one volatile storage can be managed based on a temperature of the data determined for the non-volatile storage. By way of example, persistent temperatures used for management of data in a non-volatile storage system (e.g., a multi-tier storage of a database system) can be used to effectively manage the storage of the data in a cache memory that is typically provided for improving performance by keeping data that is likely to be used in the cache memory.

Abstract: A method of processing a transaction request at a database load balancer. The method comprises receiving the transaction request, where the transaction request is comprised of one or more operations; analyzing the transaction request to determine the one or more operations; associating one or more database locks with each of the one or more operations; analyzing one or more of the database locks to determine the one or more sequence numbers associated with each of the one or more operations; and transmitting the one or more operations with the associated database locks and the sequence numbers to one or more databases servers accessible to the database load balancer.