Abstract: Apparatus, systems, and methods may operate to receive a designation of multiple rows to supply data to a single user defined function, which is made available in a structured query language SELECT statement. Further activities may include retrieving the data from at least one storage medium, packing each of the multiple rows having a common key into a single row, and transforming the data from a first state into a second state by applying the single function to the data using a single access module processor. Other apparatus, systems, and methods are disclosed.

Abstract: Excess capacity (or excess resources) can be used in a capacity controlled environment to effectively manage data storage of a database. In this context, excess capacity can, for example, be controlled used as needed, as configured and/or on a temporary basis. Management of data storage in a database can, for example, include operations associated with moving or relocating data of the database. Relocation of data can, for example, be performed to relocate data deemed to be “hot” data to a location that can provide a faster access time in order to improve the overall efficiency of the database system.

Abstract: A computer-implemented method, apparatus and article of manufacture for optimizing a database query. A query execution plan is generated for the database query, which may be stored in an in-line query capture database. Execution of the query execution plan may be monitored in order to generate performance information, which also may be stored in the in-line query capture database. The data stored in in-line query capture database may be used during the initial generation of query execution plans, as well as for the re-optimization of a query execution plan, during the execution of the query execution plan.

Abstract: Techniques for finding a column with column partitioning are provided. Metadata for a container row is expanded to include information for searching ranges of partitioned column values. The metadata identifies offsets to specific ranges and specific columns within a specific range. The offsets also identify where compressed data for a desired column resides. Thereby, permitting partitioned columns having compressed data to be located without being decompressed and decompressed on demand as needed.

Abstract: Data or one or more operations can be provided, based on one or more characteristics associated with the data and/or operations, to a designated computing group or pool of computing resources designated for handling the data and/or operations with the particular data characteristic(s). The designated computing group can, for example, be one of multiple computing groups in the same system or device. As such, all of the computing groups can still function together in the same system or device, for example, in parallel. However, each one of the multiple computing groups can, for example, be defined or predefined to include one or more computing resources that are more suitable for storing and/or processing data with one or more data characteristics or handle operations with one or more determined characteristics.

Abstract: Techniques for ordering predicates in column partitioned databases for query optimization. Predicates on a single CP table within a query are organized to predicate-CP nodes with various sets of column partitions. The predicates within each predicate-CP node and the predicate-CP nodes as a whole are ordered in ascending order of cost which is determined by CPU/IO cost and predicate selectivity. The reorganized query is then executed.

Abstract: Data can be stored based on one or more indications and one or more other storage criteria. The indications can effectively indicate or identify a storage level for storing data in a multi-storage system. The indications, however, need not be the only basis for storing the data object in a multi-storage system as one or more other storage criteria can also be considered. As a result, the indication can be used to effectively influence data storage but other storage criteria can be used as well to prevent adverse effects caused by undue influence and to ensure the overall efficiency of the system. Also, the one or more other storage criteria can be evaluated or reevaluated on a continual basis.

Abstract: Inputs are received. The inputs are a star schema data model comprising a non-partitioned fact table (F) comprising fields (f1, f2, . . . fn); a set of queries (Q=q1, q2, . . . qm); and a set of weights for each query in Q. Each weight defines the priority of a respective query in a workload. The inputs are pre-processed to produce a most-granular-partitioning. The most-granular-partitioning is processed to produce an initial multi-level partitioned primary index, the processing including determining the scan cost of one of the queries in Q. The initial multi-level partitioned primary index is processed to produce a final multi-level partitioned primary index, the processing including determining the query cost of one of the queries in Q. F is partitioned using the final multi-level partitioned primary index. A query from Q is run against F to produce a result. The result is stored.

Abstract: Techniques for processing joins on column partitioned tables are provided. A query includes a first-Column Partition (CP) table joined with a second-CP table. The query is decomposed into a three-step process and rewritten and processed.

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: 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 there (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: A system, method, and computer-readable medium that facilitate efficient use of cache memory in a massively parallel processing system are provided. A residency time of a data block to be stored in cache memory or a disk drive is estimated. A metric is calculated for the data block as a function of the residency time. The metric may further be calculated as a function of the data block size. One or more data blocks stored in cache memory are evaluated by comparing a respective metric of the one or more data blocks with the metric of the data block to be stored. A determination is then made to either store the data block on the disk drive or flush the one or more data blocks from the cache memory and store the data block in the cache memory. In this manner, the cache memory may be more efficiently utilized by storing smaller data blocks with lesser residency times by flushing larger data blocks with significant residency times from the cache memory.

Abstract: Techniques for processing joins on column partitioned tables are provided. A join operation having a column partitioned table within a query is decomposed into a two-step process. The first process performs the join condition on the column portioned table with optional filtering conditions and a non-column partitioned table and spools the resulting columns to a spooled table. The spooled table is then rowid joined back to the column partitioned table to acquire remaining columns not present in the spooled table. Both the first and second steps can be separately resolved for costs when determining a query execution plan.

Abstract: Techniques for query statistics inheritance are provided. Statistics for a database are used to determine selectivity estimates for sparse joins and tables being joined together within a given query. These statistics are inherited up to the given query along with the selectivity estimates and provided to a database optimizer to use when developing query plans and selecting an optimal query plan for the given query.

Abstract: A computer-implemented method, apparatus and article of manufacture for optimizing a database query. A query execution plan for the database query is generated using estimated cost information; one or more steps of the query execution plan are executed to retrieve data from a database stored on the computer system. Actual cost information is generated for each of the executed steps, and the estimated cost information is re-calculated using the actual cost information. One or more resource allocation rules defined on one or more steps of the query execution plan are executed, based on the estimated cost information, wherein the resource allocation rules include one or more defined actions. The estimated cost information may be re-calculated using the actual cost information when confidence in the estimated cost information is low, but the estimated cost information may not be re-calculated when confidence in the estimated cost information is high.

Abstract: Techniques for using metadata as comments to assist with search problem determination and analysis are provided. Before an action is taken on a search, contextual information is gathered as metadata about the action and actor requesting the action. The metadata is embedded in the search as comments and the comments are subsequently logged when the action is performed on the search. The comments combine with other comments previously recorded to permit subsequent analysis on searches.

Abstract: A filter receives a request to perform an operation in a database system, and the filter receives a resource estimate relating to the request from an optimizer. The filter determines whether the resource estimate exceeds an available resource of the database system, and if so, the filter rejects the request prior to execution of the request.

Abstract: A system, method, and computer-readable medium that provide automatic and dynamic control of optimizer settings in a large complex system environment are provided. The optimizer may pursue more aggressive query execution plans and switch to a more conservative approach in cases of actual observed inaccuracies.

Abstract: Metadata can be provided to multiple processing units of a database system by using local storages respectively provided for the processing units, such that a local storage is accessible only to its respective processing unit. As a result, processing units can access metadata when needed (e.g., when needed to process a database request at runtime) without having to access a source external to the database system. In addition, metadata (e.g., an XML object, XML schema, XSLT stylesheets, XQuery modules) can be provided using a database request or command, for example, by using a register statement.

Abstract: Techniques for dynamic resource management are presented. A World-Wide Web (WWW) page is acquired on first access to a WWW site and rendered with a script tag. When a browser loads the WWW page, the script tag is processed to remotely execute a script on the WWW site. The script produces a single file having code for the resources that are referenced in the WWW page. The single file is provided back to the browser where it is cached so that when any of the resources are accessed via the WWW page, the needed code for those resources are available for execution within the cache of the browser.