Patent application number | Description | Published |
20090271360 | Assigning Plan Volatility Scores to Control Reoptimization Frequency and Number of Stored Reoptimization Plans - Methods, systems, and computer program products are provided for improving the processing of database queries. Some embodiments include generating volatility scores for various plans for executing similar database queries. Different embodiments may utilize: database statistics, the variable values being selected for, and/or historical run time data, to generate the plan volatility scores. In some embodiments, the volatility scores are used to determine whether to generate a new plan for a query, whether to prune an existing plan, and/or how many different plans to store for a query. | 10-29-2009 |
20090281986 | Generating Database Query Plans - Embodiments of the invention provide techniques for optimizing database queries for energy efficiency. In general, a query optimizer is configured to compare energy requirements of query plans, and to select a query plan requiring minimal energy to execute. In one embodiment, the query optimizer may also compare time performance of the query plans, and may select a query plan by matching to a user preference for a relative priority between energy requirements and time performance. | 11-12-2009 |
20090281992 | Optimizing Database Queries - Embodiments of the invention provide techniques for optimizing database queries for energy efficiency. In general, a query optimizer is configured to compare energy requirements of query plans, and to select a query plan requiring minimal energy to execute. In one embodiment, the query optimizer may also compare time performance of the query plans, and may select a query plan by matching to a user preference for a relative priority between energy requirements and time performance. | 11-12-2009 |
20090282272 | Organizing Databases for Energy Efficiency - Embodiments of the invention provide techniques for optimizing database queries for energy efficiency. In general, a query optimizer is configured to compare energy requirements of query plans, and to select a query plan requiring minimal energy to execute. In one embodiment, the query optimizer may also compare time performance of the query plans, and may select a query plan by matching to a user preference for a relative priority between energy requirements and time performance. | 11-12-2009 |
20090319474 | Aggregating Database Queries - Embodiments of the invention provide techniques for aggregating database queries for energy efficiency. In one embodiment, queries received by a DBMS are aggregated and staged according to hard-disk drives required for query execution. Each group of queries accessing a given drive may be dispatched for execution together. Further, the queries received by a DBMS may be matched to patterns of previously received queries. The matching patterns may be used to predict other queries which are likely to be received by the DBMS. The received queries may be staged to be dispatched with the predicted queries. By aggregating queries to be executed, access to each hard-disk drive may be optimized, thus reducing the overall energy consumption required for executing the queries. | 12-24-2009 |
20090319475 | Grouping Predicted Database Queries - Embodiments of the invention provide techniques for aggregating database queries for energy efficiency. In one embodiment, queries received by a DBMS are aggregated and staged according to hard-disk drives required for query execution. Each group of queries accessing a given drive may be dispatched for execution together. Further, the queries received by a DBMS may be matched to patterns of previously received queries. The matching patterns may be used to predict other queries which are likely to be received by the DBMS. The received queries may be staged to be dispatched with the predicted queries. By aggregating queries to be executed, access to each hard-disk drive may be optimized, thus reducing the overall energy consumption required for executing the queries. | 12-24-2009 |
20100036804 | Maintained and Reusable I/O Value Caches - Embodiments of the invention provide techniques for maintaining I/O value caches for database queries. Each maintained cache may be configured for use with a particular database query. Each cache may be persistently maintained in a system, meaning the cache is not automatically deleted after some period of time, and may thus be used to process subsequent instances of the same query. By use of the maintained cache, executing subsequent instances of the query may be avoided, thus saving time and system resources. Further, the maintained cache may be adapted to process other queries having similar characteristics to the initial query. The data included in each cache may be refreshed as required by changes to the underlying data. | 02-11-2010 |
20100036805 | System Maintainable and Reusable I/O Value Caches - Embodiments of the invention provide techniques for maintaining I/O value caches for database queries. Each maintained cache may be configured for use with a particular database query. Each cache may be persistently maintained in a system, meaning the cache is not automatically deleted after some period of time, and may thus be used to process subsequent instances of the same query. By use of the maintained cache, executing subsequent instances of the query may be avoided, thus saving time and system resources. Further, the maintained cache may be adapted to process other queries having similar characteristics to the initial query. The data included in each cache may be refreshed as required by changes to the underlying data. | 02-11-2010 |
20110185062 | Qualitative Assignment of Resources to a Logical Partition In a Multipartitioned Computer System - A qualitative resource assignment wizard receives qualitative information for a logical partition (LPAR) and calculates computer resource assignments for the LPAR based on the qualitative information and a set of conversion functions. For example, the qualitative resource assignment wizard may calculate a processing unit assignment, a memory assignment, and an I/O slot assignment for the LPAR. The qualitative information may be input by a user, for example, utilizing a graphical user interface (GUI). In one embodiment, the conversion functions are calculated during a training phase, in which a user periodically provides qualitative information while resource usage data is gathered. The wizard may reside in a hardware management console (HMC) or other administrative console and/or may be a component of a hypervisor or other partition management code. Software code associated with the wizard may be provided by a network server application to a client system for enabling a user to remotely input the qualitative information. | 07-28-2011 |
20120198423 | Code Path Tracking - Methods, systems, and products are provided for code path tracking. Embodiments include identifying an instrumented trace point in software code to be path tracked; identifying a function executed at the instrumented trace point in the software code; identifying parameters for the function executed at the instrumented trace point; and recording a description of the function, the parameters, and the result of the execution of the function using the parameters. | 08-02-2012 |
20130132405 | Dynamically Associating Different Query Execution Strategies with Selective Portions of a Database Table - A query facility for database queries dynamically determines whether selective portions of a database table are likely to benefit from separate query execution strategies, and constructs an appropriate separate execution strategies accordingly. Preferably, the database contains at least one relatively large table comprising multiple partitions, each sharing the definitional structure of the table and containing a different respective discrete subset of the table records. The query facility compares metadata for different partitions to determine whether sufficiently large differences exist among the partitions, and in appropriate cases selects one or more partitions for separate execution strategies. Preferably, partitions are ranked for separate evaluation using a weighting formula which takes into account: (a) the number of indexes for the partition, (b) recency of change activity, and (c) the size of the partition. | 05-23-2013 |