Abstract:
Nodes in a query execution data structure have monitor and dump methods defined. The monitor method enables the collection of information from the node. The dump method outputs the monitored information from each node. A monitor and debug mechanism of the preferred embodiments includes a graphical user interface that allows a user to graphically examine a query execution tree, to enable monitoring of the nodes on a node-by-node basis, and to view information dumped from the query execution data structure as the query is executed or after the query is executed. The result is a powerful tool that allows efficiently monitoring and debugging a query implemented in an object oriented query execution data structure.
Abstract:
Methods, systems, and computer program products are provided for executing database rollup queries. Methods can include iterating through a database table which has been grouped and ordered on the different columns which are in the ROLLUP clause. In some embodiments, a GROUP BY ROLLUP construct can be executed while only requiring an additional one storage location per ordered column per each aggregate function to be performed on each database row. The higher level aggregate functions can be executed without relying on accessing any lower level aggregate results in some embodiments. A suitably grouped and ordered database table can have a multiple level hierarchical ROLLUP function executed in a single pass without having to retrieve lower level aggregate results.
Abstract translation:提供方法,系统和计算机程序产品用于执行数据库汇总查询。 方法可以包括遍历已经在ROLLUP子句中的不同列上分组和排序的数据库表。 在一些实施例中,可以执行GROUP BY ROLLUP构造,同时仅在每个数据库行上执行每个聚合函数需要每个排序列的附加一个存储位置。 在一些实施例中,可以不依赖于访问任何较低级别的聚合结果来执行较高级别的聚合函数。 适当分组和排序的数据库表可以具有在单次通过中执行的多级分层ROLLUP功能,而不必检索较低级别的聚合结果。
Abstract:
Methods, systems and articles of manufacture of processing a multi-state attribute field query. One embodiment provides a method of processing a multi-state attribute field query, comprising instantiating a plurality of live objects; performing, by each live object, an attribute operation, wherein at least one attribute operation is a comparison operation associated with attributes of the query. The plurality of live objects access a global status storage area only when an operand of the comparison operation is null or error. In any case, execution control is passed from each live object to an adjacent live object.
Abstract:
An apparatus, program product and method utilize a dynamically-populated query buffer to facilitate the handling of at least a portion of a database query in parallel. A query is implemented using at least first and second portions, where the second portion of the query is executed in parallel using a plurality of threads. The first portion of the query is executed to dynamically populate a query buffer with records from a data source, and the plurality of threads that execute the second portion of the query are specified to the query buffer so that the effective data source for the second portion of the query comprises the records that are dynamically populated into the query buffer.
Abstract:
A stream data node receives real-time streamed data from one or more input devices, dynamically filters the streamed data to reduce the streamed data, and delivers the reduced data when requested. By providing real-time filtering of the data, the amount of data that must be stored in a database may be substantially reduced. The stream data node can perform aggregation functions, group functions, and select functions, thereby also significantly reducing the amount of data that must be stored in a database. The stream data node may also be part of a query execution data structure, where it delivers its data when requested by another node in the query execution data structure.
Abstract:
Nodes in a query execution data structure have monitor and dump methods defined. The monitor method enables the collection of information from the node. The dump method outputs the monitored information from each node. A monitor and debug mechanism of the preferred embodiments includes a graphical user interface that allows a user to graphically examine a query execution tree, to enable monitoring of the nodes on a node-by-node basis, and to view information dumped from the query execution data structure as the query is executed or after the query is executed. The result is a powerful tool that allows efficiently monitoring and debugging a query implemented in an object oriented query execution data structure.
Abstract:
A stream data node receives real-time streamed data from one or more input devices, dynamically filters the streamed data to reduce the streamed data, and delivers the reduced data when requested. By providing real-time filtering of the data, the amount of data that must be stored in a database may be substantially reduced. The stream data node can perform aggregation functions, group functions, and select functions, thereby also significantly reducing the amount of data that must be stored in a database. The stream data node may also be part of a query execution data structure, where it delivers its data when requested by another node in the query execution data structure.
Abstract:
A method, apparatus and program product dynamically activate and/or deactivate buffers during execution of a database query. The dynamic deactivation and activation is based on the monitoring of information associated with the consumption of data by a plurality of threads during execution of an access plan for the database query. By doing so, the selection of a less optimal buffer position during optimization may be replaced with a more optimal buffer position during runtime, often resulting in improved query performance and parallelism.
Abstract:
Nodes in a query execution data structure have monitor and dump methods defined. The monitor method enables the collection of information from the node. The dump method outputs the monitored information from each node. A monitor and debug mechanism of the preferred embodiments includes a graphical user interface that allows a user to graphically examine a query execution tree, to enable monitoring of the nodes on a node-by-node basis, and to view information dumped from the query execution data structure as the query is executed or after the query is executed. The result is a powerful tool that allows efficiently monitoring and debugging a query implemented in an object oriented query execution data structure.
Abstract:
Previously-optimized database queries are stored in memory. When a new query needs to be optimized, the previously-optimized queries are examined to determine whether the new query has been previously optimized. If the new query has not been previously optimized, the previously-optimized queries are examined to determine whether any previously-optimized queries differ only in data type of one or more operands when compared to the new query. If a previously-optimized query that differs only in data type is located, the previously-optimized query is refreshed to reflect the different data type without the need of optimizing the new query from scratch. Portions of previously-optimized queries may thus be re-used even when a previously-optimized query is not identical to a new query to be optimized. As a result, the performance of query optimization in a database system is increased.