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.

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 mechanism that dynamically adjusts the number of packets sent in a train from a node to reflect the rate-of-packets arriving at a node in a network. In the preferred embodiment, the node has a packet controller that determines the optimum number-of-packetsito send in the train. The node also has a timer interval, which is the maximum time-to wait before sending the next train. The packet controller samples the packet arrival-rate and calculates the elapsed time to receive a configurable-constant number-of-packets in a train. This elapsed time is referred to as a sampling interval. The packet controller only calibrates the optimum number-of-packets when the sampling interval changes significantly from the historic sampling-interval. A significant change is a predetermined percentage greater or less than the historic interval-time.

Abstract: A mechanism that dynamically adjusts the number of packets sent in the train from a node to reflect the rate of packets arriving at the node. A train is a group of packets that are sent from the node as one unit. The node has an optimum train length that the node would like to send. The node also has a timer interval, which is the maximum time to wait before sending the next train. If the timer interval expires and the number of packets accumulated in the train is less than the optimum train length, then the node transmits the train and sets the optimum train length to be the number of packets actually received; that is, the optimum train length is adjusted downward. If the number of packets accumulated equals the optimum train length and the timer interval has not yet expired, the receiving node transmits these packets in a train, and if the next packet arrives before the time that the timer would have expired, the node increases the optimum train length.