Abstract: Aggregation in a computing system can include receiving, at a service node of the computing system, a first query specifying aggregation and translating the first query into a second query having a first canonical format and specifying the aggregation. The method can include forwarding the second query to a first subset of a plurality of endpoint nodes and translating, at each endpoint node of the first subset, the second query into a third query having a format executable by a data source connected to the endpoint node. The third query can specify a level of the aggregation to be performed by the data source determined based upon a processing capability of the data source. The endpoint nodes can initiate execution of the third query by the data sources and provide an aggregated result including a result from the data source(s) to the service node.

Abstract: A method includes: a first node and a second node in a distributed computing system each creating a respective partial join filter; the first node and the second node each transmitting its respective partial join filter to a third node in the distributed computing system; the third node creating a final join filter by combining the respective partial join filters of the first node and the second node; the third node retrieving target data from a data source of the third node by applying the final join filter to the data source of the third node; and the third node transmitting the retrieved target data to a controlling node in the distributed computing system.

Abstract: Aggregation in a computing system can include receiving, at a service node of the computing system, a first query specifying aggregation and translating the first query into a second query having a first canonical format and specifying the aggregation. The method can include forwarding the second query to a first subset of a plurality of endpoint nodes and translating, at each endpoint node of the first subset, the second query into a third query having a format executable by a data source connected to the endpoint node. The third query can specify a level of the aggregation to be performed by the data source determined based upon a processing capability of the data source. The endpoint nodes can initiate execution of the third query by the data sources and provide an aggregated result including a result from the data source(s) to the service node.

Abstract: Aggregation in a computing system can include receiving, at a service node of the computing system, a first query specifying aggregation and translating the first query into a second query having a first canonical format and specifying the aggregation. The method can include forwarding the second query to a first subset of a plurality of endpoint nodes and translating, at each endpoint node of the first subset, the second query into a third query having a format executable by a data source connected to the endpoint node. The third query can specify a level of the aggregation to be performed by the data source determined based upon a processing capability of the data source. The endpoint nodes can initiate execution of the third query by the data sources and provide an aggregated result including a result from the data source(s) to the service node.

Abstract: A method includes: a first node and a second node in a distributed computing system each creating a respective partial join filter; the first node and the second node each transmitting its respective partial join filter to a third node in the distributed computing system; the third node creating a final join filter by combining the respective partial join filters of the first node and the second node; the third node retrieving target data from a data source of the third node by applying the final join filter to the data source of the third node; and the third node transmitting the retrieved target data to a controlling node in the distributed computing system.

Abstract: Table discovery in a distributed and dynamic computing system can include detecting an event of a type indicating an update to a data source of a selected node of a plurality of nodes of a computing system, in response to the event, generating, within the selected node, a first collaborative trigger having a query identifier correlated with the type of the event, and distributing the first collaborative trigger through other ones of the plurality of the nodes of the computing system so that the first collaborative trigger reaches an actor of the computing system. Table discovery further can include, in response to receiving the first collaborative trigger within the actor, generating, within the actor, a query for table definition information. The query may be implemented as an aggregation query and may be distributed through the plurality of the nodes.

Abstract: Table discovery in a distributed and dynamic computing system can include detecting an event of a type indicating an update to a data source of a selected node of a plurality of nodes of a computing system, in response to the event, generating, within the selected node, a first collaborative trigger having a query identifier correlated with the type of the event, and distributing the first collaborative trigger through other ones of the plurality of the nodes of the computing system so that the first collaborative trigger reaches an actor of the computing system. Table discovery further can include, in response to receiving the first collaborative trigger within the actor, generating, within the actor, a query for table definition information. The query may be implemented as an aggregation query and may be distributed through the plurality of the nodes.

Abstract: Using collaborative triggers within a distributed computing system can include, in response to detecting a first event of a selected type within a first node of the computing system, generating a first collaborative trigger having a query identifier correlated with the selected type of the event and distributing the first collaborative trigger through other nodes of the computing system so that the first collaborative trigger reaches an actor of the computing system. The computer-implemented method can include suppressing, within each node that distributes the first collaborative trigger, each other collaborative trigger having a same query identifier as the first collaborative trigger until a response to the first collaborative trigger is received from the actor.

Abstract: Using collaborative triggers within a distributed computing system can include, in response to detecting a first event of a selected type within a first node of the computing system, generating a first collaborative trigger having a query identifier correlated with the selected type of the event and distributing the first collaborative trigger through other nodes of the computing system so that the first collaborative trigger reaches an actor of the computing system. The computer-implemented method can include suppressing, within each node that distributes the first collaborative trigger, each other collaborative trigger having a same query identifier as the first collaborative trigger until a response to the first collaborative trigger is received from the actor.

Abstract: Table discovery in a distributed and dynamic computing system can include detecting an event of a type indicating an update to a data source of a selected node of a plurality of nodes of a computing system, in response to the event, generating, within the selected node, a first collaborative trigger having a query identifier correlated with the type of the event, and distributing the first collaborative trigger through other ones of the plurality of the nodes of the computing system so that the first collaborative trigger reaches an actor of the computing system. Table discovery further can include, in response to receiving the first collaborative trigger within the actor, generating, within the actor, a query for table definition information. The query may be implemented as an aggregation query and may be distributed through the plurality of the nodes.

Abstract: Table discovery in a distributed and dynamic computing system can include detecting an event of a type indicating an update to a data source of a selected node of a plurality of nodes of a computing system, in response to the event, generating, within the selected node, a first collaborative trigger having a query identifier correlated with the type of the event, and distributing the first collaborative trigger through other ones of the plurality of the nodes of the computing system so that the first collaborative trigger reaches an actor of the computing system. Table discovery further can include, in response to receiving the first collaborative trigger within the actor, generating, within the actor, a query for table definition information. The query may be implemented as an aggregation query and may be distributed through the plurality of the nodes.

Abstract: Using collaborative triggers within a distributed computing system can include, in response to detecting a first event of a selected type within a first node of the computing system, generating a first collaborative trigger having a query identifier correlated with the selected type of the event and distributing the first collaborative trigger through other nodes of the computing system so that the first collaborative trigger reaches an actor of the computing system. The computer-implemented method can include suppressing, within each node that distributes the first collaborative trigger, each other collaborative trigger having a same query identifier as the first collaborative trigger until a response to the first collaborative trigger is received from the actor.

Abstract: Aggregation in a computing system can include receiving, at a service node of the computing system, a first query specifying aggregation and translating the first query into a second query having a first canonical format and specifying the aggregation. The method can include forwarding the second query to a first subset of a plurality of endpoint nodes and translating, at each endpoint node of the first subset, the second query into a third query having a format executable by a data source connected to the endpoint node. The third query can specify a level of the aggregation to be performed by the data source determined based upon a processing capability of the data source. The endpoint nodes can initiate execution of the third query by the data sources and provide an aggregated result including a result from the data source(s) to the service node.

Abstract: Using collaborative triggers within a distributed computing system can include, in response to detecting a first event of a selected type within a first node of the computing system, generating a first collaborative trigger having a query identifier correlated with the selected type of the event and distributing the first collaborative trigger through other nodes of the computing system so that the first collaborative trigger reaches an actor of the computing system. The computer-implemented method can include suppressing, within each node that distributes the first collaborative trigger, each other collaborative trigger having a same query identifier as the first collaborative trigger until a response to the first collaborative trigger is received from the actor.

Abstract: A sequence of processing transactions operating on a cached data set, which depend on each other because they operate on the same items of data from the data set. The transactions are saved until the master copy of the data becomes available. The transactions are played back against the master copy until one of the played back transactions fails because another transaction which operated on the same items of data but against a separate cached copy and originating from another application, was successfully played back on the master copy at an earlier time. At this point, all subsequent transactions which depended on the failing transaction are rolled back on the cached copy (with appropriate failure reports generated) and activity resumes from there. “Chained” (optimistic) transactions can therefore be applied to cached data and can be allowed to progress by recording their dependencies so they can be undone when required.

Abstract: A method and system for managing channels in a voice response system is provided. The method comprises periodically monitoring utilisation of a system resource and determining a number, N, of voice channels required to be quiesced based on the utilisation level of the system resource. This number is compared with the number of channels currently quiescing, Q, and the number of quiescing channels is adjusted accordingly. A quiescing channel is disabled when it becomes inactive.

Abstract: A method and system for distribution of information are provided in a publish and subscribe system in which a publisher application transmits a message (210, 310) to one or more subscribing applications (208, 308) via a messaging infrastructure. The method includes receiving (203, 303) a message at a subscribing system (202, 302) and generating an event by the subscribing system to allow access to the message (210, 310) by a subscribing application (208, 308) at a reveal time (211, 311). A counting means (205, 305) on the subscribing system determines when it is the reveal time (211, 311) and the event is triggered at the reveal time (211, 311). A message (210) has a reveal time (211, 311) common to the one or more subscribing applications (208, 308).