Abstract: The present disclosure provides methods, systems and apparatus for efficient data management in distributed database system. According to an aspect, a method is provided. The method includes relocating a first table and a second table of a database to a first node of the database, wherein the first table and a second table (or one or more tables which have a colocation relationship with the first table) are associated with one or more distribution keys corresponding to one or more columns of the first table and the second table. The method further includes defining a colocation relationship between the first table and the second table based on a distribution key of the one or more distribution keys. The colocation relationship may indicate that data of the first table and the second table that correspond according to the distribution key are to reside on a same node of the database.

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: 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: 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: 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: 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: Embodiments of the invention provide a method for regaining memory consistency after a trap via transactional memory. Transactional memory and a transactional memory log are used to undo changes made to memory from a transaction start point up to the point of a trap event. After the trap event is processed, and the changes are rolled back, the program can resume execution at the beginning of the transaction.

Abstract: A method for describing activities in software products is provided. The method provides for identifying a plurality of activities in a software product that are of interest, defining an event structure to describe each identified activity as an event, associating each identified activity with one or more problem determination technologies, executing the software product, and responsive to detecting one of the plurality of identified activities during execution of the software product, creating one or more event records for the one detected activity based on the defined event structure, initiating the one or more problem determination technologies associated with the one detected activity, and passing the one or more event records to each of the one or more problem determination technologies.

Abstract: Disclosed is a data processing system for facilitating problem resolution. The data processing system-implemented system includes a configuring module for configuring a system pathway that leads to a solution, and an associating module for associating a usage indicator with the symptom pathway, the usage indicator indicating a frequency in which the symptom pathway was previously implemented for successfully resolving previously experienced problems.

Abstract: Embodiments of the invention provide a method for regaining memory consistency after a trap via transactional memory. Transactional memory and a transactional memory log are used to undo changes made to memory from a transaction start point up to the point of a trap event. After the trap event is processed, and the changes are rolled back, the program can resume execution at the beginning of the transaction.

Abstract: A method for describing activities in software products is provided. The method provides for identifying a plurality of activities in a software product that are of interest, defining an event structure to describe each identified activity as an event, associating each identified activity with one or more problem determination technologies, executing the software product, and responsive to detecting one of the plurality of identified activities during execution of the software product, creating one or more event records for the one detected activity based on the defined event structure, initiating the one or more problem determination technologies associated with the one detected activity, and passing the one or more event records to each of the one or more problem determination technologies.

Abstract: Disclosed is a data processing system for facilitating problem resolution. The data processing system-implemented system includes a configuring module for configuring a system pathway that leads to a solution, and an associating module for associating a usage indicator with the symptom pathway, the usage indicator indicating a frequency in which the symptom pathway was previously implemented for successfully resolving previously experienced problems.

Abstract: Disclosed is a data processing system-implemented method. The data processing system-implemented method includes configuring a symptom pathway that leads to a solution, and associating a usage indicator with the symptom pathway, the usage indicator indicating a frequency in which the symptom pathway was previously implemented for successfully resolving previously experienced problems.

Abstract: Disclosed is a data processing system-implemented method, a data processing system and an article of manufacture for facilitating problem resolution. The data processing system-implemented method includes configuring a symptom pathway that leads to a solution, and associating a usage indicator with the symptom pathway, the usage indicator indicating a frequency in which the symptom pathway was previously implemented for successfully resolving previously experienced problems.