Abstract: A database executes logical queries against in-flight data in a data streaming application. The data streaming application returns results representing in-flight data matching the parameters of the logical queries. Preferably, the streaming application produces data tuples for input to at least one table of the database. A user submitting queries may define the query scope to include in-flight data in the streaming application, causing the database manager to forward the query to the streaming application. A streaming application manager invokes database agents in respective nodes of the streaming application, which query in-flight data in respective buffers of the streaming application. The responses are provided back to the stream manager and the database manager. Profiling data obtained by trace analysis may be used to predict tuples which will be produced for the database.

Abstract: Disclosed aspects relate to tuple attribute expiry management in a stream computing environment to process a stream of tuples. A tuple may be received. The tuple may include a tuple attribute that has a first attribute value. An expiry criterion may be determined for the first attribute value of the tuple attribute. An achievement of the expiry criterion for the first attribute value of the tuple attribute may be detected. The tuple attribute related to the first attribute value may be modified. The modification of the tuple attribute may occur in response to detecting the achievement of the expiry criterion for the first attribute value of the tuple attribute.

Abstract: Techniques are described for re-starting queries based on an expected amount of data to be changed in a database. Embodiments of the present disclosure may generally receive a first query to be executed against a database, and start execution of the first query against the database according to a first access plan. Upon detecting, during execution of the first query, that an amount of data to be changed in one or more tables of the database as a result of a second query satisfies a predetermined condition, embodiments of the present disclosure determine whether to re-start execution of the first query against the database with a second access plan different from the first access plan or wait a predetermined period of time before re-starting execution of the first query against the database with the first access plan.

Abstract: Techniques are described for re-starting queries based on system resource availability. Embodiments of the present disclosure may generally receive a query to be executed against a database, determine, based on an amount of available system resources, a first access plan to use for executing the query against the database, and start execution of the query against the database according to the first access plan. Upon determining, during the execution of the query, that an amount of change in the available system resources satisfies a predetermined condition, embodiments of the present disclosure halt the execution of the query according to the first access plan, determine, based on the amount of change in the available system resources, a second access plan to use for executing the query against the database, and re-execute the query according to the second access plan.

Abstract: Disclosed aspects relate to window management in a stream computing environment. An indication of congestion may be detected with respect to the stream computing environment. Based on the indication of congestion, a set of window configurations in the stream computing environment may be determined. In response to determining the set of window configurations in the stream computing environment, the set of window configurations may be established in the stream computing environment.

Abstract: Disclosed aspects relate to managing a database management system (DBMS) using a set of stream computing data derived from a stream computing environment. The set of stream computing data which indicates a set of stream computing environment statistics may be collected with respect to the stream computing environment. A proactive database management operation may be determined for performance with respect to the DBMS based on the set of stream computing data which indicates the set of stream computing environment statistics. The proactive database management operation may be performed to manage the DBMS using the set of stream computing data.

Abstract: Disclosed aspects relate to operation efficiency management in a shared pool of configurable computing resources. A first set of processing operations of a first application may be detected. A second set of processing operations of a second application may be detected. The first set of processing operations of the first application may be compared with the second set of processing operations of the second application. A substantial match of the first and second processing operations of the first and second applications may be determined. A single set of processing operations for both the first and second applications may be compiled.

Abstract: A database which receives input from a data streaming application may include in-flight streamed data within the scope of a command which alters database data. Preferably, the streaming application produces data tuples for input to at least one table of the database. A user submitting modify data commands to apply to multiple tuples meeting some specified logical parameters may define the command scope to include in-flight data in the streaming application, causing the database manager to forward the command to the streaming application. A streaming application manager invokes database agents in respective nodes of the streaming application, which identify in-flight data meeting the specified logical parameters of the command, and apply the modify data operation to such data.

Abstract: Method and apparatus for query optimization using metadata. A first query associated with a first metadata is received. Upon receiving the first query, the first metadata is compared to predefined criteria, to determine that the first query is delayable. Upon determining that the first query is delayable, a first query plan is generated for the first query based on the first metadata. Upon generating the first query plan, a first schedule for executing the first query plan is generated. The first execution query plan may be scheduled to be executed at a later point in time based on the first metadata. Finally, the first query plan is executed according to the first schedule.

Abstract: Techniques are described for managing the execution of one or more groups of queries. Embodiments of the present disclosure may generally receive a group of queries to be executed against a database. Embodiments also determine, based on one or more attributes of the group of queries, an expected amount of resources that will be used in executing the group of queries against the database. Embodiments further schedule one or more queries of the group of queries for execution against the database based on the expected amount of resources to be used for the group of queries.

Abstract: Profiling data characterizing a data streaming application is used to project changes to a relational database resulting from current in-flight streamed data. Preferably, the streaming application produces tuples which are entered into the relational database. Trace data is collected during previous execution of the streaming application to construct operator graph profile data showing likely paths of tuples through multiple processing elements of the streaming application. Responsive to a query, agent(s) residing within the computer system(s) supporting the streaming application query in-flight tuples in one or more buffers of the streaming application. The responses to the agent queries are analyzed using the operator graph profile data to project tuples which will be output to the database. Projected changes to the database may alternatively be used for other purposes, e.g., creating database metadata structures; reorganizing data inserts; regulating query governors; and/or updating database statistics.

Abstract: A database executes logical queries against in-flight data in a data streaming application. The data streaming application returns results representing in-flight data matching the parameters of the logical queries. Preferably, the streaming application produces data tuples for input to at least one table of the database. A user submitting queries may define the query scope to include in-flight data in the streaming application, causing the database manager to forward the query to the streaming application. A streaming application manager invokes database agents in respective nodes of the streaming application, which query in-flight data in respective buffers of the streaming application. The responses are provided back to the stream manager and the database manager. Profiling data obtained by trace analysis may be used to predict tuples which will be produced for the database.

Abstract: Disclosed aspects relate to window management in a stream computing environment. A set of computing resources may be detected with respect to the stream computing environment. Based on the set of computing resources, a set of window configurations in the stream computing environment may be determined. In response to determining the set of window configurations in the stream computing environment, the set of window configurations may be established in the stream computing environment.

Abstract: Disclosed aspects relate to window management in a stream computing environment. An indication of congestion may be detected with respect to the stream computing environment. Based on the indication of congestion, a set of window configurations in the stream computing environment may be determined. In response to determining the set of window configurations in the stream computing environment, the set of window configurations may be established in the stream computing environment.

Abstract: Disclosed aspects relate to window management in a stream computing environment. An indication of congestion may be detected with respect to the stream computing environment. Based on the indication of congestion, a set of window configurations in the stream computing environment may be determined. In response to determining the set of window configurations in the stream computing environment, the set of window configurations may be established in the stream computing environment.

Abstract: Tuple attribute locking is implemented in a stream computing environment to selectively inhibit access to one or more attributes of tuples by stream operators.

Abstract: Disclosed aspects relate to window management in a stream computing environment. A set of computing resources may be detected with respect to the stream computing environment. Based on the set of computing resources, a set of window configurations in the stream computing environment may be determined. In response to determining the set of window configurations in the stream computing environment, the set of window configurations may be established in the stream computing environment.

Abstract: Embodiments of the present disclosure provide a method, system, and computer program product for managing the execution of a query. The method, system and computer program product include receiving a query to be executed. The query governor calculates an estimated replication time of the received query. The estimated replication time is an estimated duration of time required to replicate changes caused by the query. The query governor determines whether the estimated replication time exceeds the threshold replication time. Responsive to the query governor determining that the estimated replication time does not exceed the threshold replication time, the query governor executes the query against the database in accordance with the instructions.

Abstract: Techniques are described for estimating and managing an amount of data change for query processing. Embodiments of the present disclosure may generally receive a query to be executed and calculate an estimated amount of data change for the received query. If the initial estimated amount of data change for the received query does not exceed a threshold amount of data change, embodiments of the present disclosure may submit the query for execution. If the initial estimated amount of data change for the received query does exceed a threshold amount of data change, embodiments of the present disclosure may halt the execution of the query.

Abstract: A database which receives input from a data streaming application may include in-flight streamed data within the scope of a command which alters database data. Preferably, the streaming application produces data tuples for input to at least one table of the database. A user submitting modify data commands to apply to multiple tuples meeting some specified logical parameters may define the command scope to include in-flight data in the streaming application, causing the database manager to forward the command to the streaming application. A streaming application manager invokes database agents in respective nodes of the streaming application, which identify in-flight data meeting the specified logical parameters of the command, and apply the modify data operation to such data.