Abstract: A streams manager monitors performance of a streaming application and determines if operators are underperforming according to a threshold. When the performance needs to be improved, the streams manager automatically modifies the flow graph to offload or reroute a stream of data, or part of a stream of data, to a similar operator to more efficiently utilize streaming resources. Operators are provided with multiple ports to allow the streams manager to send additional streams to the operator.

Abstract: A streams manager monitors performance of a streaming application and determines if operators are underperforming according to a threshold. When the performance needs to be improved, the streams manager automatically modifies the flow graph to offload or reroute a stream of data, or part of a stream of data, to a similar operator to more efficiently utilize streaming resources. Operators are provided with multiple ports to allow the streams manager to send additional streams to the operator.

Abstract: A streams manager monitors performance of a streaming application and determines if operators are underperforming according to a threshold. When the performance needs to be improved, the streams manager automatically modifies the flow graph to offload or reroute a stream of data, or part of a stream of data, to a similar operator to more efficiently utilize streaming resources. Operators are provided with multiple ports to allow the streams manager to send additional streams to the operator.

Abstract: A streams manager monitors performance of a streaming application and determines if operators are underperforming according to a threshold. When the performance needs to be improved, the streams manager automatically modifies the flow graph to offload or reroute a stream of data, or part of a stream of data, to a similar operator to more efficiently utilize streaming resources. Operators are provided with multiple ports to allow the streams manager to send additional streams to the operator.

Abstract: A smart tuple manager includes a mechanism for merging a smart tuple, and for automatically generating one or more classes from existing classes when a smart tuple is merged. When a first smart tuple and a second smart tuple are merged into a new third smart tuple, a class for the third smart tuple is automatically generated from the classes for the first and second smart tuples. The class for the third smart tuple is a superset of the classes for the first and second smart tuples. After a class is automatically generated, new code segments may be added to the class as needed.

Abstract: Disclosed aspects relate to managing a stream computing environment. The stream computing environment may have a consistent region that includes a set of stream operators for processing a stream of tuples. An operator modification request with respect to the set of stream operators of the consistent region of the stream computing environment may be received. In response to receiving the operator modification request, a set of tuples of the stream of tuples may be detected in the consistent region. Using the operator modification request, a tuple adjustment action for the set of tuples of the stream of tuples in the consistent region may be determined. Based on the operator modification request, the set of stream operators may be modified. The set of tuples may be processed using the tuple adjustment action.

Abstract: A smart tuple manager includes a mechanism for splitting a smart tuple, and for automatically generating one or more classes from existing classes when a smart tuple is split. When a first smart tuple is split into second and third new smart tuples, classes for the second and third smart tuples are automatically generated from the class for the first smart tuple. The classes for the second and third smart tuples are subsets of the data elements and code segments in the first class. After a class is automatically generated, new code segments may be added to the class as needed.

Abstract: A smart tuple manager includes a mechanism for merging a smart tuple, and for automatically generating one or more classes from existing classes when a smart tuple is merged. When a first smart tuple and a second smart tuple are merged into a new third smart tuple, a class for the third smart tuple is automatically generated from the classes for the first and second smart tuples. The class for the third smart tuple is a superset of the classes for the first and second smart tuples. After a class is automatically generated, new code segments may be added to the class as needed.

Abstract: Disclosed aspects relate to deferred joining of a stream of tuples. The stream of tuples which is to be processed by a plurality of stream operators is received. The stream of tuples may include both a first set of tuples from a first source and a second set of tuples from a second source. For future utilization with respect to a join operation which indicates to join the first and second sets of tuples, a determination is made to establish a group of tuples. A first stream operator of the plurality of stream operators establishes the group of tuples. The group of tuples has both a first subgroup and a second subgroup. A set of stream operators of the plurality of stream operators processes the group of tuples. In response to processing the group of tuples, the join operation is performed.

Abstract: Techniques are disclosed for identifying a minimal operator subsets in a distributed streams application for debugging purposes. A debugging tool receives a selection of operators from a plurality of operators included in a distributed application. The distributed application executes the plurality of operators in a runtime environment. The debugging tool identifies, based on the selected operators, a subset of the plurality of operators to execute in a debugging environment. The subset includes at least the selected operators. The debugging tool executes the subset of the plurality of operators in the debugging environment.

Abstract: Tuple communication and decision determination is provided in a streaming environment. A processor: generates mission tuples, places the mission tuples in a computing stream of a stream application, accesses computing time upon, obtains the computing time of the mission tuples, determines: a current position in the computing stream for the mission tuples and a class and one or more sub-classes that each of the mission tuples belongs to, and communicates data: between the mission tuples and between the mission tuples and one or more runtime processes associated with the computing stream or one or more external processes associated with the computing stream. The mission tuples are configured to modify operations of the computing operators in the computing stream.

Abstract: Embodiments of the disclosure include a method, a system, and a computer program product for modifying a stream operator based on the virtual resources. The method includes receiving a first resource allocation and a second resource allocation of a virtual resource for a virtual machine supporting a stream computing application. The method also includes determining whether the second resource allocation changed within a tolerance relative to the first resource allocation. The method also includes identifying a stream operator in the stream computing application using the virtual resource of the virtual machine. The method also includes modifying the stream operator to accommodate the second resource allocation in response to the second resource allocation changing relative to the first resource allocation.

Abstract: A stream application receives a stream of tuples to be processed by a plurality of processing elements that are operating on one or more compute nodes. Each processing element has one or more stream operators. The stream application assigns one or more processing cycles to software code embedded in a tuple of the stream of tuples. The tuple obtains a first status of one or more first tuples of a set of targeted tuples to be modified by a tuple modification of a stream operator. The tuple obtains a second status of one or more second tuples of the set of targeted tuples after the stream operator performs the tuple modification. The tuple determines a potential degradation based on the first status and the second status. The tuple alters the one or more first tuples to prevent the tuple modification in response to the determined potential degradation.

Abstract: A stream application receives a stream of tuples to be processed by a plurality of processing elements. The plurality of processing elements operate on one or more compute nodes. Each processing element has one or more stream operators. Segments of software code are embedded in a tuple of the stream of tuples. The tuple retrieves one or more compute node metrics. The compute node metrics describe one or more resources of a first compute node. The tuple obtains tuple information of one or more tuples of the stream of tuples to be processed by a first stream operator that operates on the one or more resources. The tuple determines a prospective resource disparity related to the first stream operator based on the obtained tuple information and the compute node metrics. The tuple transmits a resource request to the stream application based on the determined prospective resource disparity.

Abstract: A stream application receives a stream of tuples to be processed by a plurality of processing elements. The plurality of processing elements operating on one or more compute nodes. Each processing element has one or more stream operators. The stream application assigns one or more processing cycles to one or more segments of software code. The segments of software code are embedded in a tuple of the stream of tuples. The software-embedded tuple identifies a set of target tuples based upon operation criteria. The set of target tuples are a part of the stream of tuples. The software-embedded tuple performs an operation based on the set of identified target tuples.

Abstract: A stream application receives a stream of tuples to be processed by a plurality of processing elements. The plurality of processing elements operating on one or more compute nodes. Each processing element has one or more stream operators. The stream application assigns one or more processing cycles to one or more segments of software code. The segments of software code are embedded in a tuple of the stream of tuples. The software-embedded tuple identifies a set of target tuples based upon operation criteria. The set of target tuples are a part of the stream of tuples. The software-embedded tuple performs an operation based on the set of identified target tuples.

Abstract: A stream application receives a stream of tuples to be processed by a plurality of processing elements operating on one or more compute nodes. Each processing element has one or more stream operators. The stream application assigns one or more processing cycles to one or more segments of software code. The segments of software code are embedded in one or more tuples of the stream of tuples. The stream application determines that a condition is met based on the processing cycles. The stream application performs an operation based on the processing cycles.

Abstract: Disclosed aspects include managing a set of assets of a shared pool of configurable computing resources associated with a streaming application. A stream of tuples to be processed is received by a plurality of processing elements operating on the shared pool of configurable computing resources having the set of assets. A triggering event which corresponds to a data flow of the stream of tuples is detected. Based on the data flow of the stream of tuples, an asset arrangement with respect to the set of assets is determined and established. In embodiments, the stream of tuples may be processed by the plurality of processing elements operating on the shared pool of configurable computing resources having the set of assets.

Abstract: Disclosed aspects include managing a set of assets of a shared pool of configurable computing resources associated with a streaming application. A stream of tuples to be processed is received by a plurality of processing elements operating on the shared pool of configurable computing resources having the set of assets. A triggering event which corresponds to a data flow of the stream of tuples is detected. Based on the data flow of the stream of tuples, an asset arrangement with respect to the set of assets is determined and established. In embodiments, the stream of tuples may be processed by the plurality of processing elements operating on the shared pool of configurable computing resources having the set of assets.

Abstract: Embodiments of the disclosure include a method, a system, and a computer program product for modifying a stream operator based on the virtual resources. The method includes receiving a first resource allocation and a second resource allocation of a virtual resource for a virtual machine supporting a stream computing application. The method also includes determining whether the second resource allocation changed within a tolerance relative to the first resource allocation. The method also includes identifying a stream operator in the stream computing application using the virtual resource of the virtual machine. The method also includes modifying the stream operator to accommodate the second resource allocation in response to the second resource allocation changing relative to the first resource allocation.