Abstract: Performing an extract, transform, and load (ETL) process. Column data is received by a stage of the ETL process. The size of the received column data is ascertained by the stage. In response to determining that the size of the column data exceeds a predefined threshold, the stage saves the column data and creates a data locator associated with the column data. The created data locator advances through successive downstream stages of the ETL process as a replacement for the column data.

Abstract: Provided are a computer program product, system, and method for allocating physical nodes for processes in an execution plan. An execution plan is generated indicating a plurality of processes. A resource requirement is generated indicating requested physical nodes and an assignment of the processes to execute on the requested physical nodes. A determination is made from the resource requirement of a resource allocation of physical nodes for the requested physical nodes and the processes. The execution plan is updated to generate an updated execution plan indicating the physical nodes on which the processes will execute according to the received resource allocation.

Abstract: Embodiments presented herein provide task management capabilities for designing a complex data integration workflow in an integrated design environment (IDE). A task management tool of the IDE allows a developer to tag various stages of a data integration workflow in a non-linear manner. When the task management tool receives a tag for a given stage, the task management tool identifies incomplete tasks associated with the stage and generates a task list that includes the incomplete tasks. The developer may return to completing any of the tasks in the workflow in any sequence as desired.

Abstract: Provided are a computer program product, system, and method for allocating physical nodes for processes in an execution plan. An execution plan is generated indicating a plurality of processes. A resource requirement is generated indicating requested physical nodes and an assignment of the processes to execute on the requested physical nodes. A determination is made from the resource requirement of a resource allocation of physical nodes for the requested physical nodes and the processes. The execution plan is updated to generate an updated execution plan indicating the physical nodes on which the processes will execute according to the received resource allocation.

Abstract: Provided are a computer program product, system, and method for allocating physical nodes for processes in an execution plan. An execution plan is generated indicating a plurality of processes. A resource requirement is generated indicating requested physical nodes and an assignment of the processes to execute on the requested physical nodes. A determination is made from the resource requirement of a resource allocation of physical nodes for the requested physical nodes and the processes. The execution plan is updated to generate an updated execution plan indicating the physical nodes on which the processes will execute according to the received resource allocation.

Abstract: Provided are techniques for improving data locality for parallel applications running in a big data distributed file system with a dynamic node group. In response to a consumer job starting to read one or more files in a big data distributed file system having multiple nodes, node group information for the one or more files to be read is retrieved, wherein the node group information identifies nodes from the multiple nodes on which a producer job wrote the one or more files, and the consumer job is assigned to the nodes identified by the node group information to allow for local reading of the one or more files by the consumer job.

Abstract: An electrical generator system for a vehicle comprises a power plant having a fluid cooling system, an alternating current generator mechanically coupled to the power plant, a generator control coupled to receive electrical input from the alternating current generator, and an engine speed control configured to receive a control signal from the generator control and to provide an input to the power plant to control speed of the power plant. The fluid cooling system can be configured to cool the alternating current generator. In one example, the generator can be used to electrically power a motor that can be used to mechanically power a liquid pump and an air blower. In one example, the fluid cooling system can be used to cool the generator and the motor, and heat liquid pumped by the liquid pump. In one example, the heated liquid can be used in conjunction with a carpet cleaning tool that utilizes a vacuum generated by the air blower.

Abstract: A computer-implemented method includes identifying a logical node. The logical node is associated with one or more source stages. The computer-implemented method further includes identifying one or more file block components. The one or more file block components include a retrieval target for at least one of the one or more source stages. The computer-implemented method further includes identifying one or more physical nodes and determining, for each of the one or more physical nodes, a degree value. A corresponding computer program product and computer system are also disclosed.

Abstract: System, method, and computer program product to process parallel computing tasks on a distributed computing system, by computing an execution plan for a parallel computing job to be executed on the distributed computing system, the distributed computing system comprising a plurality of compute nodes, generating, based on the execution plan, an ordered set of tasks, the ordered set of tasks comprising: (i) configuration tasks, and (ii) execution tasks for executing the parallel computing job on the distributed computing system, and launching a distributed computing application to assign the tasks of the ordered set of tasks to the plurality of compute nodes to execute the parallel computing job on the distributed computing system.

Abstract: Provided are techniques for improving data locality for parallel applications running in a big data distributed file system with a dynamic node group. In response to a consumer job starting to read one or more files in a big data distributed file system having multiple nodes, node group information for the one or more files to be read is retrieved, wherein the node group information identifies nodes from the multiple nodes on which a producer job wrote the one or more files, and the consumer job is assigned to the nodes identified by the node group information to allow for local reading of the one or more files by the consumer job.

Abstract: The present disclosure provides a method and apparatus for re-using existing data flow design jobs in a data integration design environment (IDE). An example method generally includes receiving input placing one or more data flow operators on a design canvas of the IDE, searching a database of existing data flow job designs for existing data flow job designs that include the one or more data flow operators, and displaying a list of the existing data flow job designs that include the one or more data flow operators.

Abstract: A request for analysis of a data integration job is received that includes one or more features and criteria for the analysis. Each feature is extracted from a job model representing the job by invoking a corresponding analytical rule for each feature. The analytical rule includes one or more operations and invoking the analytical rule performs the operations to analyze one or more job components associated with the corresponding feature as represented in the job model and to extract information pertaining to that feature.

Abstract: The method of managing performance of data integration are described. A performance analyzer may receive data about a data integration job execution. The performance analyzer may determine whether there is a performance issue of the data integration job execution. The performance analyzer analyzes the data about the data integration job execution when there is a performance issue. The performance analyzer generates a job execution design recommendation based on the analysis of the data and a set of predefined recommendation rules. The performance analyzer then displays the data about the data integration job execution and when there is a generated job execution design recommendation, displaying the job execution design recommendation.

Abstract: At least one application in a computing environment is executed and one or more performance metrics of the application are measured. The measured performance metrics are analyzed and an operational performance regression is detected. The detected operational performance regression is correlated with one or more recorded changes and the correlated changes are identified as a cause of the operational performance regression. The elements of the computing environment are alerted in accordance with the identified changes to adjust operational performance.

Abstract: System, method, and computer program product to perform an operation for task-based modeling for parallel data integration, by determining, for a data flow, a set of processing units, each of the set of processing units defining one or more data processing operations to process the data flow, generating a set of tasks to represent the set of processing units, each task in the set of tasks comprising one or more of the data processing operations of the set of processing units, optimizing the set of tasks based on a set of characteristics of the data flow, and generating a composite execution plan based on the optimized set of tasks to process the data flow in a distributed computing environment.

Abstract: System, method, and computer program product to perform an operation for task-based modeling for parallel data integration, by determining, for a data flow, a set of processing units, each of the set of processing units defining one or more data processing operations to process the data flow, generating a set of tasks to represent the set of processing units, each task in the set of tasks comprising one or more of the data processing operations of the set of processing units, optimizing the set of tasks based on a set of characteristics of the data flow, and generating a composite execution plan based on the optimized set of tasks to process the data flow in a distributed computing environment.

Abstract: A computer-implemented method includes identifying a logical node. The logical node is associated with one or more source stages. The computer-implemented method further includes identifying one or more file block components. The one or more file block components include a retrieval target for at least one of the one or more source stages. The computer-implemented method further includes identifying one or more physical nodes and determining, for each of the one or more physical nodes, a degree value. A corresponding computer program product and computer system are also disclosed.

Abstract: Data flow disruptions over a series of data processing operators can be detected by a computer system that generates a profile for data flow at an operator. The profile can include data input, processing, and output wait times. Using the profile, the system can detect potential flow disruptions. If the potential disruption satisfies a rule, it is considered a data flow disruption and a recommendation associated with the satisfied rule is identified. The recommendation and the operator identity is displayed.

Abstract: Techniques are disclosed for data integration on retargetable engines in a networked environment. The networked environment includes data processing engines of different types and having different sets of characteristics. A request is received execute a data flow model in the networked environment. The data flow model includes data flow objects. A first data processing engine is programmatically selected based on a predefined set of criteria and the sets of characteristics of the data processing engines. The data flow model is executed using the selected data processing engine and responsive to the request.

Abstract: A request for analysis of a data integration job is received that includes one or more features and criteria for the analysis. Each feature is extracted from a job model representing the job by invoking a corresponding analytical rule for each feature. The analytical rule includes one or more operations and invoking the analytical rule performs the operations to analyze one or more job components associated with the corresponding feature as represented in the job model and to extract information pertaining to that feature.