Abstract: A set of resources required to process a data integration job is determined. In response to determining that the set of resources is not available, queue occupation, for each queue in the computing environment, is predicted. Queue occupation is a workload of queue resources for a future time based on a previous workload. A best queue is selected based on the predicted queue occupation. The best queue is the queue or queues in the computing environment available to be assigned to process the data integration job without preemption. The data integration job is processed using the best queue. It is determined whether a preemption event occurred causing the removal of resources from the best queue. A checkpoint is created in response to determining that a preemption event occurred. The checkpoint indicates the last successful operation completed and provides a point where processing can resume when resources become available.

Abstract: A set of resources required to process a data integration job is determined. In response to determining that the set of resources is not available, queue occupation, for each queue in the computing environment, is predicted. Queue occupation is a workload of queue resources for a future time based on a previous workload. A best queue is selected based on the predicted queue occupation. The best queue is the queue or queues in the computing environment available to be assigned to process the data integration job without preemption. The data integration job is processed using the best queue. It is determined whether a preemption event occurred causing the removal of resources from the best queue. A checkpoint is created in response to determining that a preemption event occurred. The checkpoint indicates the last successful operation completed and provides a point where processing can resume when resources become available.

Abstract: Disclosed aspects relate to data integration application execution management using both a set of managed nodes and a set of unmanaged nodes. An execution request for a data integration application may be sensed. A first set of commands of the data integration application may be assigned to the set of managed nodes. A second set of commands of the data integration application may be assigned to the set of unmanaged nodes. Execution of the data integration application may be initiated using the set of managed nodes to process the first set of commands and the set of unmanaged nodes to process the second set of commands.

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: 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: 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: 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: Disclosed aspects relate to data integration application execution management using both a set of managed nodes and a set of unmanaged nodes. An execution request for a data integration application may be sensed. A first set of commands of the data integration application may be assigned to the set of managed nodes. A second set of commands of the data integration application may be assigned to the set of unmanaged nodes. Execution of the data integration application may be initiated using the set of managed nodes to process the first set of commands and the set of unmanaged nodes to process the second set of commands.

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: 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: 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: Embodiments presented herein provide techniques for optimizing parallel data flows of a batch processing job using a profile of the processing job. An application retrieves a job profile for a processing job. The processing job has a plurality of processing stages specified in an execution profile. The job profile includes statistical data for at least one of the processing stages obtained during prior executions of the job. The application modifies properties of the execution profile based on the job profile to optimize the execution of the job. The application executes the processing job with the modified execution profile.

Abstract: Embodiments presented herein provide techniques for optimizing parallel data flows of a batch processing job using a profile of the processing job. An application retrieves a job profile for a processing job. The processing job has a plurality of processing stages specified in an execution profile. The job profile includes statistical data for at least one of the processing stages obtained during prior executions of the job. The application modifies properties of the execution profile based on the job profile to optimize the execution of the job. The application executes the processing job with the modified execution profile.

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: Disclosed aspects relate to data integration application execution management using both a set of managed nodes and a set of unmanaged nodes. An execution request for a data integration application may be sensed. A first set of commands of the data integration application may be assigned to the set of managed nodes. A second set of commands of the data integration application may be assigned to the set of unmanaged nodes. Execution of the data integration application may be initiated using the set of managed nodes to process the first set of commands and the set of unmanaged nodes to process the second set of commands.

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: 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.