Table of Contents

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  1. Preface
  2. Analyst Service
  3. Catalog Service
  4. Content Management Service
  5. Data Integration Service
  6. Data Integration Service Architecture
  7. Data Integration Service Management
  8. Data Integration Service Grid
  9. Data Integration Service REST API
  10. Data Integration Service Applications
  11. Data Privacy Management Service
  12. Enterprise Data Preparation Service
  13. Interactive Data Preparation Service
  14. Informatica Cluster Service
  15. Mass Ingestion Service
  16. Metadata Access Service
  17. Metadata Manager Service
  18. Model Repository Service
  19. PowerCenter Integration Service
  20. PowerCenter Integration Service Architecture
  21. High Availability for the PowerCenter Integration Service
  22. PowerCenter Repository Service
  23. PowerCenter Repository Management
  24. PowerExchange Listener Service
  25. PowerExchange Logger Service
  26. SAP BW Service
  27. Search Service
  28. System Services
  29. Test Data Manager Service
  30. Test Data Warehouse Service
  31. Web Services Hub
  32. Application Service Upgrade
  33. Appendix A: Application Service Databases
  34. Appendix B: Connecting to Databases from Windows
  35. Appendix C: Connecting to Databases from UNIX or Linux
  36. Appendix D: Updating the DynamicSections Parameter of a DB2 Database

Maximum Number of Concurrent Jobs on a Grid

Maximum Number of Concurrent Jobs on a Grid

You can set the number of deployed and on-demand jobs that the Data Integration Service process can run concurrently.
You can configure the following Data Integration Service properties:
Maximum on-demand execution pool size
Determine the maximum number of on-demand jobs that you can run concurrently. On-demand jobs include data previews, profiling jobs, SQL queries, and web service requests. The Data Integration Service immediately runs on-demand jobs if enough resources are available. Otherwise, the Data Integration Service rejects the job. The default value is 10.
Maximum native batch execution pool size
Determines the maximum number of jobs that you can run concurrently in the native environment. The Data Integration Service moves deployed native jobs from the queue to the native batch pool when enough resources are available. The default value is 10.
Maximum Hadoop batch execution pool size
Determines the maximum number of deployed jobs that you can run concurrently in the Hadoop environment. The Data Integration Service moves deployed Hadoop jobs from the queue to the Hadoop batch pool when enough resources are available. The default value is 100.
When the Data Integration Service runs on a grid, the maximum number of deployed and on-demand jobs that can run concurrently across the grid are calculated as follows:
Maximum on-demand pool size * Number of running service processes
Maximum native batch pool size * Number of running service processes
Maximum Hadoop batch pool size * Number of running service processes
For example, a Data Integration Service grid includes three running service processes. If you set the Hadoop batch pool size to 10, each Data Integration Service process can run up to 10 deployed Hadoop jobs concurrently. A total of 30 deployed Hadoop jobs can run concurrently on the grid. If you try to run more than 30 Hadoop jobs, the Data Integration Service queues the jobs until there is space in the pool.
When you increase the pool size values, the Data Integration Service uses more hardware resources such as CPU, memory, and system I/O. Set these values based on the resources available on the nodes in the grid. For example, consider the number of CPUs on the machines where Data Integration Service processes run and the amount of memory that is available to the Data Integration Service.
If the Data Integration Service grid runs jobs in separate remote processes, additional concurrent jobs might not run on compute nodes after you increase the value of these properties. You might need to override compute node attributes to increase the number of concurrent jobs on each compute node. For more information, see Override Compute Node Attributes to Increase Concurrent Jobs.