Table of Contents


  1. Preface
  2. Introduction to Informatica Data Engineering Integration
  3. Mappings
  4. Mapping Optimization
  5. Sources
  6. Targets
  7. Transformations
  8. Python Transformation
  9. Data Preview
  10. Cluster Workflows
  11. Profiles
  12. Monitoring
  13. Hierarchical Data Processing
  14. Hierarchical Data Processing Configuration
  15. Hierarchical Data Processing with Schema Changes
  16. Intelligent Structure Models
  17. Blockchain
  18. Stateful Computing
  19. Appendix A: Connections Reference
  20. Appendix B: Data Type Reference
  21. Appendix C: Function Reference

Run-time Process on the Blaze Engine

Run-time Process on the Blaze Engine

To run a mapping on the Informatica Blaze engine, the Data Integration Service submits jobs to the Blaze engine executor. The Blaze engine executor is a software component that enables communication between the Data Integration Service and the Blaze engine components on the Hadoop cluster.
The following Blaze engine components appear on the Hadoop cluster:
  • Grid Manager. Manages tasks for batch processing.
  • Orchestrator. Schedules and processes parallel data processing tasks on a cluster.
  • Blaze Job Monitor. Monitors Blaze engine jobs on a cluster.
  • DTM Process Manager. Manages the DTM Processes.
  • DTM Processes. An operating system process started to run DTM instances.
  • Data Exchange Framework. Shuffles data between different processes that process the data on cluster nodes.
The following image shows how a Hadoop cluster processes jobs sent from the Blaze engine executor:
This image shows the Blaze engine architecture diagram.
The following events occur when the Data Integration Service submits jobs to the Blaze engine executor:
  1. The Blaze Engine Executor communicates with the Grid Manager to initialize Blaze engine components on the Hadoop cluster, and it queries the Grid Manager for an available Orchestrator.
  2. The Grid Manager starts the Blaze Job Monitor.
  3. The Grid Manager starts the Orchestrator and sends Orchestrator information back to the LDTM.
  4. The LDTM communicates with the Orchestrator.
  5. The Grid Manager communicates with the Resource Manager for available resources for the Orchestrator.
  6. The Resource Manager handles resource allocation on the data nodes through the Node Manager.
  7. The Orchestrator sends the tasks to the DTM Processes through the DTM Process Manger.
  8. The DTM Process Manager continually communicates with the DTM Processes.
  9. The DTM Processes continually communicate with the Data Exchange Framework to send and receive data across processing units that run on the cluster nodes.


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