Table of Contents

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  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Mappings in the Hadoop Environment
  4. Mapping Sources in the Hadoop Environment
  5. Mapping Targets in the Hadoop Environment
  6. Mapping Transformations in the Hadoop Environment
  7. Processing Hierarchical Data on the Spark Engine
  8. Configuring Transformations to Process Hierarchical Data
  9. Processing Unstructured and Semi-structured Data with an Intelligent Structure Model
  10. Stateful Computing on the Spark Engine
  11. Monitoring Mappings in the Hadoop Environment
  12. Mappings in the Native Environment
  13. Profiles
  14. Native Environment Optimization
  15. Cluster Workflows
  16. Connections
  17. Data Type Reference
  18. Function Reference
  19. Parameter Reference

Configure the Blaze Engine to Use Node Labels

Configure the Blaze Engine to Use Node Labels

If you enable node labeling in the Hadoop environment, you can use node labels to run Blaze components as YARN applications on specific cluster nodes.
To run Blaze components on the labeled cluster nodes, specify the node labels when you configure the Blaze engine.
To specify node labels on the Blaze engine, list the node labels in the following Hadoop connection property:
Property
Description
Blaze YARN Node Label
Node label that determines the node on the Hadoop cluster where the Blaze engine runs. If you do not specify a node label, the Blaze engine runs on the nodes in the default partition.
If the Hadoop cluster supports logical operators for node labels, you can specify a list of node labels. To list the node labels, use the operators
&&
(AND),
||
(OR), and
!
(NOT).
When the Blaze engine uses node labels, Blaze components might be redundant on the labeled nodes. If a node contains multiple labels and you specify the labels in different Hadoop connections, multiple Grid Manager, Orchestrator, or Job Monitor instances might run on the same node.


Updated October 23, 2019