Table of Contents


  1. Preface
  2. Introduction to Big Data Streaming
  3. Big Data Streaming Administration
  4. Sources in a Streaming Mapping
  5. Targets in a Streaming Mapping
  6. Streaming Mappings
  7. Window Transformation
  8. Connections
  9. Sample Files

JMS Data Objects

JMS Data Objects

A JMS data object is a physical data object that accesses a JMS server. After you configure a JMS connection, create a JMS data object to read from JMS sources.
Support for JMS source is deferred. Support will be reinstated in a future release.
JMS providers are message-oriented middleware systems that send JMS messages. The JMS data object connects to a JMS provider to read or write data.
The JMS data object can read JMS messages from a JMS provider message queue . When you configure a JMS data object, configure properties to reflect the message structure of the JMS messages. The input ports and output ports are JMS message headers.
When you configure the read data operation properties, specify the format in which the JMS data object reads data. You can specify XML, JSON, or Flat as format. When you specify XML format, you must provide an XSD file. When you specify JSON, you must provide a sample file.
You can pass any payload format directly from source to target in Streaming mappings. You can project columns in binary format pass a payload from source to target in its original form or to pass a payload format that is not supported.
Streaming mappings can read, process, and write hierarchical data. You can use array, struct, and map complex data types to process the hierarchical data. You assign complex data types to ports in a mapping to flow hierarchical data. Ports that flow hierarchical data are called complex ports.
For more information about processing hierarchical data, see the
Informatica Big Data Management User Guide


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