Table of Contents

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  1. Preface
  2. Introduction to Big Data Streaming
  3. Big Data Streaming Configuration
  4. Sources in a Streaming Mapping
  5. Targets in a Streaming Mapping
  6. Streaming Mappings
  7. Window Transformation
  8. Appendix A: Connections
  9. Appendix B: Data Type Reference
  10. Appendix C: Sample Files

Big Data Streaming User Guide

Big Data Streaming User Guide

MapRStreams Data Objects

MapRStreams Data Objects

A MapRStreams data object is a physical data object that represents data in a MapR Stream. After you create a MapRStreams connection, create a MapRStreams data object to write data to MapR Streams.
Before you create and use MapR Stream data objects in Streaming mappings, complete the required prerequisites.
For more information about the prerequisite tasks, see the
Informatica Big Data Management Cluster Integration Guide
.
When you write data to a MapR stream, specify the name of the stream that you publish to.
After you create a MapRStreams data object, create a write data object operation. You can then add the data object write operation as a target in Streaming mappings.
When you configure the data operation properties, specify the format in which the MapR Streams data object writes data. You can specify XML, JSON, or Avro as format. When you specify XML format, you must provide an XSD file. When you specify Avro format, provide a sample Avro schema in a .avsc 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
.