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Connect the data stream to the Hadoop FS or Map R FS destination to write data to the destination system using record header attributes.

The Hive Metadata processor passes the metadata record through the second output stream - the metadata output stream.

Note that you could also write the data to Map R FS -- the steps are almost identical to this case study, you'd just use a different destination.

You can use the Hive Metadata processor, Hive Metastore destination for metadata processing, and Hadoop FS or Map R FS destination for data processing in any pipeline where the logic is appropriate.

A basic implementation of the Hive Metadata processor passes records through the first output stream - the data stream.

To do this, add and configure a Kafka Consumer to read the data into the pipeline, then connect it to a Hive Metadata processor.

The processor assesses the record structure and generates a metadata record that describes any required Hive metadata changes.

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