Drift file not updating


18-Sep-2020 06:31

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.The basic Parquet implementation looks like this: As with Avro data, the Hive Metadata processor passes records through the first output stream - the data stream.Each time the destination closes an output file, it creates a file-closure event that triggers the Map Reduce executor to start an Avro to Parquet Map Reduce job.The Map R FS destination then writes the data to the updated table.When writing data without the new fields to the updated table, the destination inserts null values for the missing fields.It generates metadata records that describe the necessary changes and passes it to the Hive Metastore destination.The Hive Metadata processor also adds information to the header of each record and passes the records to the Hadoop FS destination or the Map R FS destination.

You can set up an alert to notify you when the Hive Metastore destination makes a change.enables creating and updating Hive tables based on record requirements and writing data to HDFS or Map R FS based on record header attributes.