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Medium severitydata flow

Power BI Refresh Error:
DF-Hive-InvalidStorageType

What does this error mean?

The Hive connector in ADF Mapping Data Flows supports only Azure Blob Storage or ADLS Gen2 as staging storage.

Common causes

  • 1The Hive linked service staging storage references an unsupported storage type (e.g., Azure Files, NFS, or a third-party object store)
  • 2The staging linked service type was changed after initial setup and is no longer a Blob or Gen2 linked service
  • 3No staging storage type is set in the Hive linked service — the field is empty or set to 'None'
  • 4The Hive HDInsight cluster version requires a specific storage type that differs from what is configured

How to fix it

  1. 1Open the Hive linked service in ADF Studio and go to 'Staging storage' section.
  2. 2Verify the staging storage linked service is of type 'Azure Blob Storage' or 'Azure Data Lake Storage Gen2'.
  3. 3If neither is available, create a new linked service of the correct type and assign it to the Hive staging setting.
  4. 4Test connection both the staging linked service and the Hive linked service to confirm connectivity.
  5. 5Re-publish the linked service and trigger a new debug data flow run to confirm the error is resolved.

Frequently asked questions

What storage types does the Hive connector support for staging?

Only Azure Blob Storage and ADLS Gen2. Other Azure storage types and third-party stores are not supported. If you need a different backend, consider migrating to a different Hive hosting option.

Can I use Azure Data Lake Storage Gen1 for Hive staging?

No — ADLS Gen1 is end-of-life as of February 2024 and is not supported for Hive staging. Use ADLS Gen2 (with hierarchical namespace enabled) instead.

Why is the staging storage type even required for Hive?

ADF Mapping Data Flows use a staging area to exchange data between the Spark cluster and the Hive server — this is a mandatory part of the Hive connector architecture.

Will changing the staging storage type cause data loss?

No — the staging area is a temporary workspace used during pipeline execution. Existing data in your Hive tables is not affected by changing the staging storage configuration.

Official documentation: https://learn.microsoft.com/en-us/azure/data-factory/data-flow-troubleshoot-guide

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