How to call a table created with create_table using dlt in a separate notebook?

rt-slowth
Contributor

‎11-30-2023 03:28 PM

I created a separate pipeline notebook to generate the table via DLT, and a separate notebook to write the entire output to redshift at the end. The table created via DLT is called spark.read.table("{schema}.{table}").
This way, I can import

[MATERIALIZED_VIEW_OPERATION_NOT_ALLOWED.REQUIRES_SHARED_COMPUTE] The materialized view operation query is not allowed: Cannot query the Materialized View main.voyager.shop_silver from an Assigned or No Isolation Shared cluster, please use a Shared cluster or a Databricks SQL warehouse instead.

I get this error. How can I fix it?

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rt-slowth
Contributor
In response to Retired_mod

‎12-03-2023 09:34 PM

Enable Materialized Views:

- Consider using DBSQL Serverless (recommended) or Pro warehouse for materialized views.

- Ensure that materialized view features are enabled for your workspace.

Can you point me to the documentation for this workaround?

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rt-slowth
Contributor
In response to rt-slowth

‎12-03-2023 09:40 PM

@Retired_mod 

 

Enable Materialized Views:

  • Ensure that materialized view features are enabled for your workspace.
  • Consider using DBSQL Serverless (recommended) or Pro warehouse for materialized views.

 

Can you point me to the documentation for this workaround?