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- Printing secret value in Databricks - Stack Overflow
2 Building on @camo's answer, since you're looking to use the secret value outside Databricks, you can use the Databricks Python SDK to fetch the bytes representation of the secret value, then decode and print locally (or on any compute resource outside of Databricks)
- Is there a way to use parameters in Databricks in SQL with parameter . . .
EDIT: I got a message from Databricks' employee that currently (DBR 15 4 LTS) the parameter marker syntax is not supported in this scenario It might work in the future versions Original question:
- Databricks shared access mode limitations - Stack Overflow
You're correct about listed limitations But when you're using Unity Catalog, especially with shared clusters, you need to think a bit differently than before UC + shared clusters provide very good users isolation, not allowing to access data without necessary access control (DBFS doesn't have access control at all, and ADLS provides access control only on the file level) You will need to
- Databricks: managed tables vs. external tables - Stack Overflow
While Databricks manages the metadata for external tables, the actual data remains in the specified external location, providing flexibility and control over the data storage lifecycle This setup allows users to leverage existing data storage infrastructure while utilizing Databricks' processing capabilities
- Databricks shows REDACTED on a hardcoded value - Stack Overflow
It's not possible, Databricks just scans entire output for occurences of secret values and replaces them with " [REDACTED]" It is helpless if you transform the value For example, like you tried already, you could insert spaces between characters and that would reveal the value You can use a trick with an invisible character - for example Unicode invisible separator, which is encoded as
- how to get databricks job id at the run time - Stack Overflow
1 I am trying to get the job id and run id of a databricks job dynamically and keep it on in the table with below code
- REST API to query Databricks table - Stack Overflow
Is databricks designed for such use cases or is a better approach to copy this table (gold layer) in an operational database such as azure sql db after the transformations are done in pyspark via databricks? What are the cons of this approach? One would be the databricks cluster should be up and running all time i e use interactive cluster
- Databricks - Download a dbfs: FileStore file to my Local Machine
Method3: Using third-party tool named DBFS Explorer DBFS Explorer was created as a quick way to upload and download files to the Databricks filesystem (DBFS) This will work with both AWS and Azure instances of Databricks You will need to create a bearer token in the web interface in order to connect
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