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Not able to read tables in Unity Catalog parallel

subha2
New Contributor II

There are some tables under schema/database under Unity Catalog.

The Notebook need to read the table parallel using loop and thread and execute the query configured

But the sql statement is not getting executed via spark.sql() or spark.read.table().

It is giving the error "UNITY_CREDENTIAL_SCOPE_MISSING_SCOPE Missing Credential Scope. Failed to find Unity Credential Scope.."

Although there is no credential or scope involve .

Could you please suggest or advise for the issue.

1 REPLY 1

Kaniz
Community Manager
Community Manager

Hi @subha2, It seems you’re encountering an issue related to executing SQL statements in Spark.

Let’s troubleshoot this step by step:

  1. Check the Unity Catalog Configuration:

    • Verify that the Unity Catalog configuration is correctly set up. Ensure that the schema and database you’re trying to access are properly defined.
    • Confirm that the table you’re querying exists in the specified schema/database.
  2. Credential Scopes:

    • The error message indicates a missing credential scope. Even if you believe there are no credentials involved, it’s essential to check this aspect.
    • Unity Catalog might require some form of authentication or authorization, even if it’s not explicitly mentioned in your code.
    • Double-check whether any credentials (such as API keys, tokens, or service account details) are required for accessing the Unity Catalog. If so, make sure they are correctly configured.
  3. Spark Configuration:

    • Ensure that your Spark session is correctly configured. Specifically, check if the necessary properties related to Unity Catalog are set.
    • You can set these properties using spark.conf.set("property_name", "property_value").
    • Common properties related to Unity Catalog include:
      • spark.sql.catalogImplementation: Set it to "unityCatalog" to use Unity Catalog.
      • spark.sql.catalog.unityCatalog.url: Specify the URL for the Unity Catalog service.
      • spark.sql.catalog.unityCatalog.database: Set the database name.
      • spark.sql.catalog.unityCatalog.schema: Set the schema name.
  4. Query Execution:

    • When executing SQL statements, ensure that you’re using the correct syntax and that the table name is fully qualified (including schema and database).
    • Use spark.sql("SELECT * FROM schema_name.table_name") to execute your query.
    • If you’re using spark.read.table("schema_name.table_name"), it should work similarly, but make sure the table exists.
  5. Parallel Execution:

    • To read tables in parallel, consider using Spark’s parallel processing capabilities.
    • You can create multiple threads or parallel tasks to read different tables concurrently.
    • Be cautious about thread safety and synchronization when accessing shared resources (such as Spark sessions) from multiple threads.
  6. Logging and Debugging:

    • Enable detailed logging to understand what’s happening behind the scenes.
    • Check the Spark logs for any additional error messages or warnings related to Unity Catalog.
    • Use spark.sparkContext.setLogLevel("DEBUG") to set the log level to DEBUG.

Remember that even if you believe there are no credentials involved, some services may still require implicit authentication. Double-check the Unity Catalog documentation or any relevant documentation specific to your environment.

If you need more specific guidance or have additional details, feel free to share them, and I’ll be happy to assist further!

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