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homanz's avatar
homanz
Advocate I
3 months ago
Solved

Temp views don't work when selecting tables with a schema name using Spark SQL

I created a new temporary view using Spark SQL. Code is below

 

CREATE OR REPLACE TEMPORARY VIEW tmpvw1 AS
SELECT * FROM IM.test
 
In next step, I tried to select the temp view tmpvw1 using the following code:
 
SELECT * FROM tmpvw1
 

Then, I got this error:

"Error
[TABLE_OR_VIEW_NOT_FOUND] The table or view `IM`.`test` cannot be found. Verify the spelling and correctness of the schema and catalog. If you did not qualify the name with a schema, verify the current_schema() output, or qualify the name with the correct schema and catalog. To tolerate the error on drop use DROP VIEW IF EXISTS or DROP TABLE IF EXISTS. SQLSTATE: 42P01; line 1 pos 14; 'Project [upcast(getviewcolumnbynameandordinal(`tmpvw1`, new_column, 0, 1), StringType) AS new_column#690, upcast(getviewcolumnbynameandordinal(`tmpvw1`, TestCol, 0, 1), StringType) AS TestCol#691] +- 'Project [*] +- 'UnresolvedRelation [IM, test], [], false"
 
Temp views seem to work fine when I only use tables in the dbo schema and don't specify the schema name. For example, SELECT * from tableA. Temp views start to fail when I add a schema name to tables. I often need to join tables in different schemas. Is it a bug in temp view? how to fix it? Thanks!
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6 Replies

  • deborshi_nag's avatar
    deborshi_nag
    Super User
    3 months ago

    Hello homanz 

     

    Fabric relies on an internal session database for Spark session and lakehouse binding. If you run SELECT current_database() as current_db, you'll notice a temporary database name appears.

     

    To resolve this, always use a four-part name with backticks—`<Your Workspace Name>`.Lakehouse.Schema.Table—when referencing tables. You can find your schema's namespace by running the SQL below and checking the "namespace" column.

    SHOW TABLES in IM;

     

    • homanz's avatar
      homanz
      Advocate I
      3 months ago

      Hi ati_puri  and deborshi_nag, thanks both for your sugguestion.

       

      Using the schema name works only for joining tables within a single schema, but we have tables from different schemas. So, this solution won’t work for us.

       

      Using the full four-part table name also works, but we have to parameterise the workspace name in all our SQL code for CI/CD deployment, which makes the code very messy and hard to read.

       

      One solution I found is to wrap the SQL code in the PySpark createOrReplaceTempView function. It’s surprising that PySpark can somehow resolve all the schema names from different tables, but SparkSQL cannot.

       

      %%pyspark
      spark.sql("""
      --insert SQL code below
      SELECT
          *
      from
          IM.test t1
          left join
          ref.testref t2
          on t1.key= t2.key

      """).createOrReplaceTempView("tmp_python_view")

       

      Do you know if this issue will be fixed by MS soon?

      • v-veshwara-msft's avatar
        v-veshwara-msft
        Community Support
        3 months ago

        Hi homanz ,


        Thanks for reaching out to Microsoft Fabric Community.

        At the moment, this appears to be the current behavior of Spark SQL in schema enabled Lakehouses rather than an issue that can be resolved through an immediate hotfix. The PySpark approach you identified is currently the recommended workaround.

         

        Microsoft has also indicated that schema enabled Lakehouses in Spark still have some limitations, with additional support and improvements expected to roll out gradually over the coming months.

        Lakehouse Schemas (Generally Available) - Microsoft Fabric Community

         

        For more details: Spark views in lakehouses - Microsoft Fabric | Microsoft Learn

         

        You may also consider raising this as an enhancement request through the Fabric Ideas - Microsoft Fabric Community so the product team can review and prioritize support for this scenario in future updates.

         

        Hope this helps. Please reach out for further assistance.
        Thank you.