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smpa01's avatar
smpa01
Icon for Community Champion rankCommunity Champion
2 years ago

Reading limitation spark vs sempy

Does the reading limitation (same limitation as Execute Queries)  of semantic tables through spark apply to reading through sempy?

 

I am building a production element and whether I choose spark or sempy depends on which one is NOT subject to this limitation.

 

Spark current limitations

 

 

#spark vs sempy

server = server
db = db
tbl = tbl

#spark
dataset =  spark.sql(f"""select id as id, sum(value) as value FROM pbi.{db}.{tbl} group by id""")


#sempy
dataset = (fabric
            .evaluate_dax(workspace= server,
            dataset=db,
            dax_string=query_string)
    )

 

5 Replies

  • Anonymous's avatar
    Anonymous
    Not applicable

    Hi smpa01 ,

     

    Spark limitations include for example ISNULL, IS_NOT_NULL, STARTS_WITH, ENDS_WITH, and CONTAINS.

     

    SemPy has not seen official documentation on these limitations and can bypass some of the limitations faced by Spark.SemPy may have some limitations in terms of data size and query complexity.

     

    In summary, while both Spark and SemPy have their own limitations, SemPy may have more flexibility in executing complex queries directly against Power BI datasets without some of the limitations in Spark.

     

    Best Regards,
    Yang
    Community Support Team

     

    If there is any post helps, then please consider Accept it as the solution  to help the other members find it more quickly.
    If I misunderstand your needs or you still have problems on it, please feel free to let us know. Thanks a lot!

    • smpa01's avatar
      smpa01
      Icon for Community Champion rankCommunity Champion

      I am more interested in number of rows read for which spark has clear limiations. Can you please confirm if sempy has any limitations in respect to that? Anonymous I am not interested in any other limiations sempy might have ATM.  Cause I need to handle that, if it does have any such limitations.

      • Anonymous's avatar
        Anonymous
        Not applicable

        Hi smpa01 ,

         

        I have not seen documentation that indicates sempy is limit on the number of rows that can be read.

         

        The limit I see in the documentation for sempy is:

         

        The amount of data that can be retrieved is limited by the per-query maximum memory of the capacity SKU hosting the semantic model and the Spark driver node running the notebook (see Node Size).

         

        Please see this official documentation for information:

        Read data from semantic models and write data that semantic models can consume using python - Microsoft Fabric | Microsoft Learn

         

        If you have any other questions please feel free to contact me.

         

        Best Regards,
        Yang
        Community Support Team

         

        If there is any post helps, then please consider Accept it as the solution  to help the other members find it more quickly.
        If I misunderstand your needs or you still have problems on it, please feel free to let us know. Thanks a lot!

  • Anonymous's avatar
    Anonymous
    Not applicable

    Hi smpa01 ,

     

    Is my follow-up just to ask if the problem has been solved?

     

    If so, can you accept the correct answer as a solution or share your solution to help other members find it faster?

     

    Thank you very much for your cooperation!

     

    Best Regards,
    Yang
    Community Support Team

     

    If there is any post helps, then please consider Accept it as the solution  to help the other members find it more quickly.
    If I misunderstand your needs or you still have problems on it, please feel free to let us know. Thanks a lot!

  • Anonymous's avatar
    Anonymous
    Not applicable

    Hi smpa01 ,

     

    Is my follow-up just to ask if the problem has been solved?

     

    If so, can you accept the correct answer as a solution or share your solution to help other members find it faster?

     

    Thank you very much for your cooperation!

     

    Best Regards,
    Yang
    Community Support Team

     

    If there is any post helps, then please consider Accept it as the solution  to help the other members find it more quickly.
    If I misunderstand your needs or you still have problems on it, please feel free to let us know. Thanks a lot!