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esobrino
Helper II
Helper II

Fabric Notebook in VS-Code '%%pyspark' not found - expectations...

Its awesome to be able to run Fabric Workspace Notebooks in VS Code!

 

I created the Notebook in a workspace ( and having the option to work with it in VS-Code I took the opportunity...   So far all looks good the "Synapse PySpark environment completted successfully..." so I am ready to go.

 

In the Notebook, the first statments worked as expected, for example:

 

df = spark.sql("SELECT * FROM LkStaging.tl_2019_us_zcta510 LIMIT 1000")
display(df.take(10))
df.dtypes

 

But the following (that works find in Fabric Notebook) failed (note that the default workspace/Lakehouse is "WsStaging/LkStaging"):

 

%%sql
select * from tl_2019_us_zcta510

 

The error stated:

 

UsageError: Cell magic '%%sql' not found.

 

Any subsequent cells that stated the target language in the same manner also fail...

 

I expected the that I don't need to massage the Notebook when is in VS-Code and that the same exact cell statements interroperate in both environment without any kind of update.

 

Your thoughts...

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1 ACCEPTED SOLUTION

Hi @esobrino 
Apologies for the issue you have been facing. We haven't supported %%sql magic command in vscode. This is the reason why you are getting the error.
PySpark is the only language we support now. If you would like to use spark sql, you can run it via spark.sql('select * from ....').

Hope this helps. Please let me know if you have any further questions.

View solution in original post

3 REPLIES 3
v-nikhilan-msft
Community Support
Community Support

Hi @esobrino 
Thanks for using Fabric Community.
At this time, we are reaching out to the internal team to get some help on this. We will update you once we hear back from them.
Thanks

Hi @esobrino 
Apologies for the issue you have been facing. We haven't supported %%sql magic command in vscode. This is the reason why you are getting the error.
PySpark is the only language we support now. If you would like to use spark sql, you can run it via spark.sql('select * from ....').

Hope this helps. Please let me know if you have any further questions.

Got it!  its no problem...  greatly appraciate the quick response/feedback.

 

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