Reading using sqlanalytics connector in spark using Notebooks - Synapse

Question

I am reading a table in the Synapse notebooks using the sqlanalytics connector. When the spark encounters an empty string in a column , it is trying to convert to None/Null.

I am getting error, when the column is NOT NULL .

Column ordinal: 7, Expected data type: NVARCHAR(50) collate SQL_Latin1_General_CP1_CI_AS NOT NULL

I am trying to fill with a default value, so I can read the DataFrame. It doesn't convert it somehow.

Is there any work around to this?

Answer 1

CREATE TABLE [dbo].[DimCustomer2] (
[CustomerKey] INT NOT NULL,
[GeographyKey] INT NULL,
[CustomerAlternateKey] nvarchar(15) COLLATE SQL_Latin1_General_CP1_CI_AS NOT NULL
)

insert into [dbo].[DimCustomer2] values
(
1,1,'')

Answer 2

Hi @Sivagnana Sundaram, Krithiga ,

We got response from product team on the above issue. Kindly have a look:

" Yes, this is the current behavior of Synapse/Polybase: an empty string gets treated as null on export. The upcoming Gen3 DW (ded SQL Pool) will address this which will preview late 2022. Since the fix is non-trivial, there are no plans to fix for current Gen2.

However, a couple options can be done to get unblocked here:

1. When doing CETAS export, convert the empty strings to a unique placeholder value or even an empty space. The round-trip will work and differentiate null vs. empty fields.

 CREATE EXTERNAL TABLE [dbo].[abc]  
    WITH (DATA_SOURCE = [SQLAnalyticsConnectorDataSourceTest1],LOCATION = N'/abc',FILE_FORMAT = [SQLAnalyticsConnectorDefaultFileFormat798e8ca0543342a6b43e0787ab2a7db1])  
    AS  
    SELECT  
    CASE WHEN name = '' THEN ' ' END AS name  
    FROM "dbo"."abc1"  

2. Use CSV instead of parquet and specify a STRING_DELIMITER. This will natively support null/empty string differentiation as well without any work-arounds. "

Hope this will help. Please let us know if any further queries.

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