MergeSchema Not Working

[DJey]

Hi All,

I have a scenario where my Exisiting Delta Table looks like below:

Now I have an incremental data with an additional column i.e. owner:

Dataframe Name --> scdDFBelow is the code snippet to merge Incremental Dataframe to targetTable, but the new column is not getting added:

spark.conf.set("spark.databricks.delta.schema.autoMerge.enabled",True) --> this is also enabled.

But still no luck. Below is the final result which i'm currently getting:

Data looks correct, but the only issue is New Column i.e. Owner is still not merged in targetTable. 

Someone please help.

Thanks!

[etsyal1e2r3 · Accepted solution]

Just add that column to the table with an ALTER TABLE statement. You should capture each table/dataframe columns as a list with df.columns, compare them, and if the table is missing anything do the alter table. Then run your code.

[Anonymous]

Hi @Divyansh Jain​ 

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[DJey]

This is resolved. Thanks, everyone!

[DJey]

@Vidula Khanna​  Enabling the below property resolved my issue:

spark.conf.set("spark.databricks.delta.schema.autoMerge.enabled",True) 

Thanks v much!

[g96g]

sorry, can you please explain what was the problem? cause you have already that property enabled 

[Amin112]

In Databricks Runtime 15.2 and above, you can specify schema evolution in a merge statement using SQL or Delta table APIs:

MERGE WITH SCHEMA EVOLUTION INTO target
USING source
ON source.key = target.key
WHEN MATCHED THEN
UPDATE SET *
WHEN NOT MATCHED THEN
INSERT *
WHEN NOT MATCHED BY SOURCE THEN
DELETE