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Hello,
I had a schema-enforced lakehouse and tried to create a table with Pyspark. Code as below:
Solved! Go to Solution.
Hi @schou ,
As far as I know this error message occurs due to architectural mismatch occurs .
You can try using the following syntax:
df = spark.read.format(“csv”).option(“header”, “false”).load( “Files/2019.csv")
# Create a new table
df.write.format(“delta”).saveAsTable(“test2”)
If the above syntax doesn't take effect, you may want to consider leaving this message unchecked, as checking it may cause the system to apply more stringent checks to the data being written
Best Regards,
Liu Yang
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hi @schou ,
As far as I know this error message occurs due to architectural mismatch occurs .
You can try using the following syntax:
df = spark.read.format(“csv”).option(“header”, “false”).load( “Files/2019.csv")
# Create a new table
df.write.format(“delta”).saveAsTable(“test2”)
If the above syntax doesn't take effect, you may want to consider leaving this message unchecked, as checking it may cause the system to apply more stringent checks to the data being written
Best Regards,
Liu Yang
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
The Power BI Data Visualization World Championships is back! Get ahead of the game and start preparing now!
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