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Databricks/Spark data write to SQL DW is dropping the table and recreating it
The Next CEO of Stack Overflowspark - scala - save dataframe to a table with overwrite modeSpark Dataframe / SQL - Complex enriching nested dataconnection from databricks to snowflakeSpark - Mixed case sensitivity in Spark DataFrame, Spark SQL, and/or Databricks TableDetecting CSV Headers when creating a DataBricks Delta Table?Spark/Databricks data write issue with Cosmos DB with Mongo DB APIDelete azure sql database rows from azure databricksAuthorization error with spark-sftp connector on DatabricksHow do explicit table partitions in Databricks affect write performance?
In Azure SQL DW ,I have an empty table (say table T1) .
Suppose T1 has 4 columns C1,C2,C3 and C4 (C4 is not null)
I have a dataframe in Databricks (say df1) which has data for C1,C2 and C3
I am performing the write operation on the dataframe using code snippet like the following
df1.write
.format("com.databricks.spark.sqldw")
.option("url", jdbcURL)
.option("dbtable", "T1")
.option( "forward_spark_azure_storage_credentials","True")
.option("tempDir", tempDir)
.mode("overwrite")
.save()
What I see there is that instead of getting any error ,the table T1 gets lost and new table T1 gets created with only 3 columns C1,C2 and C3.
Is that an expected behavior or ideally while trying to insert data , some exceptions should have been thrown as data corresponding to C4 was missing ?
apache-spark apache-spark-sql databricks azure-sqldw azure-databricks
asked Mar 8 at 19:03
AyanAyan
986
add a comment |
In Azure SQL DW ,I have an empty table (say table T1) .
Suppose T1 has 4 columns C1,C2,C3 and C4 (C4 is not null)
I have a dataframe in Databricks (say df1) which has data for C1,C2 and C3
I am performing the write operation on the dataframe using code snippet like the following
df1.write
.format("com.databricks.spark.sqldw")
.option("url", jdbcURL)
.option("dbtable", "T1")
.option( "forward_spark_azure_storage_credentials","True")
.option("tempDir", tempDir)
.mode("overwrite")
.save()
What I see there is that instead of getting any error ,the table T1 gets lost and new table T1 gets created with only 3 columns C1,C2 and C3.
Is that an expected behavior or ideally while trying to insert data , some exceptions should have been thrown as data corresponding to C4 was missing ?
apache-spark apache-spark-sql databricks azure-sqldw azure-databricks
asked Mar 8 at 19:03
AyanAyan
986
add a comment |
In Azure SQL DW ,I have an empty table (say table T1) .
Suppose T1 has 4 columns C1,C2,C3 and C4 (C4 is not null)
I have a dataframe in Databricks (say df1) which has data for C1,C2 and C3
I am performing the write operation on the dataframe using code snippet like the following
df1.write
.format("com.databricks.spark.sqldw")
.option("url", jdbcURL)
.option("dbtable", "T1")
.option( "forward_spark_azure_storage_credentials","True")
.option("tempDir", tempDir)
.mode("overwrite")
.save()
What I see there is that instead of getting any error ,the table T1 gets lost and new table T1 gets created with only 3 columns C1,C2 and C3.
Is that an expected behavior or ideally while trying to insert data , some exceptions should have been thrown as data corresponding to C4 was missing ?
apache-spark apache-spark-sql databricks azure-sqldw azure-databricks
asked Mar 8 at 19:03
AyanAyan
986
In Azure SQL DW ,I have an empty table (say table T1) .
Suppose T1 has 4 columns C1,C2,C3 and C4 (C4 is not null)
I have a dataframe in Databricks (say df1) which has data for C1,C2 and C3
I am performing the write operation on the dataframe using code snippet like the following
df1.write
.format("com.databricks.spark.sqldw")
.option("url", jdbcURL)
.option("dbtable", "T1")
.option( "forward_spark_azure_storage_credentials","True")
.option("tempDir", tempDir)
.mode("overwrite")
.save()
What I see there is that instead of getting any error ,the table T1 gets lost and new table T1 gets created with only 3 columns C1,C2 and C3.
Is that an expected behavior or ideally while trying to insert data , some exceptions should have been thrown as data corresponding to C4 was missing ?
apache-spark apache-spark-sql databricks azure-sqldw azure-databricks
apache-spark apache-spark-sql databricks azure-sqldw azure-databricks
asked Mar 8 at 19:03
AyanAyan
986
asked Mar 8 at 19:03
AyanAyan
986
asked Mar 8 at 19:03
AyanAyan
986
asked Mar 8 at 19:03
AyanAyan
986
asked Mar 8 at 19:03
AyanAyan
986
986
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
You’ve set the mode to overwrite — dropping and recreating the table in question is my experience there too. Maybe try append instead?
answered Mar 8 at 20:40
Stephen DarlingtonStephen Darlington
46.1k995143
add a comment |
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1 Answer
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1 Answer
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oldest
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votes
You’ve set the mode to overwrite — dropping and recreating the table in question is my experience there too. Maybe try append instead?
answered Mar 8 at 20:40
Stephen DarlingtonStephen Darlington
46.1k995143
add a comment |
You’ve set the mode to overwrite — dropping and recreating the table in question is my experience there too. Maybe try append instead?
answered Mar 8 at 20:40
Stephen DarlingtonStephen Darlington
46.1k995143
add a comment |
You’ve set the mode to overwrite — dropping and recreating the table in question is my experience there too. Maybe try append instead?
answered Mar 8 at 20:40
Stephen DarlingtonStephen Darlington
46.1k995143
You’ve set the mode to overwrite — dropping and recreating the table in question is my experience there too. Maybe try append instead?
answered Mar 8 at 20:40
Stephen DarlingtonStephen Darlington
46.1k995143
answered Mar 8 at 20:40
Stephen DarlingtonStephen Darlington
46.1k995143
answered Mar 8 at 20:40
Stephen DarlingtonStephen Darlington
46.1k995143
answered Mar 8 at 20:40
Stephen DarlingtonStephen Darlington
46.1k995143
46.1k995143
add a comment |
add a comment |
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