I'm trying to write a pyspark df to Snowflake using a function I've written:
def s3_to_snowflake(schema, table):
df = get_dataframe(schema, table, sqlContext)
username = user
password = passw
account = acct
snowflake_options = {
"sfURL" : account+".us-east-1.snowflakecomputing.com",
"sfAccount" : account,
"sfUser" : username,
"sfPassword" : password,
"sfDatabase" : "database",
"sfSchema" : schema,
"sfWarehouse" : "demo_wh"
}
sc._jsc.hadoopConfiguration().set("fs.s3.awsAccessKeyId", "KeyId")
sc._jsc.hadoopConfiguration().set("fs.s3.awsSecretAccessKey",
"AccessKey")
(
df
.write
.format("net.snowflake.spark.snowflake")
.mode("overwrite")
.options(**snowflake_options)
.option("dbtable", table)
.option('tempDir', 's3://data-temp-loads/snowflake')
.save()
)
print('Wrote {0} to {1}.'.format(table, schema))
This function has worked for all but one of the tables I've got in my datalake. This is the schema of the table I'm trying to write.
root
|-- credit_transaction_id: string (nullable = true)
|-- credit_deduction_amt: double (nullable = true)
|-- credit_adjustment_time: timestamp (nullable = true)
The error I'm getting looks like Snowflake is taking issue with that DoubleType column. I've had this issue before with Hive when using Avro/ORC filetypes. Usually it's a matter of casting one datatype to another.
Things I've tried:
- Casting (Double to Float, Double to String, Double to Numeric–this last one per the Snowflake docs )
- Rerunning DDL of the incoming table, trying Float, String, and Numeric types
One other thing of note: some of the tables that I've transferred successfully have columns of DoubleType. Unsure of what the issue with this table is.