SPRKPY1089

pyspark.sql.readwriter.DataFrameWriter.options

Message: The pyspark.sql.readwriter.DataFrameWriter.options values in Snowpark may be different, so required validation might be needed.

Category: Warning

Description

The pyspark.sql.readwriter.DataFrameWriter.options values in Snowpark may be different, so validation might be needed to ensure that the behavior is correct.

Scenarios

There are some scenarios, depending on whether the options are supported or not, or the format used to write the file.

Scenario 1

Input

Below is an example of the usage of the method options, adding the options sep and nullValue, which are currently supported.

df = spark.createDataFrame([(1, "myVal")], [2, "myVal2"], [None, "myVal3" ])

df.write.options(nullValue="myVal", sep=",").csv("some_path")

Output

The tool adds the EWI SPRKPY1089 indicating that it is required validation.

df = spark.createDataFrame([(1, "myVal")], [2, "myVal2"], [None, "myVal3" ])
#EWI: SPRKPY1089 => The pyspark.sql.readwriter.DataFrameWriter.options values in Snowpark may be different, so required validation might be needed.
df.write.options(nullValue="myVal", sep=",").csv("some_path")

Recommended fix

The Snowpark API supports these parameters, so the only action can be to check the behavior after the migration. Please refer to the Equivalences table to see the supported parameters.

df = spark.createDataFrame([(1, "myVal")], [2, "myVal2"], [None, "myVal3" ])
#EWI: SPRKPY1089 => The pyspark.sql.readwriter.DataFrameWriter.options values in Snowpark may be different, so required validation might be needed.
df.write.options(nullValue="myVal", sep=",").csv("some_path")

Scenario 2

Input

Here the scenario shows the usage of options, but adds a header option, which is not supported.

df = spark.createDataFrame([(1, "myVal")], [2, "myVal2"], [None, "myVal3" ])

df.write.options(header=True, sep=",").csv("some_path")

Output

The tool adds the EWI SPRKPY1089 indicating that it is required validation is needed.

df = spark.createDataFrame([(1, "myVal")], [2, "myVal2"], [None, "myVal3" ])
#EWI: SPRKPY1089 => The pyspark.sql.readwriter.DataFrameWriter.options values in Snowpark may be different, so required validation might be needed.
df.write.options(header=True, sep=",").csv("some_path")

Recommended fix

For this scenario it is recommended to evaluate the Snowpark format type options to see if it is possible to change it according to your needs. Also, check the behavior after the change.

df = spark.createDataFrame([(1, "myVal")], [2, "myVal2"], [None, "myVal3" ])
#EWI: SPRKPY1089 => The pyspark.sql.readwriter.DataFrameWriter.options values in Snowpark may be different, so required validation might be needed.
df.write.csv("some_path")

Scenario 3

Input

This scenario adds a sep option, which is supported and uses the JSON method.

df = spark.createDataFrame([(1, "myVal")], [2, "myVal2"], [None, "myVal3" ])

df.write.options(nullValue="myVal", sep=",").json("some_path")

Output

The tool adds the EWI SPRKPY1089 indicating that it is required validation is needed.

• Note: this scenario also applies for PARQUET.

df = spark.createDataFrame([(1, "myVal")], [2, "myVal2"], [None, "myVal3" ])
#EWI: SPRKPY1089 => The pyspark.sql.readwriter.DataFrameWriter.options values in Snowpark may be different, so required validation might be needed.
df.write.options(nullValue="myVal", sep=",").json("some_path")

Recommended fix

The file format JSON does not support the parameter sep, so it is recommended to evaluate the snowpark format type options to see if it is possible to change it according to your needs. Also, check the behavior after the change.

df = spark.createDataFrame([(1, "myVal")], [2, "myVal2"], [None, "myVal3" ])
#EWI: SPRKPY1089 => The pyspark.sql.readwriter.DataFrameWriter.options values in Snowpark may be different, so required validation might be needed.
df.write.json("some_path")

Additional recommendations

• Since there are some not supported parameters, it is recommended to check the table of equivalences and check the behavior after the transformation.

• Equivalences table:

Snowpark can support a list of equivalences for some parameters:

PySpark Option	SnowFlake Option	Supported File Formats	Description
SEP	FIELD_DELIMITER	CSV	One or more single byte or multibyte characters that separate fields in an input file.
LINESEP	RECORD_DELIMITER	CSV	One or more characters that separate records in an input file.
QUOTE	FIELD_OPTIONALLY_ENCLOSED_BY	CSV	Character used to enclose strings.
NULLVALUE	NULL_IF	CSV	String used to convert to and from SQL NULL.
DATEFORMAT	DATE_FORMAT	CSV	String that defines the format of date values in the data files to be loaded.
TIMESTAMPFORMAT	TIMESTAMP_FORMAT	CSV	String that defines the format of timestamp values in the data files to be loaded.

If the parameter used is not in the list, the API throws an error.

• For more support, you can email us at [e-mail] or post an issue in the SMA.