SPRKPY1069

pyspark.sql.DataFrameWriter.parquet

Message: If partitionBy parameter is a list, Snowpark will throw an error.

Category: Warning

Description

When there is a usage of method where it comes to the parameter partitionBy, the tool shows the EWI.

This is because in Snowpark the only supports a ColumnOrSqlExpr as a partitionBy parameter.

Scenarios

Scenario 1

Input code:

For this scenario the partitionBy parameter is not a list.

df = spark.createDataFrame([(25, "Alice", "150"), (30, "Bob", "350")], schema=["age", "name", "value"])

df.write.parquet(file_path, partitionBy="age")

Output code:

The tool adds the EWI SPRKPY1069 to let you know that Snowpark throws an error if parameter is a list.

df = spark.createDataFrame([(25, "Alice", "150"), (30, "Bob", "350")], schema=["age", "name", "value"])

#EWI: SPRKPY1069 => If partitionBy parameter is a list, Snowpark will throw and error.
df.write.parquet(file_path, partition_by = "age", format_type_options = dict(compression = "None"))

Recommended fix

df = spark.createDataFrame([(25, "Alice", "150"), (30, "Bob", "350")], schema=["age", "name", "value"])

stage = f'{Session.get_fully_qualified_current_schema()}.{_generate_prefix("TEMP_STAGE")}'
Session.sql(f'CREATE TEMPORARY STAGE IF NOT EXISTS {stage}').show()
Session.file.put(f"file:///path/to/data/file.parquet", f"@{stage}")

df.write.parquet(stage, partition_by = "age", format_type_options = dict(compression = "None"))

Scenario 2

Input code:

For this scenario the partitionBy parameter is a list.

df = spark.createDataFrame([(25, "Alice", "150"), (30, "Bob", "350")], schema=["age", "name", "value"])

df.write.parquet(file_path, partitionBy=["age", "name"])

Output code:

The tool adds the EWI SPRKPY1069 to let you know that Snowpark throws an error if parameter is a list.

df = spark.createDataFrame([(25, "Alice", "150"), (30, "Bob", "350")], schema=["age", "name", "value"])

#EWI: SPRKPY1069 => If partitionBy parameter is a list, Snowpark will throw and error.
df.write.parquet(file_path, partition_by = ["age", "name"], format_type_options = dict(compression = "None"))

Recommended fix

If the value of the parameter is a list, then replace it with a ColumnOrSqlExpr.

df.write.parquet(file_path, partition_by = sql_expr("age || name"), format_type_options = dict(compression = "None"))

Additional recommendations

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Last updated 7 months ago

df = spark.createDataFrame([(25, "Alice", "150"), (30, "Bob", "350")], schema=["age", "name", "value"]) #EWI: SPRKPY1069 => If partitionBy parameter is a list, Snowpark will throw and error. df.write.parquet(file_path, partition_by = "age", format_type_options = dict(compression = "None"))

df = spark.createDataFrame([(25, "Alice", "150"), (30, "Bob", "350")], schema=["age", "name", "value"]) stage = f'{Session.get_fully_qualified_current_schema()}.{_generate_prefix("TEMP_STAGE")}' Session.sql(f'CREATE TEMPORARY STAGE IF NOT EXISTS {stage}').show() Session.file.put(f"file:///path/to/data/file.parquet", f"@{stage}") df.write.parquet(stage, partition_by = "age", format_type_options = dict(compression = "None"))

df = spark.createDataFrame([(25, "Alice", "150"), (30, "Bob", "350")], schema=["age", "name", "value"]) #EWI: SPRKPY1069 => If partitionBy parameter is a list, Snowpark will throw and error. df.write.parquet(file_path, partition_by = ["age", "name"], format_type_options = dict(compression = "None"))