vish02/22/2021, 3:17 PM
to convert the output of a task from a pandas DataFrame to a partitioned Parquet dataset, before uploading to GCS. It worked well when serializing to a single parquet file (without partitions). However, when using partitions, the Serializer fails. From my initial look into the source code, it revealed that the Results class expects a binary stream from the serializer. However, _`pandas.to_parquet(*, partition_cols=["col1"])`_ does not return a binary output as it results in multiple parquet files being created. Example code
From my assessment this looks like this pattern (ie. serializer to multiple files) is not supported right now? If that is the case, what are your thoughts on the "prefect-way" to achieve the above.
pandas_serializer = PandasSerializer( file_type="parquet", serialize_kwargs=dict( engine="pyarrow", partition_cols=["date"] ), ) gcs_result = GCSResult( bucket="bucket-name", serializer=pandas_serializer ) class Extract(Task): def __init__(self, **kwargs): super().__init__(**kwargs, result=gcs_result, target="target_file_location") def run(self, df: pd.DataFrame) -> pd.DataFrame: # Some processing steps return df
vish02/23/2021, 12:37 AM