CODEWITHSUNDEEP
pythonpandasparquetpyarrowfastparquet
Asad Khalil
Asad Khalil

Reputation: 45

Writing Pandas DataFrame to Parquet file?

I am reading data in chunks using pandas.read_sql and appending to parquet file but get errors

Using pyarrow.parquet:

import pyarrow as pa
import pyarrow.parquet as pq
for chunk in pd.read_sql_query(query , conn, chunksize=10000):
    table_data = pa.Table.from_pandas(chunk)  #converting df to arrow
    pq.write_table(table=table_data,where=file.paraquet,
                   use_deprecated_int96_timestamps=True,
                   coerce_timestamps='ms',allow_truncated_timestamps=True)

Getting the following error:

  File "pyarrow\_parquet.pyx", line 1427, in pyarrow._parquet.ParquetWriter.__cinit__
  File "pyarrow\error.pxi", line 120, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Unhandled type for Arrow to Parquet schema conversion: duration[ns]

using fast parquet:

from fastparquet import write
for chunk in pd.read_sql_query(query , conn, chunksize=10000):
    with open(os.path.join(download_location, file_name+ '.parquet'),mode="a+") as f:
        write(filename=f.name,data=chunk,append=True)

Getting following error:

    raise ValueError("Can't infer object conversion type: %s" % head)
ValueError: Can't infer object conversion type: 0    2021-09-06

Is there any solution which converts pandas dataframe to parquet file (append mode) without datetime columns issue?

Upvotes: 0

Views: 3929

Answers (1)

Asad Khalil
Asad Khalil

Reputation: 45

The solution is to convert the pandas dataframe chunk into str and write to parquet file

        query = f'select * from `{table["table_name"]}`'

        for i,chunk in enumerate(pd.read_sql_query(query , conn, chunksize=10000)):

            all_columns = list(chunk) # Creates list of all column headers
            chunk[all_columns] = chunk[all_columns].astype(str) 
            #convert data to string

            table_schema =chunk.dtypes.astype(str).to_dict()
            
            for k,v in table_schema.items():                
                if v == 'object':
                    table_schema[k]=pa.string()
            #create pyarrow schema for string format
            fields = [pa.field(x, y) for x, y in table_schema.items()]
            new_schema = pa.schema(fields)
            
            if i == 0:  
                pqwriter = pq.ParquetWriter(where=updated_path,schema=new_schema, compression='snappy')
                
            table = pa.Table.from_pandas(df=chunk, schema=new_schema,preserve_index=False,safe=False)
            pqwriter.write_table(table)

Upvotes: 0

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