Pandas cannot read parquet files created in PySpark

Question

I am writing a parquet file from a Spark DataFrame the following way:

df.write.parquet(\"path/myfile.parquet\", mode = \"overwrite\", compression=\"gzip\")
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Answer 1

Since this still seems to be an issue even with newer pandas versions, I wrote some functions to circumvent this as part of a larger pyspark helpers library:

import pandas as pd
import datetime

def read_parquet_folder_as_pandas(path, verbosity=1):
  files = [f for f in os.listdir(path) if f.endswith("parquet")]

  if verbosity > 0:
    print("{} parquet files found. Beginning reading...".format(len(files)), end="")
    start = datetime.datetime.now()

  df_list = [pd.read_parquet(os.path.join(path, f)) for f in files]
  df = pd.concat(df_list, ignore_index=True)

  if verbosity > 0:
    end = datetime.datetime.now()
    print(" Finished. Took {}".format(end-start))
  return df


def read_parquet_as_pandas(path, verbosity=1):
  """Workaround for pandas not being able to read folder-style parquet files.
  """
  if os.path.isdir(path):
    if verbosity>1: print("Parquet file is actually folder.")
    return read_parquet_folder_as_pandas(path, verbosity)
  else:
    return pd.read_parquet(path)

This assumes that the relevant files in the parquet "file", which is actually a folder, end with ".parquet". This works for parquet files exported by databricks and might work with others as well (untested, happy about feedback in the comments).

The function read_parquet_as_pandas() can be used if it is not known beforehand whether it is a folder or not.