-
-
Save hammedb197/47c8caa63bf6feb77757dd70d9875905 to your computer and use it in GitHub Desktop.
PySpark faster toPandas using mapPartitions
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| import pandas as pd | |
| def _map_to_pandas(rdds): | |
| """ Needs to be here due to pickling issues """ | |
| return [pd.DataFrame(list(rdds))] | |
| def toPandas(df, n_partitions=None): | |
| """ | |
| Returns the contents of `df` as a local `pandas.DataFrame` in a speedy fashion. The DataFrame is | |
| repartitioned if `n_partitions` is passed. | |
| :param df: pyspark.sql.DataFrame | |
| :param n_partitions: int or None | |
| :return: pandas.DataFrame | |
| """ | |
| if n_partitions is not None: df = df.repartition(n_partitions) | |
| df_pand = df.rdd.mapPartitions(_map_to_pandas).collect() | |
| df_pand = pd.concat(df_pand) | |
| df_pand.columns = df.columns | |
| return df_pand |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment