bodo.pandas.BodoDataFrame.to_parquet

BodoDataFrame.to_parquet(path=None, engine="auto", compression="snappy", index=None, partition_cols=None, storage_options=None, row_group_size=-1, **kwargs)

Write a DataFrame as a Parquet dataset.

Parameters

path: str: Output path to write. It can be a local path (e.g. output.parquet), AWS S3 (s3://...), Azure ALDS (abfs://..., abfss://...), or GCP GCS (gcs://..., gs://).

compression : str, default 'snappy': File compression to use. Can be None, 'snappy', 'gzip', or 'brotli'.

row_group_size : int: Row group size in output Parquet files. -1 allows the backend to choose.

All other parameters will trigger a fallback to pandas.DataFrame.to_parquet.

Example

import bodo.pandas as bd

bdf = bd.DataFrame(
    {
        "A": bd.array([1, 2, 3, 7] * 3, "Int64"),
        "B": ["A1", "B1", "C1", "Abc"] * 3,
        "C": bd.array([6, 5, 4] * 4, "Int64"),
    }
)

bdf.to_parquet("output.parquet")
print(bd.read_parquet("output.parquet"))

Output:

    A    B  C
0   1   A1  6
1   2   B1  5
2   3   C1  4
3   7  Abc  6
4   1   A1  5
5   2   B1  4
6   3   C1  6
7   7  Abc  5
8   1   A1  4
9   2   B1  6
10  3   C1  5
11  7  Abc  4

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