devin-petersohn opened a new pull request, #53391:
URL: https://github.com/apache/spark/pull/53391
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### What changes were proposed in this pull request?
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Add support for Pycapsule and `__dataframe__` protocols for interchange
between Spark and other Python libraries. Here is a demo of what this enables
with Polars and DuckDB:
```
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/__ / .__/\_,_/_/ /_/\_\ version 4.2.0-SNAPSHOT
/_/
Using Python version 3.11.5 (main, Sep 11 2023 08:31:25)
Spark context Web UI available at http://192.168.86.83:4040
Spark context available as 'sc' (master = local[*], app id =
local-1765227291836).
SparkSession available as 'spark'.
In [1]: import pyspark.pandas as ps
...: import pandas as pd
...: import numpy as np
...: import polars as pl
...:
...: pdf = pd.DataFrame(
...: {"A": [True, False], "B": [1, np.nan], "C": [True, None], "D":
[None, np.nan]}
...: )
...: psdf = ps.from_pandas(pdf)
...: polars_df = pl.DataFrame(psdf)
/Users/dpetersohn/software_sources/spark/python/pyspark/pandas/__init__.py:43:
UserWarning: 'PYARROW_IGNORE_TIMEZONE' environment variable was not set. It is
required to set this environment variable to '1' in both driver and executor
sides if you use pyarrow>=2.0.0. pandas-on-Spark will set it for you but it
does not work if there is a Spark context already launched.
warnings.warn(
[Stage 0:> (0 + 1)
/ 1]
In [2]: polars_df
Out[2]:
shape: (2, 5)
┌───────────────────┬───────┬──────┬──────┬──────┐
│ __index_level_0__ ┆ A ┆ B ┆ C ┆ D │
│ --- ┆ --- ┆ --- ┆ --- ┆ --- │
│ i64 ┆ bool ┆ f64 ┆ bool ┆ f64 │
╞═══════════════════╪═══════╪══════╪══════╪══════╡
│ 0 ┆ true ┆ 1.0 ┆ true ┆ null │
│ 1 ┆ false ┆ null ┆ null ┆ null │
└───────────────────┴───────┴──────┴──────┴──────┘
In [3]: import duckdb
In [4]: import pyarrow as pa
In [5]: stream = pa.RecordBatchReader.from_stream(psdf)
In [6]: duckdb.sql("SELECT count(*) AS total, avg(B) FROM stream WHERE B IS
NOT NULL").fetchall()
Out[6]: [(1, 1.0)]
```
Polars will now be able to consume a full Pyspark dataframe (or
`pyspark.pandas`), and DuckDB can consume a stream built from the Pyspark
dataframe. Importantly, the `stream = pa.RecordBatchReader.from_stream(psdf)`
line does not trigger any computation, it simply creates a stream object which
is incrementally consumed by DuckDB when the `fetchall` call is executed.
### Why are the changes needed?
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Currently, Pyspark (and to a lesser degree Pyspark pandas) does not
integrate well with the broader Python ecosystem. Currently, the best practice
is to go through pandas with `toPandas`, but that materializes all data on the
driver all at once. This new API and protocol allows data to stream, one Arrow
Batch at a time, enabling libraries like DuckDB and Polars to consume the data
as a stream.
### Does this PR introduce _any_ user-facing change?
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Note that it means *any* user-facing change including all aspects such as
new features, bug fixes, or other behavior changes. Documentation-only updates
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Yes, new user-level API.
### How was this patch tested?
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Locally
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No
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