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https://issues.apache.org/jira/browse/SPARK-60658?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
ASF GitHub Bot updated SPARK-60658:
-----------------------------------
Labels: pull-request-available (was: )
> pandas-on-Spark np.floor converts negative infinity to the minimum int64 value
> ------------------------------------------------------------------------------
>
> Key: SPARK-60658
> URL: https://issues.apache.org/jira/browse/SPARK-60658
> Project: Spark
> Issue Type: Bug
> Components: Pandas API on Spark, PySpark
> Affects Versions: 4.2.0
> Environment: Platform: Ubuntu 24.04 Linux-6.17.0-29-generic x86_64
> Python: 3.11.17
> pyspark 4.2.0
> findspark 2.0.1
> pandas 3.0.6
> numpy 2.4.6
> Reporter: asddfl
> Priority: Critical
> Labels: pull-request-available
>
> When using the pandas API on Spark (pyspark.pandas), np.floor on a float64
> Series containing negative infinity returns -9223372036854775808 with dtype
> int64. Pandas/NumPy preserves negative infinity and returns dtype float64.
> A single float64 input with explicit negative infinity isolates the floor
> operation. Both queries complete successfully, but the value and result dtype
> differ.
> {code:python}
> import pandas as pd
> import numpy as np
> from pyspark.sql import SparkSession
> import pyspark.pandas as ps
> t0 = pd.DataFrame({'c0': [float('-inf')]})
> print("Pandas:", flush=True)
> result = np.floor(t0['c0'])
> print(result, flush=True)
> spark = (
> SparkSession.builder
> .master("local[2]")
> .config("spark.sql.ansi.enabled", "false")
> .config("spark.sql.shuffle.partitions", "2")
> .getOrCreate()
> )
> ps.set_option("compute.ops_on_diff_frames", True)
> t0 = ps.DataFrame({'c0': [float('-inf')]})
> print("PySpark Pandas:", flush=True)
> result = np.floor(t0['c0'])
> print(result, flush=True)
> spark.stop()
> {code}
> {code:bash}
> Pandas:
> 0 -inf
> Name: c0, dtype: float64
> PySpark Pandas:
> 0 -9223372036854775808
> Name: c0, dtype: int64
> {code}
> *Expected behavior*
> np.floor(float('-inf')) should preserve negative infinity and produce a
> float64 result, matching Pandas/NumPy.
> *Actual behavior*
> Pandas returns -inf with dtype float64. pandas-on-Spark returns
> -9223372036854775808, the minimum signed 64-bit integer, with dtype int64.
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