[
https://issues.apache.org/jira/browse/SPARK-60645?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
asddfl updated SPARK-60645:
---------------------------
Description:
Constructing a pandas-on-Spark Series from an existing Series and explicitly
supplying that Series' own DataFrame index raises a ValueError about the truth
value of an Index. The equivalent Pandas constructor succeeds.
{code:python}
import pandas as pd
from pyspark.sql import SparkSession
import pyspark.pandas as ps
t0 = pd.DataFrame({'c0': [1]})
print("Pandas:", flush=True)
result = pd.Series(t0['c0'], index=t0.index)
print(result, flush=True)
spark = (
SparkSession.builder
.master("local[2]")
.config("spark.sql.ansi.enabled", "false")
.config("spark.sql.shuffle.partitions", "2")
.getOrCreate()
)
t0 = ps.DataFrame({'c0': [1]})
print("PySpark Pandas:", flush=True)
result = ps.Series(t0['c0'], index=t0.index)
print(result, flush=True)
spark.stop()
{code}
{code:bash}
Pandas:
0 1
Name: c0, dtype: int64
PySpark Pandas:
Traceback (most recent call last):
File "/test.py", line 24, in <module>
result = ps.Series(t0['c0'], index=t0.index)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/conda/envs/lib/python3.11/site-packages/pyspark/pandas/series.py",
line 445, in __init__
if index:
File
"/opt/conda/envs/lib/python3.11/site-packages/pyspark/pandas/indexes/base.py",
line 2648, in __bool__
raise ValueError(
ValueError: The truth value of a Index is ambiguous. Use a.empty, a.bool(),
a.item(), a.any() or a.all().
{code}
*Expected behavior*
Return a Series named c0 containing the integer value 1 at index 0. The Index
argument should be handled without evaluating its truth value.
*Actual behavior*
ps.Series(t0['c0'], index=t0.index) raises ValueError: The truth value of a
Index is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
was:
Constructing a pandas-on-Spark Series from an existing Series and explicitly
supplying that Series' own DataFrame index raises a ValueError about the truth
value of an Index. The equivalent Pandas constructor succeeds.
{code:python}
# Minimized from err_bug6.py: The Series constructor incorrectly evaluates the
distributed Index as a boolean.
import pandas as pd
from pyspark.sql import SparkSession
import pyspark.pandas as ps
t0 = pd.DataFrame({'c0': [1]})
print("Pandas:", flush=True)
result = pd.Series(t0['c0'], index=t0.index)
print(result, flush=True)
spark = (
SparkSession.builder
.master("local[2]")
.config("spark.sql.ansi.enabled", "false")
.config("spark.sql.shuffle.partitions", "2")
.getOrCreate()
)
t0 = ps.DataFrame({'c0': [1]})
print("PySpark Pandas:", flush=True)
result = ps.Series(t0['c0'], index=t0.index)
print(result, flush=True)
spark.stop()
{code}
{code:bash}
Pandas:
0 1
Name: c0, dtype: int64
PySpark Pandas:
Traceback (most recent call last):
File "/test.py", line 24, in <module>
result = ps.Series(t0['c0'], index=t0.index)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/conda/envs/lib/python3.11/site-packages/pyspark/pandas/series.py",
line 445, in __init__
if index:
File
"/opt/conda/envs/lib/python3.11/site-packages/pyspark/pandas/indexes/base.py",
line 2648, in __bool__
raise ValueError(
ValueError: The truth value of a Index is ambiguous. Use a.empty, a.bool(),
a.item(), a.any() or a.all().
{code}
*Expected behavior*
Return a Series named c0 containing the integer value 1 at index 0. The Index
argument should be handled without evaluating its truth value.
*Actual behavior*
ps.Series(t0['c0'], index=t0.index) raises ValueError: The truth value of a
Index is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
> pandas-on-Spark Series constructor evaluates its Index argument as a boolean
> ----------------------------------------------------------------------------
>
> Key: SPARK-60645
> URL: https://issues.apache.org/jira/browse/SPARK-60645
> 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
>
> Constructing a pandas-on-Spark Series from an existing Series and explicitly
> supplying that Series' own DataFrame index raises a ValueError about the
> truth value of an Index. The equivalent Pandas constructor succeeds.
> {code:python}
> import pandas as pd
> from pyspark.sql import SparkSession
> import pyspark.pandas as ps
> t0 = pd.DataFrame({'c0': [1]})
> print("Pandas:", flush=True)
> result = pd.Series(t0['c0'], index=t0.index)
> print(result, flush=True)
> spark = (
> SparkSession.builder
> .master("local[2]")
> .config("spark.sql.ansi.enabled", "false")
> .config("spark.sql.shuffle.partitions", "2")
> .getOrCreate()
> )
> t0 = ps.DataFrame({'c0': [1]})
> print("PySpark Pandas:", flush=True)
> result = ps.Series(t0['c0'], index=t0.index)
> print(result, flush=True)
> spark.stop()
> {code}
> {code:bash}
> Pandas:
> 0 1
> Name: c0, dtype: int64
> PySpark Pandas:
> Traceback (most recent call last):
> File "/test.py", line 24, in <module>
> result = ps.Series(t0['c0'], index=t0.index)
> ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
> File
> "/opt/conda/envs/lib/python3.11/site-packages/pyspark/pandas/series.py", line
> 445, in __init__
> if index:
> File
> "/opt/conda/envs/lib/python3.11/site-packages/pyspark/pandas/indexes/base.py",
> line 2648, in __bool__
> raise ValueError(
> ValueError: The truth value of a Index is ambiguous. Use a.empty, a.bool(),
> a.item(), a.any() or a.all().
> {code}
> *Expected behavior*
> Return a Series named c0 containing the integer value 1 at index 0. The Index
> argument should be handled without evaluating its truth value.
> *Actual behavior*
> ps.Series(t0['c0'], index=t0.index) raises ValueError: The truth value of a
> Index is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
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