[jira] [Created] (SPARK-29990) Pandas UDF including numpy sort operation not working with multi-dimensional array column

["Dean Wyatte (Jira)" <ji...@apache.org>]

Dean Wyatte created SPARK-29990:
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             Summary: Pandas UDF including numpy sort operation not working with multi-dimensional array column
                 Key: SPARK-29990
                 URL: https://issues.apache.org/jira/browse/SPARK-29990
             Project: Spark
          Issue Type: Bug
          Components: PySpark
    Affects Versions: 2.4.3
            Reporter: Dean Wyatte


 

If I have a multi-dimensional array column in a Spark DataFrame (e.g., ArrayType(ArrayType(LongType())) ), I am unable to apply a Pandas UDF that uses a numpy sort operation. The function works fine on the native Pandas Series, but errors with a numpy error when called as a UDF with "ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()"

 

Minimal code to reproduce:
{code:java}
import random
import numpy as np
import pandas as pd
from pyspark.sql import SparkSession
from pyspark.sql.types import ArrayType, LongType
from pyspark.sql.functions import pandas_udf

def ndsort(s):
    return pd.Series([x for x in np.sort(s.values.tolist(), axis=1)])

X = [random.sample([[i, 400000+i] for i in range(10)], 10) for j in range(100)]
pdf = pd.DataFrame([[x] for x in X], columns=['x'])

spark = SparkSession.builder.appName('test').getOrCreate()
sdf = spark.createDataFrame(pdf)
ndsort_udf = pandas_udf(ndsort, ArrayType(ArrayType(LongType())))

ndsort(pdf['x'])  # works
sdf.withColumn('y', ndsort_udf('x')).show()  # errors{code}
 

 

UDFs that use a numpy sort operation work fine if the column is only ArrayType(LongType()):

 
{code:java}
X = [random.sample([400000+i for i in range(10)], 10) for j in range(100)]
pdf = pd.DataFrame([[x] for x in X], columns=['x'])

sdf = spark.createDataFrame(pdf)
ndsort_udf = pandas_udf(ndsort, ArrayType(LongType()))

ndsort(pdf['x'])  # works
sdf.withColumn('y', ndsort_udf('x')).show()  # also works
{code}
 



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