[jira] [Created] (SPARK-27691) Issue when running queries using filter predicates on pandas GROUPED_AGG udfs

["Michael Tong (JIRA)" <ji...@apache.org>]

Michael Tong created SPARK-27691:
------------------------------------

             Summary: Issue when running queries using filter predicates on pandas GROUPED_AGG udfs
                 Key: SPARK-27691
                 URL: https://issues.apache.org/jira/browse/SPARK-27691
             Project: Spark
          Issue Type: Bug
          Components: Input/Output
    Affects Versions: 2.4.2
            Reporter: Michael Tong


Am currently running pyspark 2.4.2 and I am currently unable to run the following code.

 
{code:java}
from pyspark.sql import functions, types
import pandas as pd
import random

# initialize test data
test_data = [[False, int(random.random() * 2)] for i in range(10000)]
test_data = pd.DataFrame(test_data, columns=['bool_value', 'int_value'])

# pandas udf
pandas_any_udf = functions.pandas_udf(lambda x: x.any(), types.BooleanType(), functions.PandasUDFType.GROUPED_AGG)

# create spark DataFrame and build the query
test_df = spark.createDataFrame(test_data)
test_df = test_df.groupby('int_value').agg(pandas_any_udf('bool_value').alias('bool_any_result'))
test_df = test_df.filter(functions.col('bool_any_result') == True)

# write to output
test_df.write.parquet('/tmp/mtong/write_test', mode='overwrite')
{code}
 

Below is a truncated error message.

 
{code:java}
Py4JJavaError: An error occurred while calling o1125.parquet. : org.apache.spark.SparkException: Job aborted.

...

Exchange hashpartitioning(int_value#123L, 2000)
+- *(1) Filter (<lambda>(bool_value#122) = true)
   +- Scan ExistingRDD arrow[bool_value#122,int_value#123L]

...

Caused by: java.lang.UnsupportedOperationException: Cannot evaluate expression: <lambda>(input[0, boolean, true]){code}
 

 

What appears to be happening is that the query optimizer incorrectly pushes up the filter predicate on bool_any_result before the group by operation. This causes the query to error out before spark attempts to execute the query. I have also tried running a variant of this query with functions.count() as the aggregation function and the query ran fine, so I believe that this is an error that only affects pandas udfs.

 

Variant of query with standard aggregation function
{code:java}
test_df = spark.createDataFrame(test_data)
test_df = test_df.groupby('int_value').agg(functions.count('bool_value').alias('bool_counts'))
test_df = test_df.filter(functions.col('bool_counts') > 0)
{code}
 

 

 



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org