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https://issues.apache.org/jira/browse/SPARK-24561?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16717491#comment-16717491
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ASF GitHub Bot commented on SPARK-24561:
----------------------------------------

icexelloss commented on a change in pull request #22305: 
[SPARK-24561][SQL][Python] User-defined window aggregation functions with 
Pandas UDF (bounded window)
URL: https://github.com/apache/spark/pull/22305#discussion_r240686637
 
 

 ##########
 File path: 
sql/core/src/main/scala/org/apache/spark/sql/execution/python/WindowInPandasExec.scala
 ##########
 @@ -27,17 +27,62 @@ import 
org.apache.spark.api.python.{ChainedPythonFunctions, PythonEvalType}
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.catalyst.InternalRow
 import org.apache.spark.sql.catalyst.expressions._
-import org.apache.spark.sql.catalyst.plans.physical._
-import org.apache.spark.sql.execution.{GroupedIterator, SparkPlan, 
UnaryExecNode}
+import org.apache.spark.sql.catalyst.plans.physical.{AllTuples, 
ClusteredDistribution, Distribution, Partitioning}
+import org.apache.spark.sql.execution.{ExternalAppendOnlyUnsafeRowArray, 
SparkPlan}
 import org.apache.spark.sql.execution.arrow.ArrowUtils
-import org.apache.spark.sql.types.{DataType, StructField, StructType}
+import org.apache.spark.sql.execution.window._
+import org.apache.spark.sql.types._
 import org.apache.spark.util.Utils
 
+/**
+ * This class calculates and outputs windowed aggregates over the rows in a 
single partition.
+ *
+ * This is similar to [[WindowExec]]. The main difference is that this node 
doesn't not compute
+ * any window aggregation values. Instead, it computes the lower and upper 
bound for each window
+ * (i.e. window bounds) and pass the data and indices to python work to do the 
actual window
 
 Review comment:
   Fixed

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> User-defined window functions with pandas udf (bounded window)
> --------------------------------------------------------------
>
>                 Key: SPARK-24561
>                 URL: https://issues.apache.org/jira/browse/SPARK-24561
>             Project: Spark
>          Issue Type: Sub-task
>          Components: PySpark
>    Affects Versions: 2.3.1
>            Reporter: Li Jin
>            Priority: Major
>




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