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https://issues.apache.org/jira/browse/SPARK-24561?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16716606#comment-16716606
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ASF GitHub Bot commented on SPARK-24561:
----------------------------------------
HyukjinKwon 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_r240523454
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/python/WindowInPandasExec.scala
##########
@@ -60,6 +105,26 @@ case class WindowInPandasExec(
override def outputPartitioning: Partitioning = child.outputPartitioning
+ /**
+ * Helper functions and data structures for window bounds
+ *
+ * It contains:
+ * (1) Total number of window bound indices in the python input row
+ * (2) Function from frame index to its lower bound column index in the
python input row
+ * (3) Function from frame index to its upper bound column index in the
python input row
+ * (4) Seq from frame index to its window bound type
+ */
+ private type WindowBoundHelpers = (Int, Int => Int, Int => Int,
Seq[WindowType])
+
+ /**
+ * Enum for window bound types. Used only inside this class.
+ */
+ private sealed case class WindowType(value: String)
+ private object UnboundedWindow extends WindowType("unbounded")
+ private object BoundedWindow extends WindowType("bounded")
+
+ private val window_bound_type_conf = "pandas_window_bound_types"
Review comment:
nit: `window_bound_type_conf` -> `windowBoundTypeConf`
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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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