Imbruced commented on code in PR #2490:
URL: https://github.com/apache/sedona/pull/2490#discussion_r2518106081
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spark/common/src/main/scala/org/apache/sedona/stats/Weighting.scala:
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@@ -109,30 +109,42 @@ object Weighting {
val formattedDataFrame = dataframe.withColumn(ID_COLUMN,
sha2(to_json(struct("*")), 256))
- formattedDataFrame
+ val spatiallyJoined = formattedDataFrame
.alias("l")
.join(
formattedDataFrame.alias("r"),
- joinCondition && col(s"l.$ID_COLUMN") =!= col(
- s"r.$ID_COLUMN"
- ), // we will add self back later if self.includeSelf
+ joinCondition && col(s"l.$ID_COLUMN") =!= col(s"r.$ID_COLUMN"),
+ "inner")
+ .select(struct("l.*").alias("left"), struct("r.*").alias("right"))
+
+ val mapped = formattedDataFrame
+ .alias("f")
+ .join(
+ spatiallyJoined.alias("s"),
+ col(s"s.left.$ID_COLUMN") === col(s"f.$ID_COLUMN"),
"left")
.select(
- col(s"l.$ID_COLUMN"),
- struct("l.*").alias("left_contents"),
- struct(
- (
- savedAttributesWithGeom match {
- case null => struct(col("r.*")).dropFields(ID_COLUMN)
- case _ =>
- struct(savedAttributesWithGeom.map(c => col(s"r.$c")): _*)
- }
- ).alias("neighbor"),
- if (!binary)
- pow(distanceFunction(col(s"l.$geometryColumn"),
col(s"r.$geometryColumn")), alpha)
- .alias("value")
- else lit(1.0).alias("value")).alias("weight"))
- .groupBy(s"l.$ID_COLUMN")
+ col(ID_COLUMN),
+ struct("f.*").alias("left_contents"),
+ when(col(ID_COLUMN).isNull, lit(null))
Review Comment:
makes sense, this condition is not needed here
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