Github user chiwanpark commented on the pull request:
https://github.com/apache/flink/pull/1220#issuecomment-153096308
I would suggest logic like following:
```scala
val useQuadTree = ~~~
if (useQuadTree) {
knnQueryWithQuadTree(training, testing, out)
} else {
knnQueryBasic(training, testing, out)
}
```
Or to reduce duplicated code in L257-L266, we can use following:
```scala
val useQuadTree = ~~~
val quadTree: Option[QuadTree] = if (useQuadTree) {
Some(buildQuadTree(training, testing))
} else {
None
}
for (a <- testing.values) {
val trainingFiltered: Seq[Vector] = quadTree match {
case Some(tree) => getSibilingsFromQuadTree(a, tree)
case None => training.values
}
for (b <- trainingFiltered) {
// (training vector, input vector, input key, distance)
queue.enqueue((b, a._2, a._1, metric.distance(b, a._2)))
if (queue.size > k) {
queue.dequeue()
}
}
for (v <- queue) {
out.collect(v)
}
}
```
In this case, we create methods about quadtree operation.
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