Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/3462#discussion_r20970806
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
---
@@ -261,6 +261,57 @@ object Vectors {
sys.error("Unsupported Breeze vector type: " + v.getClass.getName)
}
}
+
+ /**
+ * Returns the p-norm of this vector.
+ * @param vector input vector.
+ * @param p norm.
+ * @return norm in L^p^ space.
+ */
+ private[spark] def norm(vector: Vector, p: Double): Double = {
+ require(p >= 1.0)
+ val values = vector match {
+ case dv: DenseVector => dv.values
+ case sv: SparseVector => sv.values
+ case v => throw new IllegalArgumentException("Do not support vector
type " + v.getClass)
+ }
+ val size = values.size
+
+ if (p == 1) {
--- End diff --
ha~ It only works if I change type from `Double` to `Int`. See the oracle
doc you referenced `The Java Virtual Machine's tableswitch and lookupswitch
instructions operate only on int data. Because operations on byte, char, or
short values are internally promoted to int, a switch whose expression
evaluates to one of those types is compiled as though it evaluated to type int.`
With
```scala
def fun1(p: Int) = {
(p: @switch) match {
case 1 => 1
case 2 => 2
case _ => p
}
}
```
I got
```
public fun1(I)I
L0
LINENUMBER 147 L0
ILOAD 1
ISTORE 2
ILOAD 2
TABLESWITCH
1: L1
2: L2
default: L3
L3
LINENUMBER 150 L3
FRAME APPEND [I]
ILOAD 1
GOTO L4
L2
LINENUMBER 149 L2
FRAME SAME
ICONST_2
GOTO L4
L1
LINENUMBER 148 L1
FRAME SAME
ICONST_1
L4
LINENUMBER 147 L4
FRAME SAME1 I
IRETURN
L5
LOCALVARIABLE this Lorg/apache/spark/mllib/stat/Test$; L0 L5 0
LOCALVARIABLE p I L0 L5 1
MAXSTACK = 1
MAXLOCALS = 3
```
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