Skip to content

[SPARK-20615][ML][TEST] SparseVector.argmax throws IndexOutOfBoundsException #17877

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
jonmclean wants to merge 3 commits into from
Closed

[SPARK-20615][ML][TEST] SparseVector.argmax throws IndexOutOfBoundsException #17877

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
2096430
Added tests to illustrate bug SPARK-20615
May 5, 2017
5614f58
Made SparseVector.argmax return 0 when no values are defined in the v…
May 5, 2017
8969f02
Fixed style issue by removing whitespace
May 5, 2017
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 2 additions & 0 deletions mllib-local/src/main/scala/org/apache/spark/ml/linalg/Vectors.scala
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -657,6 +657,8 @@ class SparseVector @Since("2.0.0") (
override def argmax: Int = {
if (size == 0) {
-1
} else if (numActives == 0) {
0
} else {
// Find the max active entry.
var maxIdx = indices(0)
Expand Down
7 changes: 7 additions & 0 deletions mllib-local/src/test/scala/org/apache/spark/ml/linalg/VectorsSuite.scala
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -125,6 +125,13 @@ class VectorsSuite extends SparkMLFunSuite {

val vec8 = Vectors.sparse(5, Array(1, 2), Array(0.0, -1.0))
assert(vec8.argmax === 0)

// Check for case when sparse vector is non-empty but the values are empty
val vec9 = Vectors.sparse(100, Array.empty[Int], Array.empty[Double]).asInstanceOf[SparseVector]
assert(vec9.argmax === 0)

val vec10 = Vectors.sparse(1, Array.empty[Int], Array.empty[Double]).asInstanceOf[SparseVector]
assert(vec10.argmax === 0)
}

test("vector equals") {
Expand Down
2 changes: 2 additions & 0 deletions mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -846,6 +846,8 @@ class SparseVector @Since("1.0.0") (
override def argmax: Int = {
if (size == 0) {
-1
} else if (numActives == 0) {
0
} else {
// Find the max active entry.
var maxIdx = indices(0)
Expand Down
7 changes: 7 additions & 0 deletions mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -122,6 +122,13 @@ class VectorsSuite extends SparkFunSuite with Logging {

val vec8 = Vectors.sparse(5, Array(1, 2), Array(0.0, -1.0))
assert(vec8.argmax === 0)

// Check for case when sparse vector is non-empty but the values are empty
val vec9 = Vectors.sparse(100, Array.empty[Int], Array.empty[Double]).asInstanceOf[SparseVector]
assert(vec9.argmax === 0)

val vec10 = Vectors.sparse(1, Array.empty[Int], Array.empty[Double]).asInstanceOf[SparseVector]
assert(vec10.argmax === 0)
}

test("vector equals") {
Expand Down