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SPARK-3803 [MLLIB] ArrayIndexOutOfBoundsException found in executing computePrincipalComponents #2801

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SPARK-3803 [MLLIB] ArrayIndexOutOfBoundsException found in executing computePrincipalComponents #2801

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22 changes: 15 additions & 7 deletions mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -111,7 +111,10 @@ class RowMatrix(
*/
def computeGramianMatrix(): Matrix = {
val n = numCols().toInt
val nt: Int = n * (n + 1) / 2
checkNumColumns(n)
// Computes n*(n+1)/2, avoiding overflow in the multiplication.
// This succeeds when n <= 65535, which is checked above
val nt: Int = if (n % 2 == 0) ((n / 2) * (n + 1)) else (n * ((n + 1) / 2))

// Compute the upper triangular part of the gram matrix.
val GU = rows.treeAggregate(new BDV[Double](new Array[Double](nt)))(
Expand All @@ -123,6 +126,16 @@ class RowMatrix(
RowMatrix.triuToFull(n, GU.data)
}

private def checkNumColumns(cols: Int): Unit = {
if (cols > 65535) {
throw new IllegalArgumentException(s"Argument with more than 65535 cols: $cols")
}
if (cols > 10000) {
val mem = cols * cols * 8
logWarning(s"$cols columns will require at least $mem bytes of memory!")
}
}

/**
* Computes singular value decomposition of this matrix. Denote this matrix by A (m x n). This
* will compute matrices U, S, V such that A ~= U * S * V', where S contains the leading k
Expand Down Expand Up @@ -301,12 +314,7 @@ class RowMatrix(
*/
def computeCovariance(): Matrix = {
val n = numCols().toInt

if (n > 10000) {
val mem = n * n * java.lang.Double.SIZE / java.lang.Byte.SIZE
logWarning(s"The number of columns $n is greater than 10000! " +
s"We need at least $mem bytes of memory.")
}
checkNumColumns(n)

val (m, mean) = rows.treeAggregate[(Long, BDV[Double])]((0L, BDV.zeros[Double](n)))(
seqOp = (s: (Long, BDV[Double]), v: Vector) => (s._1 + 1L, s._2 += v.toBreeze),
Expand Down