[SPARK-15610][ML] update error message for k in pca

## What changes were proposed in this pull request?
Fix the wrong bound of `k` in `PCA`
`require(k <= sources.first().size, ...`  ->  `require(k < sources.first().size`

BTW, remove unused import in `ml.ElementwiseProduct`

## How was this patch tested?

manual tests

Author: Zheng RuiFeng <ruifengz@foxmail.com>

Closes #13356 from zhengruifeng/fix_pca.

mllib/src/main/scala/org/apache/spark/ml/feature/ElementwiseProduct.scala

@@ -23,7 +23,6 @@ import org.apache.spark.ml.linalg.{Vector, VectorUDT}
 import org.apache.spark.ml.param.Param
 import org.apache.spark.ml.util.{DefaultParamsReadable, DefaultParamsWritable, Identifiable}
 import org.apache.spark.mllib.feature
-import org.apache.spark.mllib.linalg.{Vectors => OldVectors}
 import org.apache.spark.mllib.linalg.VectorImplicits._
 import org.apache.spark.sql.types.DataType
 

mllib/src/main/scala/org/apache/spark/mllib/feature/PCA.scala

@@ -40,8 +40,9 @@ class PCA @Since("1.4.0") (@Since("1.4.0") val k: Int) {
    */
   @Since("1.4.0")
   def fit(sources: RDD[Vector]): PCAModel = {
-    require(k <= sources.first().size,
-      s"source vector size is ${sources.first().size} must be greater than k=$k")
+    val numFeatures = sources.first().size
+    require(k <= numFeatures,
+      s"source vector size $numFeatures must be no less than k=$k")
 
     val mat = new RowMatrix(sources)
     val (pc, explainedVariance) = mat.computePrincipalComponentsAndExplainedVariance(k)
@@ -58,7 +59,6 @@ class PCA @Since("1.4.0") (@Since("1.4.0") val k: Int) {
       case m =>
         throw new IllegalArgumentException("Unsupported matrix format. Expected " +
           s"SparseMatrix or DenseMatrix. Instead got: ${m.getClass}")
-
     }
     val denseExplainedVariance = explainedVariance match {
       case dv: DenseVector =>