You declare that the vector has 3 dimensions, but then refer to its
4th dimension (at index 3). That is the error.
On Wed, Aug 3, 2016 at 10:43 AM, Tony Lane <tonylane....@gmail.com> wrote:
> I am using the following vector definition in java
>
> Vectors.sparse(3, new int[] { 1, 2, 3 }, new double[] { 1.1, 1.1, 1.1 }))
>
> However when I run the predict method on this vector it leads to
>
> Exception in thread "main" java.lang.ArrayIndexOutOfBoundsException: 3
> at org.apache.spark.mllib.linalg.BLAS$.dot(BLAS.scala:143)
> at org.apache.spark.mllib.linalg.BLAS$.dot(BLAS.scala:115)
> at
> org.apache.spark.mllib.util.MLUtils$.fastSquaredDistance(MLUtils.scala:298)
> at
> org.apache.spark.mllib.clustering.KMeans$.fastSquaredDistance(KMeans.scala:606)
> at
> org.apache.spark.mllib.clustering.KMeans$$anonfun$findClosest$1.apply(KMeans.scala:580)
> at
> org.apache.spark.mllib.clustering.KMeans$$anonfun$findClosest$1.apply(KMeans.scala:574)
> at scala.collection.mutable.ArraySeq.foreach(ArraySeq.scala:74)
> at org.apache.spark.mllib.clustering.KMeans$.findClosest(KMeans.scala:574)
> at
> org.apache.spark.mllib.clustering.KMeansModel.predict(KMeansModel.scala:59)
> at org.apache.spark.ml.clustering.KMeansModel.predict(KMeans.scala:130)
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