diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala index b5a69cee6daf3..796758a70ef18 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala @@ -102,6 +102,6 @@ object VectorAssembler { case o => throw new SparkException(s"$o of type ${o.getClass.getName} is not supported.") } - Vectors.sparse(cur, indices.result(), values.result()) + Vectors.sparse(cur, indices.result(), values.result()).compressed } } diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala index 57d0278e03639..0db27607bc274 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala @@ -20,7 +20,7 @@ package org.apache.spark.ml.feature import org.scalatest.FunSuite import org.apache.spark.SparkException -import org.apache.spark.mllib.linalg.{Vector, Vectors} +import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.{Row, SQLContext} @@ -48,6 +48,14 @@ class VectorAssemblerSuite extends FunSuite with MLlibTestSparkContext { } } + test("assemble should compress vectors") { + import org.apache.spark.ml.feature.VectorAssembler.assemble + val v1 = assemble(0.0, 0.0, 0.0, Vectors.dense(4.0)) + assert(v1.isInstanceOf[SparseVector]) + val v2 = assemble(1.0, 2.0, 3.0, Vectors.sparse(1, Array(0), Array(4.0))) + assert(v2.isInstanceOf[DenseVector]) + } + test("VectorAssembler") { val df = sqlContext.createDataFrame(Seq( (0, 0.0, Vectors.dense(1.0, 2.0), "a", Vectors.sparse(2, Array(1), Array(3.0)), 10L) diff --git a/python/pyspark/ml/feature.py b/python/pyspark/ml/feature.py index 8a0fdddd2d9b5..705a368192c24 100644 --- a/python/pyspark/ml/feature.py +++ b/python/pyspark/ml/feature.py @@ -121,12 +121,12 @@ class VectorAssembler(JavaTransformer, HasInputCols, HasOutputCol): >>> df = sc.parallelize([Row(a=1, b=0, c=3)]).toDF() >>> vecAssembler = VectorAssembler(inputCols=["a", "b", "c"], outputCol="features") >>> vecAssembler.transform(df).head().features - SparseVector(3, {0: 1.0, 2: 3.0}) + DenseVector([1.0, 0.0, 3.0]) >>> vecAssembler.setParams(outputCol="freqs").transform(df).head().freqs - SparseVector(3, {0: 1.0, 2: 3.0}) + DenseVector([1.0, 0.0, 3.0]) >>> params = {vecAssembler.inputCols: ["b", "a"], vecAssembler.outputCol: "vector"} >>> vecAssembler.transform(df, params).head().vector - SparseVector(2, {1: 1.0}) + DenseVector([0.0, 1.0]) """ _java_class = "org.apache.spark.ml.feature.VectorAssembler"