remove element type parameter from getArray

mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala

@@ -154,9 +154,9 @@ private[spark] class MatrixUDT extends UserDefinedType[Matrix] {
         row.setByte(0, 0)
         row.setInt(1, sm.numRows)
         row.setInt(2, sm.numCols)
-        row.update(3, sm.colPtrs.toSeq)
-        row.update(4, sm.rowIndices.toSeq)
-        row.update(5, sm.values.toSeq)
+        row.update(3, new GenericArrayData(sm.colPtrs.map(_.asInstanceOf[Any])))
+        row.update(4, new GenericArrayData(sm.rowIndices.map(_.asInstanceOf[Any])))
+        row.update(5, new GenericArrayData(sm.values.map(_.asInstanceOf[Any])))
         row.setBoolean(6, sm.isTransposed)
 
       case dm: DenseMatrix =>
@@ -165,7 +165,7 @@ private[spark] class MatrixUDT extends UserDefinedType[Matrix] {
         row.setInt(2, dm.numCols)
         row.setNullAt(3)
         row.setNullAt(4)
-        row.update(5, dm.values.toSeq)
+        row.update(5, new GenericArrayData(dm.values.map(_.asInstanceOf[Any])))
         row.setBoolean(6, dm.isTransposed)
     }
     row
@@ -179,14 +179,12 @@ private[spark] class MatrixUDT extends UserDefinedType[Matrix] {
         val tpe = row.getByte(0)
         val numRows = row.getInt(1)
         val numCols = row.getInt(2)
-        val values = row.getAs[Seq[Double]](5, ArrayType(DoubleType, containsNull = false)).toArray
+        val values = row.getArray(5).toArray.map(_.asInstanceOf[Double])
         val isTransposed = row.getBoolean(6)
         tpe match {
           case 0 =>
-            val colPtrs =
-              row.getAs[Seq[Int]](3, ArrayType(IntegerType, containsNull = false)).toArray
-            val rowIndices =
-              row.getAs[Seq[Int]](4, ArrayType(IntegerType, containsNull = false)).toArray
+            val colPtrs = row.getArray(3).toArray.map(_.asInstanceOf[Int])
+            val rowIndices = row.getArray(4).toArray.map(_.asInstanceOf[Int])
             new SparseMatrix(numRows, numCols, colPtrs, rowIndices, values, isTransposed)
           case 1 =>
             new DenseMatrix(numRows, numCols, values, isTransposed)

mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala

@@ -209,11 +209,11 @@ private[spark] class VectorUDT extends UserDefinedType[Vector] {
         tpe match {
           case 0 =>
             val size = row.getInt(1)
-            val indices = row.getArray(2, IntegerType).toArray().map(_.asInstanceOf[Int])
-            val values = row.getArray(3, DoubleType).toArray().map(_.asInstanceOf[Double])
+            val indices = row.getArray(2).toArray().map(_.asInstanceOf[Int])
+            val values = row.getArray(3).toArray().map(_.asInstanceOf[Double])
             new SparseVector(size, indices, values)
           case 1 =>
-            val values = row.getArray(3, DoubleType).toArray().map(_.asInstanceOf[Double])
+            val values = row.getArray(3).toArray().map(_.asInstanceOf[Double])
             new DenseVector(values)
         }
     }

sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/SpecializedGetters.java

@@ -52,5 +52,5 @@ public interface SpecializedGetters {
 
   InternalRow getStruct(int ordinal, int numFields);
 
-  ArrayData getArray(int ordinal, DataType elementType);
+  ArrayData getArray(int ordinal);
 }

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/CatalystTypeConverters.scala

@@ -187,7 +187,7 @@ object CatalystTypeConverters {
     }
 
     override def toScalaImpl(row: InternalRow, column: Int): Seq[Any] =
-      toScala(row.getArray(column, elementType))
+      toScala(row.getArray(column))
   }
 
   private case class MapConverter(

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/InternalRow.scala

@@ -76,7 +76,7 @@ abstract class InternalRow extends Serializable with SpecializedGetters {
   override def getStruct(ordinal: Int, numFields: Int): InternalRow =
     getAs[InternalRow](ordinal, null)
 
-  override def getArray(ordinal: Int, elementType: DataType): ArrayData = getAs(ordinal, null)
+  override def getArray(ordinal: Int): ArrayData = getAs(ordinal, null)
 
   override def toString: String = s"[${this.mkString(",")}]"
 

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala

@@ -110,9 +110,7 @@ class CodeGenContext {
       case BinaryType => s"$getter.getBinary($ordinal)"
       case CalendarIntervalType => s"$getter.getInterval($ordinal)"
       case t: StructType => s"$getter.getStruct($ordinal, ${t.size})"
-      case a: ArrayType =>
-        val typeString = '"' + a.elementType.json.replace("\"", "\\\"") + '"'
-        s"$getter.getArray($ordinal, org.apache.spark.sql.types.DataType.fromJson($typeString))"
+      case a: ArrayType => s"$getter.getArray($ordinal)"
       case _ => s"($jt)$getter.get($ordinal)" // todo: remove generic getter.
     }
   }

sql/catalyst/src/main/scala/org/apache/spark/sql/types/GenericArrayData.scala

@@ -53,7 +53,7 @@ class GenericArrayData(array: Array[Any]) extends ArrayData {
 
   override def getStruct(ordinal: Int, numFields: Int): InternalRow = getAs(ordinal)
 
-  override def getArray(ordinal: Int, elementType: DataType): ArrayData = getAs(ordinal)
+  override def getArray(ordinal: Int): ArrayData = getAs(ordinal)
 
   override def numElements(): Int = array.length
 }