Add a test case for the new TypedRow encoder

implemented the proposal

Author: tribbloid

dataset/src/main/scala/frameless/RecordEncoder.scala

@@ -119,20 +119,19 @@ object DropUnitValues {
     }
 }
 
-class RecordEncoder[F, G <: HList, H <: HList]
+abstract class RecordEncoder[F, G <: HList, H <: HList]
   (implicit
-    i0: LabelledGeneric.Aux[F, G],
-    i1: DropUnitValues.Aux[G, H],
-    i2: IsHCons[H],
-    fields: Lazy[RecordEncoderFields[H]],
-    newInstanceExprs: Lazy[NewInstanceExprs[G]],
+    stage1: RecordEncoderStage1[G, H],
     classTag: ClassTag[F]
   ) extends TypedEncoder[F] {
+
+  import stage1._
+
     def nullable: Boolean = false
 
-    def jvmRepr: DataType = FramelessInternals.objectTypeFor[F]
+    lazy val jvmRepr: DataType = FramelessInternals.objectTypeFor[F]
 
-    def catalystRepr: DataType = {
+    lazy val catalystRepr: DataType = {
       val structFields = fields.value.value.map { field =>
         StructField(
           name = field.name,
@@ -145,41 +144,94 @@ class RecordEncoder[F, G <: HList, H <: HList]
       StructType(structFields)
     }
 
+  }
+
+object RecordEncoder {
+
+  case class ForGeneric[F, G <: HList, H <: HList](
+    )(implicit
+      stage1: RecordEncoderStage1[G, H],
+      classTag: ClassTag[F])
+      extends RecordEncoder[F, G, H] {
+
+    import stage1._
+
     def toCatalyst(path: Expression): Expression = {
-      val nameExprs = fields.value.value.map { field =>
-        Literal(field.name)
-      }
 
       val valueExprs = fields.value.value.map { field =>
         val fieldPath = Invoke(path, field.name, field.encoder.jvmRepr, Nil)
         field.encoder.toCatalyst(fieldPath)
       }
 
-      // the way exprs are encoded in CreateNamedStruct
-      val exprs = nameExprs.zip(valueExprs).flatMap {
-        case (nameExpr, valueExpr) => nameExpr :: valueExpr :: Nil
-      }
+      val createExpr = stage1.cellsToCatalyst(valueExprs)
 
-      val createExpr = CreateNamedStruct(exprs)
       val nullExpr = Literal.create(null, createExpr.dataType)
 
       If(IsNull(path), nullExpr, createExpr)
     }
 
     def fromCatalyst(path: Expression): Expression = {
-      val exprs = fields.value.value.map { field =>
-        field.encoder.fromCatalyst(
-          GetStructField(path, field.ordinal, Some(field.name)))
-      }
 
-      val newArgs = newInstanceExprs.value.from(exprs)
+      val newArgs = stage1.fromCatalystToCells(path)
       val newExpr = NewInstance(
         classTag.runtimeClass, newArgs, jvmRepr, propagateNull = true)
 
       val nullExpr = Literal.create(null, jvmRepr)
 
       If(IsNull(path), nullExpr, newExpr)
     }
+  }
+
+  case class ForTypedRow[G <: HList, H <: HList](
+    )(implicit
+      stage1: RecordEncoderStage1[G, H],
+      classTag: ClassTag[TypedRow[G]])
+      extends RecordEncoder[TypedRow[G], G, H] {
+
+    import stage1._
+
+    private final val _apply = "apply"
+    private final val _fromInternalRow = "fromInternalRow"
+
+    def toCatalyst(path: Expression): Expression = {
+
+      val valueExprs = fields.value.value.zipWithIndex.map {
+        case (field, i) =>
+          val fieldPath = Invoke(
+            path,
+            _apply,
+            field.encoder.jvmRepr,
+            Seq(Literal.create(i, IntegerType))
+          )
+          field.encoder.toCatalyst(fieldPath)
+      }
+
+      val createExpr = stage1.cellsToCatalyst(valueExprs)
+
+      val nullExpr = Literal.create(null, createExpr.dataType)
+
+      If(IsNull(path), nullExpr, createExpr)
+    }
+
+    def fromCatalyst(path: Expression): Expression = {
+
+      val newArgs = stage1.fromCatalystToCells(path)
+      val aggregated = CreateStruct(newArgs)
+
+      val partial = TypedRow.WithCatalystTypes(newArgs.map(_.dataType))
+
+      val newExpr = Invoke(
+        Literal.fromObject(partial),
+        _fromInternalRow,
+        TypedRow.catalystType,
+        Seq(aggregated)
+      )
+
+      val nullExpr = Literal.create(null, jvmRepr)
+
+      If(IsNull(path), nullExpr, newExpr)
+    }
+  }
 }
 
 final class RecordFieldEncoder[T](

dataset/src/main/scala/frameless/RecordEncoderStage1.scala

@@ -0,0 +1,49 @@
+package frameless
+
+import org.apache.spark.sql.catalyst.expressions.{
+  CreateNamedStruct,
+  Expression,
+  GetStructField,
+  Literal
+}
+import shapeless.{ HList, Lazy }
+
+case class RecordEncoderStage1[G <: HList, H <: HList](
+  )(implicit
+//    i1: DropUnitValues.Aux[G, H],
+//    i2: IsHCons[H],
+    val fields: Lazy[RecordEncoderFields[H]],
+    val newInstanceExprs: Lazy[NewInstanceExprs[G]]) {
+
+  def cellsToCatalyst(valueExprs: Seq[Expression]): Expression = {
+    val nameExprs = fields.value.value.map { field => Literal(field.name) }
+
+    // the way exprs are encoded in CreateNamedStruct
+    val exprs = nameExprs.zip(valueExprs).flatMap {
+      case (nameExpr, valueExpr) => nameExpr :: valueExpr :: Nil
+    }
+
+    val createExpr = CreateNamedStruct(exprs)
+    createExpr
+  }
+
+  def fromCatalystToCells(path: Expression): Seq[Expression] = {
+    val exprs = fields.value.value.map { field =>
+      field.encoder.fromCatalyst(
+        GetStructField(path, field.ordinal, Some(field.name))
+      )
+    }
+
+    val newArgs = newInstanceExprs.value.from(exprs)
+    newArgs
+  }
+}
+
+object RecordEncoderStage1 {
+
+  implicit def usingDerivation[G <: HList, H <: HList](
+      implicit
+      i3: Lazy[RecordEncoderFields[H]],
+      i4: Lazy[NewInstanceExprs[G]]
+    ): RecordEncoderStage1[G, H] = RecordEncoderStage1[G, H]()
+}

dataset/src/main/scala/frameless/TypedEncoder.scala

@@ -727,15 +727,23 @@ object TypedEncoder {
     }
 
   /** Encodes things as records if there is no Injection defined */
-  implicit def usingDerivation[F, G <: HList, H <: HList](
+  implicit def deriveForGeneric[F, G <: HList, H <: HList](
       implicit
       i0: LabelledGeneric.Aux[F, G],
       i1: DropUnitValues.Aux[G, H],
       i2: IsHCons[H],
       i3: Lazy[RecordEncoderFields[H]],
       i4: Lazy[NewInstanceExprs[G]],
       i5: ClassTag[F]
-    ): TypedEncoder[F] = new RecordEncoder[F, G, H]
+    ): TypedEncoder[F] = RecordEncoder.ForGeneric[F, G, H]()
+
+  implicit def deriveForTypedRow[G <: HList, H <: HList](
+      implicit
+      i1: DropUnitValues.Aux[G, H],
+      i2: IsHCons[H],
+      i3: Lazy[RecordEncoderFields[H]],
+      i4: Lazy[NewInstanceExprs[G]]
+    ): TypedEncoder[TypedRow[G]] = RecordEncoder.ForTypedRow[G, H]()
 
   /** Encodes things using a Spark SQL's User Defined Type (UDT) if there is one defined in implicit */
   implicit def usingUserDefinedType[

dataset/src/main/scala/frameless/TypedRow.scala

@@ -0,0 +1,45 @@
+package frameless
+
+import org.apache.spark.sql.Row
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.types.{ DataType, ObjectType }
+import shapeless.HList
+
+case class TypedRow[T <: HList](row: Row) {
+
+  def apply(i: Int): Any = row.apply(i)
+}
+
+object TypedRow {
+
+  def apply(values: Any*): TypedRow[HList] = {
+
+    val row = Row.fromSeq(values)
+    TypedRow(row)
+  }
+
+  case class WithCatalystTypes(schema: Seq[DataType]) {
+
+    def fromInternalRow(row: InternalRow): TypedRow[HList] = {
+      val data = row.toSeq(schema).toArray
+
+      apply(data: _*)
+    }
+
+  }
+
+  object WithCatalystTypes {}
+
+  def fromHList[T <: HList](
+      hlist: T
+    ): TypedRow[T] = {
+
+    val cells = hlist.runtimeList
+
+    val row = Row.fromSeq(cells)
+    TypedRow(row)
+  }
+
+  lazy val catalystType: ObjectType = ObjectType(classOf[TypedRow[_]])
+
+}

dataset/src/test/scala/frameless/InjectionTests.scala

@@ -180,7 +180,7 @@ class InjectionTests extends TypedDatasetSuite {
   }
 
   test("Resolve ambiguity by importing usingDerivation") {
-    import TypedEncoder.usingDerivation
+    import TypedEncoder.deriveForGeneric
     assert(implicitly[TypedEncoder[Person]].isInstanceOf[RecordEncoder[Person, _, _]])
     check(forAll(prop[Person] _))
   }

dataset/src/test/scala/frameless/RecordEncoderTests.scala

@@ -1,23 +1,12 @@
 package frameless
 
-import org.apache.spark.sql.{Row, functions => F}
-import org.apache.spark.sql.types.{
-  ArrayType,
-  BinaryType,
-  DecimalType,
-  IntegerType,
-  LongType,
-  MapType,
-  ObjectType,
-  StringType,
-  StructField,
-  StructType
-}
-
-import shapeless.{HList, LabelledGeneric}
-import shapeless.test.illTyped
-
+import frameless.RecordEncoderTests.{ A, B, E }
+import org.apache.spark.sql.types._
+import org.apache.spark.sql.{ Row, functions => F }
 import org.scalatest.matchers.should.Matchers
+import shapeless.record.Record
+import shapeless.test.illTyped
+import shapeless.{ HList, LabelledGeneric }
 
 final class RecordEncoderTests extends TypedDatasetSuite with Matchers {
   test("Unable to encode products made from units only") {
@@ -87,6 +76,20 @@ final class RecordEncoderTests extends TypedDatasetSuite with Matchers {
     ds.collect.head shouldBe obj
   }
 
+  test("TypedRow") {
+
+    val r1: RecordEncoderTests.RR = Record(x = 1, y = "abc")
+    val r2: TypedRow[RecordEncoderTests.RR] = TypedRow.fromHList(r1)
+
+    val rdd = sc.parallelize(Seq(r2))
+    val ds =
+      session.createDataset(rdd)(
+        TypedExpressionEncoder[TypedRow[RecordEncoderTests.RR]]
+      )
+
+    ds.collect.head shouldBe r2
+  }
+
   test("Scalar value class") {
     import RecordEncoderTests._
 
@@ -548,6 +551,9 @@ object RecordEncoderTests {
   case class D(m: Map[String, Int])
   case class E(b: Set[B])
 
+  val RR = Record.`'x -> Int, 'y -> String`
+  type RR = RR.T
+
   final class Subject(val name: String) extends AnyVal with Serializable
 
   final class Grade(val value: BigDecimal) extends AnyVal with Serializable

refined/src/test/scala/frameless/RefinedFieldEncoderTests.scala

@@ -114,7 +114,7 @@ object RefinedTypesTests {
 
   import frameless.refined._ // implicit instances for refined
 
-  implicit val encoderA: TypedEncoder[A] = TypedEncoder.usingDerivation
+  implicit val encoderA: TypedEncoder[A] = TypedEncoder.deriveForGeneric
 
-  implicit val encoderB: TypedEncoder[B] = TypedEncoder.usingDerivation
+  implicit val encoderB: TypedEncoder[B] = TypedEncoder.deriveForGeneric
 }