Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/6869#discussion_r32703264
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/InternalRow.scala ---
@@ -19,39 +19,193 @@ package org.apache.spark.sql.catalyst
import org.apache.spark.sql.Row
import org.apache.spark.sql.catalyst.expressions.GenericRow
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.unsafe.types.UTF8String
/**
* An abstract class for row used internal in Spark SQL, which only
contain the columns as
* internal types.
+ *
+ * The following is a mapping between Spark SQL types and types of objects
in row:
+ *
+ * BooleanType -> java.lang.Boolean
+ * ByteType -> java.lang.Byte
+ * ShortType -> java.lang.Short
+ * IntegerType -> java.lang.Integer
+ * FloatType -> java.lang.Float
+ * DoubleType -> java.lang.Double
+ * StringType -> UTF8String
+ * DecimalType -> org.apache.spark.sql.types.Decimal
+ *
+ * DateType -> java.lang.Int
+ * TimestampType -> java.lang.Long
+ *
+ * BinaryType -> Array[Byte]
+ * ArrayType -> scala.collection.Seq
+ * MapType -> scala.collection.Map
+ * StructType -> InternalRow
*/
-abstract class InternalRow extends Row {
- // A default implementation to change the return type
- override def copy(): InternalRow = {this}
-}
+abstract class InternalRow extends Serializable {
+ /** Number of elements in the Row. */
+ def size: Int = length
-object InternalRow {
- def unapplySeq(row: InternalRow): Some[Seq[Any]] = Some(row.toSeq)
+ /** Number of elements in the Row. */
+ def length: Int
/**
- * This method can be used to construct a [[Row]] with the given values.
+ * Schema for the row.
*/
- def apply(values: Any*): InternalRow = new GenericRow(values.toArray)
+ def schema: StructType = null
--- End diff --
do we need this here?
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