Github user liancheng commented on a diff in the pull request:
https://github.com/apache/spark/pull/8971#discussion_r41426190
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnType.scala ---
@@ -399,24 +415,164 @@ private[sql] object BINARY extends
ByteArrayColumnType(16) {
override def getField(row: InternalRow, ordinal: Int): Array[Byte] = {
row.getBinary(ordinal)
}
+
+ def serialize(value: Array[Byte]): Array[Byte] = value
+ def deserialize(bytes: Array[Byte]): Array[Byte] = bytes
}
-// Used to process generic objects (all types other than those listed
above). Objects should be
-// serialized first before appending to the column `ByteBuffer`, and is
also extracted as serialized
-// byte array.
-private[sql] case class GENERIC(dataType: DataType) extends
ByteArrayColumnType(16) {
- override def setField(row: MutableRow, ordinal: Int, value:
Array[Byte]): Unit = {
- row.update(ordinal, SparkSqlSerializer.deserialize[Any](value))
+private[sql] case class DECIMAL(precision: Int, scale: Int)
--- End diff --
Maybe rename this one as `LARGE_DECIMAL` (in contrast to `COMPACT_DECIMAL`)
since this only handles decimals with precision >= 19.
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