Github user liancheng commented on a diff in the pull request:
https://github.com/apache/spark/pull/5279#discussion_r27488225
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeConversions.scala
---
@@ -21,23 +21,20 @@ import java.text.SimpleDateFormat
import org.apache.spark.sql.Row
import org.apache.spark.sql.catalyst.ScalaReflection
-import org.apache.spark.sql.catalyst.expressions.GenericMutableRow
+import org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema
protected[sql] object DataTypeConversions {
def productToRow(product: Product, schema: StructType): Row = {
- val mutableRow = new GenericMutableRow(product.productArity)
- val schemaFields = schema.fields.toArray
-
+ val ar = new Array[Any](schema.length)
var i = 0
- while (i < mutableRow.length) {
- mutableRow(i) =
- ScalaReflection.convertToCatalyst(product.productElement(i),
schemaFields(i).dataType)
+ while (i < schema.length) {
+ ar(i) =
+ ScalaReflection.convertToCatalyst(product.productElement(i),
schema.fields(i).dataType)
i += 1
}
-
- mutableRow
+ new GenericRowWithSchema(ar, schema)
--- End diff --
I agree. The original version uses a mutable row mostly because of the
updates in the while loop I guess.
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