[GitHub] [spark] HyukjinKwon commented on a change in pull request #34359: [SPARK-36986][SQL] Improving external schema management flexibility on DataSet and StructType

[GitBox <gi...@apache.org>]

HyukjinKwon commented on a change in pull request #34359:
URL: https://github.com/apache/spark/pull/34359#discussion_r734908797



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/SparkSession.scala
##########
@@ -511,6 +511,20 @@ class SparkSession private(
     createDataset(data.asScala.toSeq)
   }
 
+  /**
+   * Creates a [[Dataset]] from an RDD of spark.sql.catalyst.InternalRow. This method allows
+   * the caller to create externally the InternalRow set, as we as define the schema externally.
+   *
+   * @since 3.3.0
+   */
+  def createDataset(data: RDD[InternalRow], schema: StructType): DataFrame = {

Review comment:
       My concern is that `InternalRow` is not supposed to be exposed to end users.
   
   Maybe we should expose `Dataset.ofRows` as a developer API, and do it like:
   
   ```scala
   Dataset.ofRows(
     spark,
     org.apache.spark.sql.execution.LogicalRDD(
       df.queryExecution.executedPlan.output, df.queryExecution.toRdd)(spark))
   ```




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