Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/1346#discussion_r15482888
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala ---
@@ -89,6 +90,44 @@ class SQLContext(@transient val sparkContext:
SparkContext)
new SchemaRDD(this, SparkLogicalPlan(ExistingRdd.fromProductRdd(rdd)))
/**
+ * :: DeveloperApi ::
+ * Creates a [[SchemaRDD]] from an [[RDD]] containing [[Row]]s by
applying a schema to this RDD.
+ * It is important to make sure that the structure of every [[Row]] of
the provided RDD matches
+ * the provided schema. Otherwise, there will be runtime exception.
+ *
+ * @group userf
+ */
+ @DeveloperApi
+ def applySchema(rowRDD: RDD[Row], schema: StructType): SchemaRDD = {
+ // TODO: use MutableProjection when rowRDD is another SchemaRDD and
the applied
+ // schema differs from the existing schema on any field data type.
+ val logicalPlan = SparkLogicalPlan(ExistingRdd(schema.toAttributes,
rowRDD))
+ new SchemaRDD(this, logicalPlan)
+ }
+
+ /**
+ * Parses the data type in our internal string representation. The data
type string should
+ * have the same format as the one generate by `toString` in scala.
--- End diff --
Is this only here for pyspark? Probably should make a note of that.
Nit: "generated"
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