Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/1346#discussion_r14904635
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala ---
@@ -89,6 +88,33 @@ class SQLContext(@transient val sparkContext:
SparkContext)
new SchemaRDD(this, SparkLogicalPlan(ExistingRdd.fromProductRdd(rdd)))
/**
+ * Creates a [[SchemaRDD]] from an [[RDD]] by applying a schema to this
RDD and using a function
+ * that will be applied to each partition of the RDD to convert RDD
records to [[Row]]s.
+ *
+ * @group userf
+ */
+ def applySchema[A](rdd: RDD[A], schema: StructType, f: A => Row):
SchemaRDD =
+ applySchemaToPartitions(rdd, schema, (iter: Iterator[A]) =>
iter.map(f))
+
+ /**
+ * Creates a [[SchemaRDD]] from an [[RDD]] by applying a schema to this
RDD and using a function
+ * that will be applied to each partition of the RDD to convert RDD
records to [[Row]]s.
--- End diff --
Maybe provide some guidance here on when you'd want to use this function.
> Similar to `RDD.mapPartitions`, this function can be used to improve
performance where there is other setup work that can be amortized and used
repeatedly for all of the elements in a partition.
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