Github user concretevitamin commented on a diff in the pull request:
https://github.com/apache/spark/pull/1774#discussion_r15790441
--- Diff: docs/sql-programming-guide.md ---
@@ -152,6 +152,41 @@ val teenagers = sqlContext.sql("SELECT name FROM
people WHERE age >= 13 AND age
teenagers.map(t => "Name: " + t(0)).collect().foreach(println)
{% endhighlight %}
+Another way to turns an RDD to table is to use `applySchema`. Here is an
example.
+{% highlight scala %}
+// sc is an existing SparkContext.
+val sqlContext = new org.apache.spark.sql.SQLContext(sc)
+
+// Create an RDD
+val people = sc.textFile("examples/src/main/resources/people.txt")
+
+// Import Spark SQL data types and Row.
+import org.apache.spark.sql._
+
+// Define the schema that will be applied to the RDD.
+val schema =
+ StructType(
+ StructField("name", StringType, true) ::
+ StructField("age", IntegerType, true) :: Nil)
+
+// Convert records of the RDD (people) to rows.
--- End diff --
"to Rows"?
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