Github user liancheng commented on a diff in the pull request:
https://github.com/apache/spark/pull/14119#discussion_r70262914
--- Diff: docs/sql-programming-guide.md ---
@@ -679,43 +435,7 @@ a `DataFrame` can be created programmatically with
three steps.
by `SparkSession`.
For example:
-{% highlight scala %}
-val spark: SparkSession // An existing SparkSession
-
-// Create an RDD
-val people = sc.textFile("examples/src/main/resources/people.txt")
-
-// The schema is encoded in a string
-val schemaString = "name age"
-
-// Import Row.
-import org.apache.spark.sql.Row;
-
-// Import Spark SQL data types
-import org.apache.spark.sql.types.{StructType, StructField, StringType};
-
-// Generate the schema based on the string of schema
-val schema = StructType(schemaString.split(" ").map { fieldName =>
- StructField(fieldName, StringType, true)
-})
-
-// Convert records of the RDD (people) to Rows.
-val rowRDD = people.map(_.split(",")).map(p => Row(p(0), p(1).trim))
-
-// Apply the schema to the RDD.
-val peopleDataFrame = spark.createDataFrame(rowRDD, schema)
-
-// Creates a temporary view using the DataFrame.
-peopleDataFrame.createOrReplaceTempView("people")
-
-// SQL statements can be run by using the sql methods provided by spark.
-val results = spark.sql("SELECT name FROM people")
-
-// The columns of a row in the result can be accessed by field index or by
field name.
-results.map(t => "Name: " + t(0)).collect().foreach(println)
-{% endhighlight %}
-
-
+{% include_example programmatic_schema
scala/org/apache/spark/examples/sql/SparkSqlExample.scala %}
--- End diff --
Seems that you have to add a newline before the `{% include_example ... %}`
tag, otherwise this section can't be properly rendered, not sure why:
<img width="925" alt="screenshot at jul 11 21-59-30"
src="https://cloud.githubusercontent.com/assets/230655/16733123/cd5a0d70-47b2-11e6-9689-621e9bdac73f.png";>
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