viirya commented on code in PR #493:
URL: https://github.com/apache/spark-website/pull/493#discussion_r1426302479


##########
examples.md:
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@@ -19,12 +19,18 @@ On top of Spark’s RDD API, high level APIs are provided, 
e.g.
 [DataFrame 
API](https://spark.apache.org/docs/latest/sql-programming-guide.html#datasets-and-dataframes)
 and
 [Machine Learning API](https://spark.apache.org/docs/latest/mllib-guide.html).
 These high level APIs provide a concise way to conduct certain data operations.
-In this page, we will show examples using RDD API as well as examples using 
high level APIs.
 
-<h2>RDD API examples</h2>
+<h2>DataFrame API examples</h2>
+<p>
+In Spark, a <a 
href="https://spark.apache.org/docs/latest/sql-programming-guide.html#dataframes";>DataFrame</a>
+is a distributed collection of data organized into named columns.
+Users can use DataFrame API to perform various relational operations on both 
external
+data sources and Spark’s built-in distributed collections without providing 
specific procedures for processing data.
+Also, programs based on DataFrame API will be automatically optimized by 
Spark’s built-in optimizer, Catalyst.
+</p>
 
 <h3>Word count</h3>
-<p>In this example, we use a few transformations to build a dataset of 
(String, Int) pairs called <code>counts</code> and then save it to a file.</p>
+<p>In this example, we use a few transformations to build a dataset of 
(String, Long) pairs and then save it to a file.</p>

Review Comment:
   Hmm, I think `transformations` are terms used for RDD operations (i.e, 
`transformations` and `actions` as this page mentioned above)? For DataFrame, 
maybe `relational operations`?



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