Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/13592#discussion_r67749954
--- Diff: docs/sql-programming-guide.md ---
@@ -419,35 +423,39 @@ In addition to simple column references and
expressions, DataFrames also have a
## Running SQL Queries Programmatically
-The `sql` function on a `SQLContext` enables applications to run SQL
queries programmatically and returns the result as a `DataFrame`.
-
<div class="codetabs">
<div data-lang="scala" markdown="1">
+The `sql` function on a `SparkSession` enables applications to run SQL
queries programmatically and returns the result as a `DataFrame`.
+
{% highlight scala %}
-val sqlContext = ... // An existing SQLContext
-val df = sqlContext.sql("SELECT * FROM table")
+val spark = ... // An existing SparkSession
+val df = spark.sql("SELECT * FROM table")
{% endhighlight %}
</div>
<div data-lang="java" markdown="1">
+The `sql` function on a `SparkSession` enables applications to run SQL
queries programmatically and returns the result as a `Dataset<Row>`.
+
{% highlight java %}
-SQLContext sqlContext = ... // An existing SQLContext
-DataFrame df = sqlContext.sql("SELECT * FROM table")
+SparkSession spark = ... // An existing SparkSession
+Dataset<Row> df = spark.sql("SELECT * FROM table")
{% endhighlight %}
</div>
<div data-lang="python" markdown="1">
+The `sql` function on a `SparkSession` enables applications to run SQL
queries programmatically and returns the result as a `DataFrame`.
+
{% highlight python %}
-from pyspark.sql import SQLContext
-sqlContext = SQLContext(sc)
-df = sqlContext.sql("SELECT * FROM table")
+# spark is an existing SparkSession
+df = spark.sql("SELECT * FROM table")
{% endhighlight %}
</div>
<div data-lang="r" markdown="1">
+The `sql` function enables applications to run SQL queries
programmatically and returns the result as a `DataFrame`.
--- End diff --
also, in SparkR, the class is called "SparkDataFrame"
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