Github user dongjoon-hyun commented on a diff in the pull request:
https://github.com/apache/spark/pull/13751#discussion_r67604590
--- Diff: docs/sparkr.md ---
@@ -158,20 +152,19 @@ write.df(people, path="people.parquet",
source="parquet", mode="overwrite")
### From Hive tables
-You can also create SparkR DataFrames from Hive tables. To do this we will
need to create a HiveContext which can access tables in the Hive MetaStore.
Note that Spark should have been built with [Hive
support](building-spark.html#building-with-hive-and-jdbc-support) and more
details on the difference between SQLContext and HiveContext can be found in
the [SQL programming
guide](sql-programming-guide.html#starting-point-sqlcontext).
+You can also create SparkDataFrames from Hive tables. To do this we will
need to create a SparkSession with Hive support which can access tables in the
Hive MetaStore. Note that Spark should have been built with [Hive
support](building-spark.html#building-with-hive-and-jdbc-support) and more
details can be found in the [SQL programming
guide](sql-programming-guide.html#starting-point-sqlcontext). In SparkR, by
default it will attempt to create a SparkSession with Hive support enabled
(`enableHiveSupport = TRUE`).
--- End diff --
This will eventually be broken in the following PR for the SQL Programming
Guide.
https://github.com/apache/spark/pull/13592/files#diff-d8aa7a37d17a1227cba38c99f9f22511R55
- `#starting-point-sqlcontext` -> `#starting-point-sparksession`
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