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authorAndy Konwinski <andykonwinski@gmail.com>2014-11-17 11:52:23 -0800
committerMichael Armbrust <michael@databricks.com>2014-11-17 11:53:13 -0800
commit202627fda6a48453c3ba853cf1361ef84ba47c63 (patch)
treeb41fa70e50389cbbf9c5976d5f868e7efd5cd281 /docs
parent84cc0a20978dedc0dcff62e1b48a4aabc0792787 (diff)
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[DOCS][SQL] Fix broken link to Row class scaladoc
Author: Andy Konwinski <andykonwinski@gmail.com> Closes #3323 from andyk/patch-2 and squashes the following commits: 4699fdc [Andy Konwinski] Fix broken link to Row class scaladoc (cherry picked from commit cec1116b4b80c36b36a8a13338b948e4d6ade377) Signed-off-by: Michael Armbrust <michael@databricks.com>
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-rw-r--r--docs/sql-programming-guide.md2
1 files changed, 1 insertions, 1 deletions
diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md
index 48e8267ac0..5500da83b2 100644
--- a/docs/sql-programming-guide.md
+++ b/docs/sql-programming-guide.md
@@ -14,7 +14,7 @@ title: Spark SQL Programming Guide
Spark SQL allows relational queries expressed in SQL, HiveQL, or Scala to be executed using
Spark. At the core of this component is a new type of RDD,
[SchemaRDD](api/scala/index.html#org.apache.spark.sql.SchemaRDD). SchemaRDDs are composed of
-[Row](api/scala/index.html#org.apache.spark.sql.catalyst.expressions.Row) objects, along with
+[Row](api/scala/index.html#org.apache.spark.sql.package@Row:org.apache.spark.sql.catalyst.expressions.Row.type) objects, along with
a schema that describes the data types of each column in the row. A SchemaRDD is similar to a table
in a traditional relational database. A SchemaRDD can be created from an existing RDD, a [Parquet](http://parquet.io)
file, a JSON dataset, or by running HiveQL against data stored in [Apache Hive](http://hive.apache.org/).