From ac06a85da59db8f2654cdf6601d186348da09c01 Mon Sep 17 00:00:00 2001
From: Reynold Xin <rxin@apache.org>
Date: Wed, 25 Jun 2014 01:01:23 -0700
Subject: [PATCH] Replace doc reference to Shark with Spark SQL.

---
 docs/index.md | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/docs/index.md b/docs/index.md
index 1a4ff3dbf5..4ac0982ae5 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -6,7 +6,7 @@ title: Spark Overview
 Apache Spark is a fast and general-purpose cluster computing system.
 It provides high-level APIs in Java, Scala and Python,
 and an optimized engine that supports general execution graphs.
-It also supports a rich set of higher-level tools including [Shark](http://shark.cs.berkeley.edu) (Hive on Spark), [Spark SQL](sql-programming-guide.html) for structured data, [MLlib](mllib-guide.html) for machine learning, [GraphX](graphx-programming-guide.html) for graph processing, and [Spark Streaming](streaming-programming-guide.html).
+It also supports a rich set of higher-level tools including [Spark SQL](sql-programming-guide.html) for SQL and structured data processing, [MLlib](mllib-guide.html) for machine learning, [GraphX](graphx-programming-guide.html) for graph processing, and [Spark Streaming](streaming-programming-guide.html).
 
 # Downloading
 
@@ -109,10 +109,9 @@ options for deployment:
 **External Resources:**
 
 * [Spark Homepage](http://spark.apache.org)
-* [Shark](http://shark.cs.berkeley.edu): Apache Hive over Spark
 * [Mailing Lists](http://spark.apache.org/mailing-lists.html): ask questions about Spark here
 * [AMP Camps](http://ampcamp.berkeley.edu/): a series of training camps at UC Berkeley that featured talks and
-  exercises about Spark, Shark, Spark Streaming, Mesos, and more. [Videos](http://ampcamp.berkeley.edu/3/),
+  exercises about Spark, Spark Streaming, Mesos, and more. [Videos](http://ampcamp.berkeley.edu/3/),
   [slides](http://ampcamp.berkeley.edu/3/) and [exercises](http://ampcamp.berkeley.edu/3/exercises/) are
   available online for free.
 * [Code Examples](http://spark.apache.org/examples.html): more are also available in the `examples` subfolder of Spark ([Scala]({{site.SPARK_GITHUB_URL}}/tree/master/examples/src/main/scala/org/apache/spark/examples),
-- 
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