svn commit: r1827248 - /ignite/site/trunk/use-cases/spark/shared-memory-layer.html

[dm...@apache.org]

Author: dmagda
Date: Mon Mar 19 21:46:51 2018
New Revision: 1827248

URL: http://svn.apache.org/viewvc?rev=1827248&view=rev
Log:
Spark and Ignite page updates

Modified:
    ignite/site/trunk/use-cases/spark/shared-memory-layer.html

Modified: ignite/site/trunk/use-cases/spark/shared-memory-layer.html
URL: http://svn.apache.org/viewvc/ignite/site/trunk/use-cases/spark/shared-memory-layer.html?rev=1827248&r1=1827247&r2=1827248&view=diff
==============================================================================
--- ignite/site/trunk/use-cases/spark/shared-memory-layer.html (original)
+++ ignite/site/trunk/use-cases/spark/shared-memory-layer.html Mon Mar 19 21:46:51 2018
@@ -111,7 +111,7 @@ under the License.
                 Apache Spark DataFrame API introduced the concept of a schema to describe the data,
                 allowing Spark to manage the schema and organize the data into a tabular format.
                 To put it simply, a DataFrame is a distributed collection of data organized into named columns.
-                It is conceptually equivalent to a table in a relational database which allows Spark leveraging
+                It is conceptually equivalent to a table in a relational database which allows Spark to leverage
                 from Catalyst query optimizer. The optimizer produces much more efficient query execution plans
                 in compare to RDDs which are just collections of elements partitioned across the nodes of the cluster.
             </p>