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authorHolden Karau <holden@pigscanfly.ca>2014-01-05 22:05:30 -0800
committerHolden Karau <holden@pigscanfly.ca>2014-01-05 22:05:30 -0800
commitd86dc74d796121b61ff43c632791c52dd49ff8ad (patch)
treeb04601ff15a651093d3a00e54c8f0e4630c72505 /docs/quick-start.md
parentdf92f1c0254dc9073c18bc7b76f8b9523ecd7cec (diff)
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diff --git a/docs/quick-start.md b/docs/quick-start.md
index 9b9261cfff..153081bdaa 100644
--- a/docs/quick-start.md
+++ b/docs/quick-start.md
@@ -12,7 +12,7 @@ See the [programming guide](scala-programming-guide.html) for a more complete re
To follow along with this guide, you only need to have successfully built Spark on one machine. Simply go into your Spark directory and run:
{% highlight bash %}
-$ sbt assembly
+$ sbt/sbt assembly
{% endhighlight %}
# Interactive Analysis with the Spark Shell
@@ -146,7 +146,7 @@ If you also wish to read data from Hadoop's HDFS, you will also need to add a de
libraryDependencies += "org.apache.hadoop" % "hadoop-client" % "<your-hdfs-version>"
{% endhighlight %}
-Finally, for sbt to work correctly, we'll need to layout `SimpleApp.scala` and `simple.sbt` according to the typical directory structure. Once that is in place, we can create a JAR package containing the application's code, then use `sbt run` to execute our program.
+Finally, for sbt to work correctly, we'll need to layout `SimpleApp.scala` and `simple.sbt` according to the typical directory structure. Once that is in place, we can create a JAR package containing the application's code, then use `sbt/sbt run` to execute our program.
{% highlight bash %}
$ find .
@@ -157,8 +157,8 @@ $ find .
./src/main/scala
./src/main/scala/SimpleApp.scala
-$ sbt package
-$ sbt run
+$ sbt/sbt package
+$ sbt/sbt run
...
Lines with a: 46, Lines with b: 23
{% endhighlight %}