diff --git a/docs/quick-start.md b/docs/quick-start.md
index 1b961fd455..a29e28faf2 100644
--- a/docs/quick-start.md
+++ b/docs/quick-start.md
@@ -40,7 +40,7 @@ RDDs have _[actions](programming-guide.html#actions)_, which return values, and
 
 {% highlight scala %}
 scala> textFile.count() // Number of items in this RDD
-res0: Long = 126
+res0: Long = 126 // May be different from yours as README.md will change over time, similar to other outputs
 
 scala> textFile.first() // First item in this RDD
 res1: String = # Apache Spark
@@ -184,10 +184,10 @@ scala> linesWithSpark.cache()
 res7: linesWithSpark.type = MapPartitionsRDD[2] at filter at <console>:27
 
 scala> linesWithSpark.count()
-res8: Long = 19
+res8: Long = 15
 
 scala> linesWithSpark.count()
-res9: Long = 19
+res9: Long = 15
 {% endhighlight %}
 
 It may seem silly to use Spark to explore and cache a 100-line text file. The interesting part is
@@ -202,10 +202,10 @@ a cluster, as described in the [programming guide](programming-guide.html#initia
 >>> linesWithSpark.cache()
 
 >>> linesWithSpark.count()
-19
+15
 
 >>> linesWithSpark.count()
-19
+15
 {% endhighlight %}
 
 It may seem silly to use Spark to explore and cache a 100-line text file. The interesting part is