diff --git a/docs/programming-guide.md b/docs/programming-guide.md
index 49f319ba775e5..c64637eba64fc 100644
--- a/docs/programming-guide.md
+++ b/docs/programming-guide.md
@@ -1177,7 +1177,7 @@ Accumulators are variables that are only "added" to through an associative opera
 therefore be efficiently supported in parallel. They can be used to implement counters (as in
 MapReduce) or sums. Spark natively supports accumulators of numeric types, and programmers
 can add support for new types. If accumulators are created with a name, they will be
-displayed in Spark's UI. This can can be useful for understanding the progress of 
+displayed in Spark's UI. This can be useful for understanding the progress of 
 running stages (NOTE: this is not yet supported in Python).
 
 An accumulator is created from an initial value `v` by calling `SparkContext.accumulator(v)`. Tasks