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authorlewuathe <lewuathe@me.com>2014-11-30 17:18:50 -0800
committerJosh Rosen <joshrosen@databricks.com>2014-11-30 17:19:10 -0800
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tree031b4251ec91f25a28581d768308652fb62c84f6 /docs
parentd3247284d6a5e0009c917185ade866c9d06a5b37 (diff)
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[SPARK-4656][Doc] Typo in Programming Guide markdown
Grammatical error in Programming Guide document Author: lewuathe <lewuathe@me.com> Closes #3412 from Lewuathe/typo-programming-guide and squashes the following commits: a3e2f00 [lewuathe] Typo in Programming Guide markdown (cherry picked from commit a217ec5fd5cd7addc69e538d6ec6dd64956cc8ed) Signed-off-by: Josh Rosen <joshrosen@databricks.com>
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diff --git a/docs/programming-guide.md b/docs/programming-guide.md
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@@ -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