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authorlewuathe <lewuathe@me.com>2014-11-30 17:18:50 -0800
committerJosh Rosen <joshrosen@databricks.com>2014-11-30 17:18:50 -0800
commita217ec5fd5cd7addc69e538d6ec6dd64956cc8ed (patch)
tree15fdfbfc256ef7f5bf75ef1f4a02b08133e24683
parentaea7a99761b00b514df2b58ca836ba0de6742a3d (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
-rw-r--r--docs/programming-guide.md2
1 files changed, 1 insertions, 1 deletions
diff --git a/docs/programming-guide.md b/docs/programming-guide.md
index c60de6e970..7a16ee8742 100644
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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