Github user jaceklaskowski commented on a diff in the pull request:
https://github.com/apache/spark/pull/12569#discussion_r60577867
--- Diff: docs/programming-guide.md ---
@@ -1328,12 +1328,18 @@ value of the broadcast variable (e.g. if the
variable is shipped to a new node l
Accumulators are variables that are only "added" to through an associative
and commutative operation and can
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
+can add support for new types.
+
+If accumulators are created with a name, they will be
displayed in Spark's UI. This can be useful for understanding the progress
of
running stages (NOTE: this is not yet supported in Python).
+<p style="text-align: center;">
--- End diff --
I copied it from another file
https://github.com/apache/spark/blob/master/docs/cluster-overview.md as I
didn't know how to include images.
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