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new 2fbed37 [MINOR][DOC] Add missing space after comma
2fbed37 is described below
commit 2fbed378bf9688cfca649de162f2f8e2582ac06d
Author: “attilapiros” <piros.attila.zs...@gmail.com>
AuthorDate: Mon Mar 25 15:22:07 2019 -0500
[MINOR][DOC] Add missing space after comma
Adding missing spaces after commas.
Closes #24205 from attilapiros/minor-doc-changes.
Authored-by: “attilapiros” <piros.attila.zs...@gmail.com>
Signed-off-by: Sean Owen <sean.o...@databricks.com>
---
docs/configuration.md | 2 +-
docs/graphx-programming-guide.md | 2 +-
docs/mllib-statistics.md | 2 +-
3 files changed, 3 insertions(+), 3 deletions(-)
diff --git a/docs/configuration.md b/docs/configuration.md
index f23dc7c..006d839 100644
--- a/docs/configuration.md
+++ b/docs/configuration.md
@@ -2296,7 +2296,7 @@ In some cases, you may want to avoid hard-coding certain
configurations in a `Sp
instance, Spark allows you to simply create an empty conf and set spark/spark
hadoop properties.
{% highlight scala %}
-val conf = new SparkConf().set("spark.hadoop.abc.def","xyz")
+val conf = new SparkConf().set("spark.hadoop.abc.def", "xyz")
val sc = new SparkContext(conf)
{% endhighlight %}
diff --git a/docs/graphx-programming-guide.md b/docs/graphx-programming-guide.md
index 6a0be7b..3badb0a 100644
--- a/docs/graphx-programming-guide.md
+++ b/docs/graphx-programming-guide.md
@@ -317,7 +317,7 @@ class Graph[VD, ED] {
// Iterative graph-parallel computation
==========================================================
def pregel[A](initialMsg: A, maxIterations: Int, activeDirection:
EdgeDirection)(
vprog: (VertexId, VD, A) => VD,
- sendMsg: EdgeTriplet[VD, ED] => Iterator[(VertexId,A)],
+ sendMsg: EdgeTriplet[VD, ED] => Iterator[(VertexId, A)],
mergeMsg: (A, A) => A)
: Graph[VD, ED]
// Basic graph algorithms
========================================================================
diff --git a/docs/mllib-statistics.md b/docs/mllib-statistics.md
index c29400a..6bf013f 100644
--- a/docs/mllib-statistics.md
+++ b/docs/mllib-statistics.md
@@ -239,7 +239,7 @@ Refer to the [`Statistics` Python
docs](api/python/pyspark.mllib.html#pyspark.ml
### Streaming Significance Testing
`spark.mllib` provides online implementations of some tests to support use
cases
like A/B testing. These tests may be performed on a Spark Streaming
-`DStream[(Boolean,Double)]` where the first element of each tuple
+`DStream[(Boolean, Double)]` where the first element of each tuple
indicates control group (`false`) or treatment group (`true`) and the
second element is the value of an observation.
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