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Github user HyukjinKwon commented on a diff in the pull request:
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--- Diff: sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala ---
@@ -1271,10 +1271,11 @@ class DataFrame private[sql](
* @since 1.6.0
Github user yinxusen commented on the pull request:
https://github.com/apache/spark/pull/10193#issuecomment-163527097
Faint! OSX's file name is not case sensitive... that's why I miss the
Element[W|w]iseProductExample.scala error.
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Github user yinxusen commented on the pull request:
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@BenFradet All clear now. Thanks!
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GitHub user markgrover opened a pull request:
https://github.com/apache/spark/pull/10248
Small doc change on how to use dynamic partitioning in Spark SQL
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/markgrover/spark spark_sql_
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Can one of the admins verify this patch?
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Github user aa8y commented on the pull request:
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@JoshRosen I've created a new pull request, #10247 with a fresh new commit
which should merge. @srowen I would really appreciate it if you could get
Jenkins to test it. Pl
Github user aa8y closed the pull request at:
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GitHub user aa8y opened a pull request:
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[SPARK-11962] Added getAsOpt functions to Row and tests for it.
getAsOpt[T] functions have been added to Row and GeneicRowWithSchema to get
the values present in a row object optionally. Corresponding
Github user maver1ck commented on the pull request:
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OK. I will add few words to documentation.
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Github user BenFradet commented on the pull request:
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Plus, there is inconsistent naming between the docs and the example file
for Element[W|w]iseProductExample.scala
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Github user asfgit closed the pull request at:
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Github user liancheng commented on the pull request:
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Thanks, merging to master.
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Github user anabranch commented on the pull request:
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@BenFradet integrated your feedback thanks.
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Github user liancheng commented on the pull request:
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@cloud-fan Could you please mention SPARK-12131 in the PR title and
description since it's also fixed in this PR? Then I can merge it to master.
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Github user BenFradet commented on the pull request:
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LGTM except one minor comment.
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Github user BenFradet commented on a diff in the pull request:
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--- Diff: docs/ml-guide.md ---
@@ -613,7 +613,49 @@ for row in selected.collect():
{% endhighlight %}
+
+
+## Example: Saving a
Github user ygcao commented on the pull request:
https://github.com/apache/spark/pull/10152#issuecomment-163517944
To see is to believe, comparison is the key. You are encouraged to use my
version(using a simple sentence splitter by dot and question mark. Btw:if your
data is not text,
Github user holdenk commented on the pull request:
https://github.com/apache/spark/pull/10194#issuecomment-163517495
Being consistent with the python datamodel is probably good, just important
not to surprise anyone whose code may have been written against the old
assumptions.
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Github user BenFradet commented on the pull request:
https://github.com/apache/spark/pull/10193#issuecomment-163517061
There is one nit in
[polynomial_expansion_example.py](https://github.com/apache/spark/blob/master/examples/src/main/python/ml/polynomial_expansion_example.py#L33)
wit
Github user andrewor14 commented on a diff in the pull request:
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Github user gatorsmile commented on the pull request:
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@cloud-fan Sure, let me open it now. Thank you!
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Github user maver1ck commented on the pull request:
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Yes.
Now, it'll be consistent with Python documentation:
https://docs.python.org/3/reference/datamodel.html
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GitHub user jerryshao opened a pull request:
https://github.com/apache/spark/pull/10246
[Streaming][Doc][Minor] Update the description of direct Kafka stream doc
With the merge of
[SPARK-8337](https://issues.apache.org/jira/browse/SPARK-8337), now the Python
API has the same functi
Github user cloud-fan commented on the pull request:
https://github.com/apache/spark/pull/10239#issuecomment-163513683
@gatorsmile , the problem is: currently kryo/javaSerialization encoder is
not composable, so it's another story, feel free to open a JIRA for it.
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Github user ygcao commented on the pull request:
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I have to say word2vec or skip gram can be absolutely affected by training
data just like any other ML algorithm. I also can tell you I observed big
differences when I a
Github user zsxwing commented on a diff in the pull request:
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--- Diff:
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@@ -197,4 +197,34 @@ class AsyncRDDActionsSuite extends SparkFunSuite with
Github user gatorsmile commented on the pull request:
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retest this please
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Github user gatorsmile commented on the pull request:
https://github.com/apache/spark/pull/10239#issuecomment-163496616
Regarding the JIRA SPARK-12131, how about the following statement?
```scala
implicit val kryoEncoder = Encoders.kryo[KryoClassData]
val ds = Seq((KryoClas
Github user liancheng commented on the pull request:
https://github.com/apache/spark/pull/10133#issuecomment-163493682
Closing this one in favor of #10239.
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Great, so the inner class issue is also resolved. I'm closing #10133 then.
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Can one of the admins verify this patch?
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GitHub user Wenpei opened a pull request:
https://github.com/apache/spark/pull/10245
[SPARK] [API DOC] rdd's aggregate function
More accurate for RDD's aggregate function, especially for zeroValue
parameter.
In old version, people may misunderstand and thought zeroValue may us
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--- Diff: core/src/main/scala/org/apache/spark/util/Utils.scala ---
@@ -331,6 +331,30 @@ private[spark] object Utils extends Logging {
}
/
Github user JoshRosen commented on the pull request:
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Jenkins, retest this please.
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}
/
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Github user vanzin commented on the pull request:
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Haven't seen any feedback so I guess people are ok with turning this into a
real PR?
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Jenkins, test this please.
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ping @jkbradley
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Jenkins, test this please.
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merging to master and 1.6
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[SPARK-12215][ML][DOC] User guide section for KMeans in spark.ml
cc @jkbradley
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