GitHub user sun-rui opened a pull request:
https://github.com/apache/spark/pull/8794
[SPARK-10051][SPARKR] Support collecting data of StructType in DataFrame
Two points in this PR:
1.Originally thought was that a named R list is assumed to be a struct
in SerDe. But
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Github user yu-iskw commented on the pull request:
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Sure! I'll check it.
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Github user yu-iskw commented on the pull request:
https://github.com/apache/spark/pull/8689#issuecomment-140994215
@noel-smith thanks for the review.
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Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/8784
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Github user rxin commented on the pull request:
https://github.com/apache/spark/pull/8616#issuecomment-140999032
cc @davies - this looks good to me?
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Github user yu-iskw commented on the pull request:
https://github.com/apache/spark/pull/8643#issuecomment-140981031
@jkbradley thank you for the comment. Just to be sure,
`LDAModelWrapper`.`describeTopics()` should return a DataFrame and then extract
the return value from the
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Github user piskvorky commented on the pull request:
https://github.com/apache/spark/pull/3737#issuecomment-140985570
@JoshRosen how exactly does `boto` get distributed to the cluster machines?
My app is failing and it seems to be connected to the fact that all EC2
nodes have
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All right. I have rebased this PR with the master branch.
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Github user yu-iskw commented on the pull request:
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@noel-smith thank you for reviewing it.
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Github user rxin commented on the pull request:
https://github.com/apache/spark/pull/8662#issuecomment-140994101
Actually never mind - it does. This seems a lot more complicated still - we
would need to handle spilling, and then in that case it would strictly be
slower due to the
Github user rxin commented on the pull request:
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If I'm reading it correctly, this is not "appends all the rows into an
array when compute() is called for the first time, then pull and remove the
rows when compute() is
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Github user ericl commented on the pull request:
https://github.com/apache/spark/pull/7987#issuecomment-141000851
@mengxr made the requested changes. I found it simpler to keep
`numFeatures` in combination with an array of offsets instead of just the
cumulative count though.
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Github user davies commented on the pull request:
https://github.com/apache/spark/pull/8662#issuecomment-140989401
Here are some benchmark with different approaches:
```
Without fix:
Number of udfs: 0 - 0.142887830734
Number of udfs: 1 - 0.948309898376
Number of
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Can one of the admins verify this patch?
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[MINOR][DOCS] Fixes markup so code is properly formatted
* Backticks are processed properly in Spark Properties table
* Removed unnecessary spaces
* See
Github user litao-buptsse commented on the pull request:
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@scwf @liancheng Is there any plan to merge this PR to branch-1.5 recently?
I think this feature is pretty useful.
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--- Diff: python/pyspark/rdd.py ---
@@ -84,7 +84,7 @@ def portable_hash(x):
h ^= len(x)
if h == -1:
h = -2
-
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Github user yu-iskw commented on the pull request:
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@noel-smith I have merged this PR with master and have fixed them which you
reviewed. Could you check it please?
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--- Diff: python/pyspark/rdd.py ---
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h ^= len(x)
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h = -2
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--- Diff:
streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala ---
@@ -198,7 +198,7 @@ class StreamingContext private[streaming] (
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test failure is `org.apache.spark.streaming.CheckpointSuite.recovery with
invertible reduceByKeyAndWindow operation`; appears unrelated.
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Title & Description changed.
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Github user zsxwing commented on the pull request:
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LGTM except my comment about `startSite`.
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