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Thanks, merging to master.
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GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/10605
[SPARK-12295] [SQL] external spilling for window functions
This PR manage the memory used by window functions (buffered rows), also
enable external spilling.
After this PR, we can run windo
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Github user nongli commented on a diff in the pull request:
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--- Diff:
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+/*
+ * Licensed to the Apache Softwar
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@@ -451,3 +457,147 @@ private[sql] class DynamicPartit
Github user feynmanliang closed the pull request at:
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@@ -451,3 +457,147 @@ private[sql] class DynamicPartit
Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/9667#issuecomment-169114349
@NarineK Apologies for the lack of response here! We've had limited review
bandwidth. I like providing this information to users. However, we have some
of it provid
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Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/9020#issuecomment-169112070
@da-steve101 I do think this should be put on hold, but I hope we can
revisit SPARK-6442 soon. Could you please keep your branch, but close this
issue for now? Thank
Github user nongli commented on a diff in the pull request:
https://github.com/apache/spark/pull/10498#discussion_r4699
--- Diff:
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---
@@ -451,3 +457,147 @@ private[sql] class DynamicPartit
Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/8618#issuecomment-169111257
@feynmanliang I don't think we'll be able to get this merged soon b/c of
limited review bandwidth, but please don't delete the branch since it's
something we'd eventua
Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/9614#issuecomment-169110930
@avulanov Thanks that makes sense.
@hhbyyh I'd agree with not creating a new optimizer every time, if this
were a public API. Is there a real need for it to b
Github user BryanCutler commented on the pull request:
https://github.com/apache/spark/pull/10598#issuecomment-169110387
thanks @vijaykiran! I marked a few things for correction and I think in
general we should extend the comments to the 100 character limit where
applicable.
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--- Diff:
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@@ -130,6 +130,34 @@ final class DataFrameWriter private[sql](df:
DataFrame)
Github user nongli commented on a diff in the pull request:
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--- Diff:
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@@ -130,6 +130,34 @@ final class DataFrameWriter private[sql](df:
DataFrame)
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Github user BryanCutler commented on a diff in the pull request:
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--- Diff: python/pyspark/mllib/classification.py ---
@@ -323,38 +330,45 @@ def train(cls, data, iterations=100,
initialWeights=None, regParam=0.01, regTy
Github user BryanCutler commented on a diff in the pull request:
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--- Diff: python/pyspark/mllib/classification.py ---
@@ -323,38 +330,45 @@ def train(cls, data, iterations=100,
initialWeights=None, regParam=0.01, regTy
Github user vanzin commented on the pull request:
https://github.com/apache/spark/pull/10582#issuecomment-169108769
Another mysterious failure with no failure (although this change should not
affect any test code - if it compiles, it's good). retest this please
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@jkbradley Thank you for your comment! I understand, I will close the issue.
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--- Diff: python/pyspark/mllib/classification.py ---
@@ -272,37 +274,42 @@ def train(cls, data, iterations=100, step=1.0,
miniBatchFraction=1.0,
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Github user jkbradley commented on the pull request:
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@acflorea I just commented on the JIRA about this: Thanks for the PR, but
we'll need to postpone work on this because of limited review bandwidth. Could
you please cl
Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/10598#discussion_r48886211
--- Diff: python/pyspark/mllib/classification.py ---
@@ -490,37 +506,45 @@ def train(cls, data, iterations=100, step=1.0,
regParam=0.01,
"""
Github user hvanhovell commented on the pull request:
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LGTM
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--- Diff: python/pyspark/mllib/classification.py ---
@@ -323,38 +330,45 @@ def train(cls, data, iterations=100,
initialWeights=None, regParam=0.01, regTy
Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/10105#issuecomment-169104918
@yinxusen I just commented on the JIRA about this, but could we please
close this issue for now? I'd like to postpone this feature due to limited
review bandwidth.
Github user vanzin commented on the pull request:
https://github.com/apache/spark/pull/10238#issuecomment-169104775
retest this please
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@HuJiayin I just commented on the JIRA about this, but could we please
close this issue for now? We won't be able to get it into MLlib soon.
However, you should defi
Github user asfgit closed the pull request at:
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--- Diff:
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@@ -87,7 +87,7 @@ class HiveSparkSubmitSuite
runSparkSubmit(
Github user JoshRosen commented on the pull request:
https://github.com/apache/spark/pull/10569#issuecomment-169099056
LGTM. I'm going to merge this now in order to avoid merge conflicts. Let's
file a followup to deal with
https://github.com/apache/spark/pull/10569#discussion-diff-488
Github user JoshRosen commented on a diff in the pull request:
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@@ -87,7 +87,7 @@ class HiveSparkSubmitSuite
runSparkSu
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--- Diff: core/src/main/scala/org/apache/spark/SparkContext.scala ---
@@ -2364,113 +2258,6 @@ object SparkContext extends Logging {
*/
privat
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--- Diff: core/src/main/scala/org/apache/spark/Aggregator.scala ---
@@ -34,10 +34,6 @@ case class Aggregator[K, V, C] (
mergeValue: (C, V) => C,
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Github user holdenk commented on the pull request:
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I've fixed the _set call ( @davies ) and simplified the branching ( @sethah
).
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@yanboliang I've added the since annotations.
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Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/10539#issuecomment-169094377
@ankurdave Maybe I should ask you: What does ```Graph.fromEdges``` require
of the given edge RDD? Is it just that identical edges need to be in the same
partition?
Github user thunterdb commented on a diff in the pull request:
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--- Diff: python/pyspark/mllib/clustering.py ---
@@ -346,7 +346,7 @@ def train(cls, rdd, k, convergenceTol=1e-3,
maxIterations=100, seed=None, initia
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@ankurdave Would you mind checking out this issue? It's really weird to
me. Here's what's happening:
* Background: PowerIterationClustering (PIC) initializes a `
Github user marmbrus commented on the pull request:
https://github.com/apache/spark/pull/10574#issuecomment-169090153
We've already pushed the docs, but any committer can update them I think :)
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ok to test
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Github user marmbrus commented on the pull request:
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This seems like a reasonable thing to do, but the implementation seems
unnecessarily complex. Why not just:
- `transform` the condition, matching on non determini
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Github user asfgit closed the pull request at:
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Jenkins, test this please.
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Thanks - I've merged this.
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I've merged this. Thank.
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/SparkOptimizer.scala ---
@@ -0,0 +1,30 @@
+/*
+ * Licensed to the Apache Software F
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Thanks, merging to master.
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Github user marmbrus commented on the pull request:
https://github.com/apache/spark/pull/10314#issuecomment-169086076
This seems like a nice convenience for the users. A few comments:
- The description / title could be improved. Some think about support
units for configuration.
Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/10570#issuecomment-169084717
@JoshRosen you might be able to help here. The Spark build passed, but the
MiMa failed due to a compilation error. The change that tripped this uses an
API call in `comm
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/10154#issuecomment-169084460
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Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/10348#discussion_r48875105
--- Diff: R/pkg/R/DataFrame.R ---
@@ -661,6 +661,34 @@ setMethod("saveAsParquetFile",
write.parquet(x, path)
})
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/10573#issuecomment-169083412
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Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/9858#discussion_r48874115
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala ---
@@ -361,8 +361,15 @@ private[sql] abstract class SparkStrategies e
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/10582#issuecomment-169082252
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Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/9858#discussion_r48873698
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala ---
@@ -361,8 +361,15 @@ private[sql] abstract class SparkStrategies e
Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/9589#discussion_r48873452
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/client/ClientWrapper.scala ---
@@ -151,29 +152,34 @@ private[hive] class ClientWrapper(
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/8909#issuecomment-169077537
@Neuw84 Since 1.6, each SQLContext will have separated session, you should
share the same SQLContext in this case (using SQLContext.getOrCreate()).
---
If your project i
Github user marmbrus commented on the pull request:
https://github.com/apache/spark/pull/10577#issuecomment-169077567
> Will add the new Dataframe and Dataset APIs for unionAll, if my
understanding is correct.
You don't need to add any new APIs, just call the optimizer rule di
Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/10577#discussion_r48872458
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/planning/patterns.scala
---
@@ -169,18 +169,3 @@ object ExtractFiltersAndInnerJoins ext
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