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Well it's not cheating if the user doesn't need to explicitly reuse.
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--- Diff: core/src/main/scala/org/apache/spark/rdd/UnionRDD.scala ---
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var rdds: Seq[RDD[T]])
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GitHub user bomeng opened a pull request:
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[SPARK-14460] [SQL] properly handling of column name contains space
## What changes were proposed in this pull request?
Although it is not recommended, table can be created with column name
Github user yanboliang commented on the pull request:
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Jenkins, test this please.
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Github user jasonmoore2k commented on the pull request:
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@andrewor14, think it's safe to just retest? I don't think the fatal error
was because of these changes. I don't have the permissions to start a test
run.
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Github user cloud-fan commented on the pull request:
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And I think "reuse a single object" should help, as then we only need to
create one object for one partition. But it's like cheating, because RDD
doesn't reuse the ob
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retest this please
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Github user cloud-fan commented on the pull request:
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In the benchmark, for RDD, we first apply a function to turn a long into a
`Data`, then do aggregate. For Dataset, we first turn a long to a `UTFString`,
then turn th
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@vectorijk This PR looks good overall, please address my last comments.
Thanks!
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--- Diff: python/pyspark/ml/regression.py ---
@@ -934,6 +935,146 @@ def predict(self, features):
return self._call_java("predict", features)
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Jenkins, retest this please.
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Github user rxin commented on the pull request:
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The part I don't get is that even in the RDD case, we'd need to create an
object per row. This is equivalent to the "deserialization" in aggregator,
since they both just c
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org.spark-project.hive:hive-exec:1.2.1.spark2 is now on Maven Central, so
this PR is no longer WIP.
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@@ -934,6 +935,146 @@ def predict(self, features):
return self._call_java("predict", features)
Github user rxin commented on the pull request:
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if we can reuse a single object and mutate the object in place, would it be
the same speed?
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Github user skparkes commented on the pull request:
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It appears the user documentation is nicely scraped from the docstrings, so
I went ahead and expanded the docstring slightly (and added a couple
`doctest`s).
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@rxin , because aggregator needs to deserialize internal row to object
fist, then call aggregator methods.
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--- Diff: python/pyspark/ml/regression.py ---
@@ -425,6 +429,9 @@ class DecisionTreeRegressor(JavaEstimator,
HasFeaturesCol, HasLabelCol, HasPredi
Github user zhengruifeng commented on the pull request:
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@jkbradley Thanks. BTW, I have three minor PRs for DOC, and there is a
whiile since I open them. Do you mind if I cc you at those PRs and you give a
glimpse in you
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+1 @jkbradley
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labelCol="label", predictionCol="pred
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labelCol="label", predictionCol="pred
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--- Diff: python/pyspark/ml/regression.py ---
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Flaky test? The second test that is running has passed that one.
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Github user skparkes commented on the pull request:
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I updated the pull request description, but I also realize your comment
could have meant the user documentation. I'll spend a moment to see if I can
find the appropri
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Github user asfgit closed the pull request at:
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retest this please.
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Github user AmplabJenkins commented on the pull request:
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Github user jkbradley commented on the pull request:
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Merging with master
@holdenk @hhbyyh Thanks for taking a look!
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Github user SparkQA commented on the pull request:
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Github user dbtsai commented on the pull request:
https://github.com/apache/spark/pull/11242#issuecomment-207184221
LGTM. This PR dramatically improves our s3 performance at Netflix.
@andrewor14 @srowen @JoshRosen @davies @marmbrus @yhuai, any further
feedback? Thanks.
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Github user rxin commented on the pull request:
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Can you update the description to include the ways that are being expanded?
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