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could you add some tests specifically to make sure iris or some other
known/available dataset is "serialized" properly?
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cc @zsxwing
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that's good. data.table is very fast to begin with...
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High level approach LGTM
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LGTM. I'm going to merge this now. There's some followup tasks to do in
terms of refactoring some old spilling tests, but there's followup tasks for
those and we'll do
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package org.apache.spark.sql.catalys
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[SPARK-10389][SQL][1.5] support order by non-attribute grouping expression
on Aggregate
backport https://github.com/apache/spark/pull/8548 to 1.5
You can merge this pull request into a Git reposi
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From the above discussion, we can see that it's easy to get wrong, I also
+1 for close this.
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Jenkins, retest this please
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ok to test
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LGTM pending Jenkins
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add to whitelist
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[SPARK-10619] Can't sort columns on Executor Page
should pick into spark 1.5.2 also.
https://issues.apache.org/jira/browse/SPARK-10619
looks like this was broken by commit:
https
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Merged into master.
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LGTM except for the new API, cc @rxin
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@mfliu Just FYI, you can check the lint-r tests locally by running the
script `dev/lint-r`
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*/
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@cloud-fan, yep, planning to update shortly.
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Github user cloud-fan commented on the pull request:
https://github.com/apache/spark/pull/9093#issuecomment-147827220
Now what this PR did doesn't conform to the title, can you update title and
description?
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Github user zero323 commented on the pull request:
https://github.com/apache/spark/pull/9099#issuecomment-147826281
@felixcheung Here you are:
Spark 1.5.1
```
dt <- data.table::fread("flights.csv")
microbenchmark::microbenchmark(createDataFrame(sqlContext, dt),
Github user shivaram commented on the pull request:
https://github.com/apache/spark/pull/9099#issuecomment-147826194
cc @sun-rui
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