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[SPARK-23614][SQL] Fix incorrect reuse exchange when caching is used
## What changes were proposed in this pull request?
We should provide customized canonicalize plan for `InMemoryRelation`
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retest this please
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@rxin, checking empty is likely to be a common process in every ETL batch
job. I think it is the right place to provide that functionality. When a basic
function is missing already supposed to be p
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BTW, I double checked it produces the stack trace fine by manually changing
some tests locally.
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val metadata
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@ueshin and @BryanCutler, could you take a look when you are available?
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[SPARK-23691][PYTHON] Use sql_conf util in PySpark tests where possible
## What changes were proposed in this pull request?
https://github.com/apache/spark/commit/d6632d185e147fcbe6724
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So why this PR still open ?
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Merged to master and branch-2.3.
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ok to test
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But I haven't benchmark. Maybe it do not worth to do codegen for
treeAggregate.
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@viirya Yes. `treeAggregate` should only apply to global aggregate.
But in this PR the API have to use `seqOp`/`combOp`.
What I expect is that the dataframe version treeAggregate can expl
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org.apache.spark.sql
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Can one of the admins verify this patch?
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[SPARK-23690] [ML] Add handleinvalid to VectorAssembler
## What changes were proposed in this pull request?
Introduce `handleInvalid` parameter in `VectorAssembler` that can take in
`"keep
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@WeichenXu123 I feel `groupBy` is more SQL-like aggregation by which we can
specify a key to grouping by. At least `rdd.treeAggregate` does not support
key-specified aggregation.
For typed g
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Or .. should it be `SPARK-23683`? I just saw you opened a JIRA.
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/**
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Hey @steveloughran, can you fix the title to like
`[SPARK-20236][SQL][FOLLOW-UP] ... ` BTW?
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@tdas @zsxwing
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Github user MrBago commented on the issue:
https://github.com/apache/spark/pull/19108
Thanks for the changes Weichen, this lgtm.
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Github user AmplabJenkins commented on the issue:
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Can one of the admins verify this patch?
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GitHub user jose-torres opened a pull request:
https://github.com/apache/spark/pull/20828
[SPARK-23687][SS] Add a memory source for continuous processing.
## What changes were proposed in this pull request?
Add a memory source for continuous processing.
Note that on
Github user AmplabJenkins commented on the issue:
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Github user AmplabJenkins commented on the issue:
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Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/20686
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Github user WeichenXu123 commented on the issue:
https://github.com/apache/spark/pull/20806
The API seems not dataframe style. What I expect is something like:
```
dataset.groupBy().setAggregateLevel(2).agg(Map("age" -> "max", "salary" ->
"avg"))
```
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Github user jkbradley commented on the issue:
https://github.com/apache/spark/pull/20686
Merging to branch-2.3 too
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