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@cloud-fan, I like this solution better than adding a special case in the
v2 conversion to physical plan. This explains why the Python exec nodes weren't
already in the tree! I'd much rather commit
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@gatorsmile @cloud-fan @HyukjinKwon @mgaido91 Could you please review this
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[SPARK-16281][SQL][FOLLOW-UP] Add parse_url to functions.scala
## What changes were proposed in this pull request?
Add `parse_url` function to `functions.scala`. This will allow users
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df.withColumn('mean_v',
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Yes. But we can remove the code in 2.12, and this can also fix the printing
order issue in 2.12.
I don't know why we get some reflection error in tests. It works in command
line. I will do
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I understand, you still need the extra source files in a separate tree just
for 2.11.
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`SparkILoopInterpreter.scala` and `SparkExprTyper.scala` are only on 2.11
branch. It can not be compiled in 2.12. I think it's okay to have them in 2.11
branch since they are not needed in 2.12. We
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test this please
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TestPull
## What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
## How was this patch tested?
(Please explain how
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Oh, but if there's on tree for both versions, and it has files that 2.11
needs but 2.12 can't compile, won't it fail? Not sure about the NSME error up
there, I haven't seen it.
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@viirya The reflection trick we use in
`scala.reflect.internal.util.ScalaClassLoader` doesn't work when the REPL is
called from test. Do you have any idea about it? Thanks.
```
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If it works, great! You can then remove the hacks in the POM to support
2.11 vs 2.12 code? I wonder if 2.12 will compile the other two classes found in
the 2.11 tree.
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[SPARK-25253][PYSPARK] Refactor local connection & auth code
This eliminates some duplication in the code to connect to a server on
localhost to talk directly to the jvm. Also it gives consistent
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@kiszk I have added some more details in the PR description. Thank you.
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--- Diff: docs/structured-streaming-programming-guide.md ---
@@ -2812,6 +2812,12 @@ See [Input Sources](#input-sources) and [Output
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Thanks! Merging to master.
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new DoubleRDDFunctions(rdd.map(x =>
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