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test this please
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test this please
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Works for me. Thanks, guys!
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@cloud-fan @markhamstra They should be all fixed (handling null in
arguments and results).
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hi @markhamstra , can you add some log in your UDF, to see if the NPE
occurred before run into your UDF code or after?
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@davies The exact same UDF worked fine in 1.5.
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@markhamstra I think it's because of your UDF did not handle null correctly.
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Github user markhamstra commented on the pull request:
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Still doesn't work for me. Now it ends up in a different place, but a NPE:
```
...
2015-12-11 06:48:09,285 INFO
org.apache.spark.sql.catalyst.expression
Github user markhamstra commented on the pull request:
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@davies No -- see the other PR.
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LGTM pending tests.
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@markhamstra Once it works, I will merge this to unblock RC2.
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No problem; I'll cherry-pick another.
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@markhamstra Sorry, just pushed a commit to fix it now, added a regression
test.
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@davies This results in a slightly different failure from the one I
previously reported:
Everything looks the same as the prior post except now:
```
Github user davies commented on the pull request:
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It's not a Janino bug, `(Integer)-1` does not work in Java, faint :-(
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Github user cloud-fan commented on the pull request:
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I changed `int` to `Integer` and tried again ,the result is the same. And I
also tried `Integer i = (Integer) -1;` which also failed to compile. I think
the problem i
Github user yhuai commented on the pull request:
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Wenchen, should the type of i be Integer?
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Could you try to add `(Integer)` before `null`?
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I tried it locally, here is my findings:
* `int i = false ? null : (Integer) -1;` **doesn't compile**
* `int i = false ? null : (Integer) 1;` compiles
Github user davies commented on the pull request:
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@markhamstra Does https://github.com/apache/spark/pull/10266 fix it?
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GitHub user davies opened a pull request:
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[SPARK-12258] [SQL] passing null into ScalaUDF (follow-up)
This is a follow-up PR for #10259
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Github user cloud-fan commented on the pull request:
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hi @markhamstra , can you share you test code? so that we can reproduce it,
thanks!
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Github user markhamstra commented on the pull request:
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Sorry, but after this I am now seeing codeGen errors. Like this:
```
testTimestampArithmeticUDFs(com.clearstorydata.dataengine.udfs.TestTimestampArithmeticU
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LGTM
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LGTM pending jenkins.
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Github user yhuai commented on the pull request:
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I tried use `java.lang` types and the result look good.
@davies how about we update our doc (the `Data Types` section) to explain
that those primitive types are n
Github user gatorsmile commented on the pull request:
https://github.com/apache/spark/pull/10259#issuecomment-163794997
Ok, I see your point. This is a possible workaround. It works well when the
input values of primitive types are not null.
I am just afraid how users know th
Github user davies commented on the pull request:
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@gatorsmile Because your UDF is using primitive types, we have to chance to
pass `null` in. In order to got the behavior you expect, you should change the
UDF to use box
Github user gatorsmile commented on the pull request:
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Yeah. That is my understanding.
```
inputsNullCheck.map(If(_, Literal.create(null, udf.dataType),
udf)).getOrElse(udf)
```
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Github user yhuai commented on the pull request:
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the analyzer rule was introduced by
https://github.com/apache/spark/pull/9770 ?
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Github user gatorsmile commented on the pull request:
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Yeah. Below is the result of
```scala
sql("SELECT * FROM test").show();
```
```
+++---+++++++++
| ti|
Github user yhuai commented on the pull request:
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Does `INSERT INTO TABLE test VALUES` actually work?
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Github user gatorsmile commented on the pull request:
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Thank you @davies !
I guess we might still have a bug in the code. As long as any input
variable is Null, the return result is `null`. Is that by design?
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test this please
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GitHub user davies opened a pull request:
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[SPARK-12258] [SQL] passing null into ScalaUDF
Check nullability and passing them into ScalaUDF.
Closes #10249
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