[GitHub] spark issue #22419: [SPARK-23906][SQL] Add built-in UDF TRUNCATE(number)

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2018-09-26 Thread wangyum
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retest this please


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retest this please


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[GitHub] spark issue #22419: [SPARK-23906][SQL] Add built-in UDF TRUNCATE(number)

2018-09-24 Thread maropu
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https://github.com/apache/spark/pull/22419#issuecomment-423454727
This approach looks good to me cuz it makes the implementation simpler. 
But, there is one thing I worry about; truncating is a kind of rounding (Is it 
ok to extend `RoundBase` for `Truncate`)? This is just a naming issue of 
`RoundBase` though. cc: @gatorsmile 


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retest this please


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[GitHub] spark issue #22419: [SPARK-23906][SQL] Add built-in UDF TRUNCATE(number)

2018-09-21 Thread wangyum
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retest this please


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2018-09-21 Thread wangyum
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@ueshin Thanks a lot! 


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[GitHub] spark issue #22419: [SPARK-23906][SQL] Add built-in UDF TRUNCATE(number)

2018-09-21 Thread ueshin
Github user ueshin commented on the issue:

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On second thoughts, I'm wondering whether we can reuse `RoundBase`?
I mean:

```scala
case class Truncate(child: Expression, scale: Expression)
  extends RoundBase(child, scale, BigDecimal.RoundingMode.DOWN, 
"ROUND_DOWN")
with Serializable with ImplicitCastInputTypes {
  def this(child: Expression) = this(child, Literal(0))
}
```

If we want to round negative values towards negative infinity instead of 
towards zero, we should use `RoundingMode.FLOOR` instead of `DOWN`, thought.

Btw, could you add test cases for negative value child as well?


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