[jira] [Commented] (ARROW-17601) [C++] Error when creating Expression on Decimal128 types: precision out of range

["Neal Richardson (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/ARROW-17601?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17599604#comment-17599604 ] 

Neal Richardson commented on ARROW-17601:
-----------------------------------------

Here's a reproducer just using Expressions, no dplyr:

{code}
expr <- Expression$create("multiply_checked", Expression$field_ref("col1"), Expression$field_ref("col2"))
expr

# Expression
# multiply_checked(col1, col2)

expr$type(schema(col1=decimal128(33, 4), col2=decimal128(15, 2)))

# Error: Invalid: Decimal precision out of range [1, 38]: 49
{code}

Note that the different kernels have different promotion logic. Subtraction, for example, doesn't go out of range with these types.

{code}
expr <- Expression$create("subtract_checked", Expression$field_ref("col1"), Expression$field_ref("col2"))
expr$type(schema(col1=decimal128(33, 4), col2=decimal128(15, 2)))

# Decimal128Type
# decimal128(34, 4)
{code}

> [C++] Error when creating Expression on Decimal128 types: precision out of range
> --------------------------------------------------------------------------------
>
>                 Key: ARROW-17601
>                 URL: https://issues.apache.org/jira/browse/ARROW-17601
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: C++
>            Reporter: Neal Richardson
>            Priority: Major
>
> Reproducer in R:
> {code}
> library(arrow)
> library(dplyr)
> tab <- Table$create(col1 = 1:4, col2 = 5:8)
> tab <- tab$cast(schema(col1 = decimal128(33, 4), col2 = decimal128(15, 2)))
> tab %>% mutate(col1 * col2)
> # Error: Invalid: Decimal precision out of range [1, 38]: 49
> # /Users/me/arrow/cpp/src/arrow/compute/kernels/scalar_arithmetic.cc:1078  DecimalType::Make(left_type.id(), precision, scale)
> # /Users/me/arrow/cpp/src/arrow/compute/exec/expression.cc:413  call.kernel->signature->out_type().Resolve(&kernel_context, types)
> {code}
> With integers and floats, we upcast to a wider size in some compute functions like multiplication. Should this go up to Decimal256? Or is there a better way to determine the size required?



--
This message was sent by Atlassian Jira
(v8.20.10#820010)