alamb commented on a change in pull request #1408:
URL: https://github.com/apache/arrow-datafusion/pull/1408#discussion_r771482976
##########
File path: datafusion/src/physical_plan/expressions/average.rs
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@@ -38,11 +40,19 @@ use super::{format_state_name, sum};
pub struct Avg {
name: String,
expr: Arc<dyn PhysicalExpr>,
+ data_type: DataType,
}
/// function return type of an average
pub fn avg_return_type(arg_type: &DataType) -> Result<DataType> {
match arg_type {
+ DataType::Decimal(precision, scale) => {
+ // in the spark, the result type is DECIMAL(min(38,precision+4),
min(38,scale+4)).
+ // ref:
https://github.com/apache/spark/blob/fcf636d9eb8d645c24be3db2d599aba2d7e2955a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Average.scala#L66
+ let new_precision = MAX_PRECISION_FOR_DECIMAL128.min(*precision +
4);
+ let new_scale = MAX_SCALE_FOR_DECIMAL128.min(*scale + 4);
+ Ok(DataType::Decimal(new_precision, new_scale))
Review comment:
Could potentially use `make_decimal_type` :
https://github.com/apache/arrow-datafusion/blob/4b454d0363b034e3ebcdf88f6add2403cd77a23b/datafusion/src/sql/utils.rs#L510
here too
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