mustafasrepo commented on code in PR #10651:
URL: https://github.com/apache/datafusion/pull/10651#discussion_r1622006126
##########
datafusion/physical-expr-common/src/aggregate/mod.rs:
##########
@@ -292,16 +307,38 @@ impl AggregateExpr for AggregateFunctionExpr {
is_distinct: self.is_distinct,
input_type: &self.input_type,
args_num: self.args.len(),
+ name: &self.name,
};
self.fun.groups_accumulator_supported(args)
}
fn create_groups_accumulator(&self) -> Result<Box<dyn GroupsAccumulator>> {
- self.fun.create_groups_accumulator()
+ let args = AccumulatorArgs {
+ data_type: &self.data_type,
+ schema: &self.schema,
+ ignore_nulls: self.ignore_nulls,
+ sort_exprs: &self.sort_exprs,
+ is_distinct: self.is_distinct,
+ input_type: &self.input_type,
+ args_num: self.args.len(),
+ name: &self.name,
+ };
+ self.fun.create_groups_accumulator(args)
}
fn order_bys(&self) -> Option<&[PhysicalSortExpr]> {
- (!self.ordering_req.is_empty()).then_some(&self.ordering_req)
+ if self.fun.has_ordering_requirements() &&
!self.ordering_req.is_empty() {
+ return Some(&self.ordering_req);
+ }
+ None
Review Comment:
For some data types, order of the operation may effect the results. Hence, I
think, we shouldn't ignore the requirement given by the user. For instance, for
floating point type, `sum` will produce different results for different
permutations of the input.
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