alamb commented on code in PR #14271:
URL: https://github.com/apache/datafusion/pull/14271#discussion_r1929720287
##########
datafusion/expr/src/udaf.rs:
##########
@@ -39,6 +39,26 @@ use crate::utils::AggregateOrderSensitivity;
use crate::{Accumulator, Expr};
use crate::{Documentation, Signature};
+/// Status of an Aggregate Expression's Monotonicity
+#[derive(Debug, Clone)]
+pub enum AggregateExprMonotonicity {
Review Comment:
Instead of a new structure, did you consider `SortProperties` (which I
think @berkaysynnada added) that also reflects the idea of monotonicity?
I am thinking of this in particular:
https://docs.rs/datafusion/latest/datafusion/logical_expr/sort_properties/enum.SortProperties.html
https://github.com/apache/datafusion/blob/95d296cd5aa1c58baf18e7625afe50f2e8989b07/datafusion/expr-common/src/sort_properties.rs#L37-L36
In addition to being an existing pattern, the `SortProperties` structure
also can represent the difference between `ASC NULLS FIRST` and `ASC NULLS
LAST` which this structure does not seem to do
##########
datafusion/sqllogictest/test_files/aggregate.slt:
##########
@@ -4963,6 +4963,9 @@ false
true
NULL
+statement ok
Review Comment:
In order that the tests better explain the implications of this change, can
you please add a new test rather than updating the existing test (by setting
this option).
So that would mean set the flag and run the EXPLAIN again in a separate block
That will let the tests better illustrate any change in behavior
##########
datafusion/sqllogictest/test_files/aggregates_topk.slt:
##########
@@ -143,13 +143,12 @@ logical_plan
03)----TableScan: traces projection=[trace_id, timestamp]
physical_plan
01)SortPreservingMergeExec: [max(traces.timestamp)@1 ASC NULLS LAST], fetch=4
-02)--SortExec: TopK(fetch=4), expr=[max(traces.timestamp)@1 ASC NULLS LAST],
preserve_partitioning=[true]
-03)----AggregateExec: mode=FinalPartitioned, gby=[trace_id@0 as trace_id],
aggr=[max(traces.timestamp)]
-04)------CoalesceBatchesExec: target_batch_size=8192
-05)--------RepartitionExec: partitioning=Hash([trace_id@0], 4),
input_partitions=4
-06)----------RepartitionExec: partitioning=RoundRobinBatch(4),
input_partitions=1
-07)------------AggregateExec: mode=Partial, gby=[trace_id@0 as trace_id],
aggr=[max(traces.timestamp)]
-08)--------------MemoryExec: partitions=1, partition_sizes=[1]
+02)--AggregateExec: mode=FinalPartitioned, gby=[trace_id@0 as trace_id],
aggr=[max(traces.timestamp)]
Review Comment:
This plan doesn't look correct to me
Avioding the sort requires that the output of `AggregateExec:
mode=FinalPartitioned, gby=[trace_id@0 as trace_id],
aggr=[max(traces.timestamp)]` is sorted on `max(timestamp)` but that is only
true if there is a single group (aka a single value of `trace_id`) 🤔
##########
datafusion/sqllogictest/test_files/aggregate.slt:
##########
@@ -4978,17 +4981,19 @@ logical_plan
physical_plan
01)GlobalLimitExec: skip=0, fetch=5
02)--CoalescePartitionsExec
-03)----AggregateExec: mode=FinalPartitioned, gby=[c3@0 as c3,
min(aggregate_test_100.c1)@1 as min(aggregate_test_100.c1)], aggr=[], lim=[5]
+03)----AggregateExec: mode=FinalPartitioned, gby=[c3@0 as c3,
min(aggregate_test_100.c1)@1 as min(aggregate_test_100.c1)], aggr=[],
ordering_mode=PartiallySorted([1])
04)------CoalesceBatchesExec: target_batch_size=8192
-05)--------RepartitionExec: partitioning=Hash([c3@0,
min(aggregate_test_100.c1)@1], 4), input_partitions=4
-06)----------AggregateExec: mode=Partial, gby=[c3@0 as c3,
min(aggregate_test_100.c1)@1 as min(aggregate_test_100.c1)], aggr=[], lim=[5]
+05)--------RepartitionExec: partitioning=Hash([c3@0,
min(aggregate_test_100.c1)@1], 4), input_partitions=4, preserve_order=true,
sort_exprs=min(aggregate_test_100.c1)@1 DESC NULLS LAST
+06)----------AggregateExec: mode=Partial, gby=[c3@0 as c3,
min(aggregate_test_100.c1)@1 as min(aggregate_test_100.c1)], aggr=[],
ordering_mode=PartiallySorted([1])
Review Comment:
I am not sure if it is important, but the `lim=[5]` appears to have been
lost in this plan
Otherwise it looks better to me (as it uses a PartiallySorted aggregate
rather than rehashing the entire thing)
##########
datafusion/expr/src/udaf.rs:
##########
@@ -635,6 +655,14 @@ pub trait AggregateUDFImpl: Debug + Send + Sync {
fn documentation(&self) -> Option<&Documentation> {
None
}
+
+ /// Indicates whether the aggregation function is monotonic as a set
function. A set
+ /// function is monotonically increasing if its value increases as its
argument grows
+ /// (as a set). Formally, `f` is a monotonically increasing set function
if `f(S) >= f(T)`
+ /// whenever `S` is a superset of `T`.
+ fn monotonicity(&self, _data_type: &DataType) -> AggregateExprMonotonicity
{
Review Comment:
Would it be possible to follow the existing model for ScalarUDFs here
instead?
https://github.com/apache/datafusion/blob/27db82fe396f43077b5056bab4b20b084c8f6948/datafusion/expr/src/udf.rs#L753-L752
Soemthing like this:
```rust
pub trait AggregateUDFImpl {
...
/// returns the output order of this aggregate expression given the
input properites
fn output_ordering(&self, inputs: &[ExprProperties]) ->
Result<SortProperties>;
...
}
```
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