hanahmily commented on code in PR #957:
URL:
https://github.com/apache/skywalking-banyandb/pull/957#discussion_r2753000712
##########
pkg/query/aggregation/aggregation.go:
##########
@@ -36,6 +36,15 @@ type Func[N Number] interface {
In(N)
Review Comment:
```suggestion
In(...N)
```
##########
pkg/query/aggregation/aggregation.go:
##########
@@ -36,6 +36,15 @@ type Func[N Number] interface {
In(N)
Val() N
Reset()
+ // Sum returns the sum of values for distributed mean aggregation.
+ Sum() N
+ // Count returns the count of values for distributed mean aggregation.
+ Count() N
+}
+
+// DistributedMean is an interface that identifies distributed mean
aggregation functions.
+type DistributedMean interface {
+ IsDistributedMean() bool
}
Review Comment:
```suggestion
```
##########
pkg/query/aggregation/aggregation.go:
##########
@@ -36,6 +36,15 @@ type Func[N Number] interface {
In(N)
Val() N
Reset()
+ // Sum returns the sum of values for distributed mean aggregation.
+ Sum() N
+ // Count returns the count of values for distributed mean aggregation.
+ Count() N
Review Comment:
```suggestion
```
##########
pkg/query/aggregation/aggregation.go:
##########
@@ -64,6 +73,19 @@ func NewFunc[N Number](af modelv1.AggregationFunction)
(Func[N], error) {
return result, nil
}
+// NewDistributedMeanFunc returns a distributed mean aggregation function that
returns sum and count instead of mean.
+func NewDistributedMeanFunc[N Number]() Func[N] {
+ return &distributedMeanFunc[N]{zero: zero[N]()}
+}
+
+// IsDistributedMean checks if the aggregation function is a distributed mean
function.
+func IsDistributedMean[N Number](f Func[N]) bool {
+ if dm, ok := f.(DistributedMean); ok {
+ return dm.IsDistributedMean()
+ }
+ return false
+}
+
Review Comment:
```suggestion
```
##########
pkg/query/aggregation/function.go:
##########
@@ -115,3 +147,45 @@ func (m minFunc[N]) Val() N {
func (m *minFunc[N]) Reset() {
m.val = m.max
}
+
+func (m *minFunc[N]) Sum() N {
+ return m.max
+}
+
+func (m *minFunc[N]) Count() N {
+ return m.max
+}
+
+// distributedMeanFunc is used for distributed mean aggregation, returning sum
and count instead of mean.
+type distributedMeanFunc[N Number] struct {
+ sum N
+ count N
+ zero N
+}
+
+func (m *distributedMeanFunc[N]) In(val N) {
+ m.sum += val
+ m.count++
Review Comment:
```suggestion
func (m *distributedMeanFunc[N]) In(vals ...N) {
if len(vals) != 2 {
panic("expected 2 values for distributed mean")
}
m.sum += vals[0]
m.count += vals[1]
```
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