Change the argument order

processor/transformprocessor/README.md

@@ -220,24 +220,23 @@ Examples:
 
 ### extract_sum_metric
 
-> **Note** This function supports Histograms, ExponentialHistograms and Summaries
+> **Note** This function supports Histograms, ExponentialHistograms and Summaries.
 
-`extract_sum_metric(aggregation_temporality, is_monotonic)`
+`extract_sum_metric(is_monotonic, aggregation_temporality)`
 
 The `extract_sum_metric` function creates a new Sum metric from a Histogram, ExponentialHistogram or Summary's sum value.
 
-`aggregation_temporality` is an enum(`AGGREGATION_TEMPORALITY_DELTA` or `AGGREGATION_TEMPORALITY_CUMULATIVE`) representing the desired aggregation temporality of the new metric. `is_monotonic` is a boolean representing the monotonicity of the new metric.
+`is_monotonic` is a boolean representing the monotonicity of the new metric. `aggregation_temporality` is an enum(`AGGREGATION_TEMPORALITY_DELTA` or `AGGREGATION_TEMPORALITY_CUMULATIVE`) representing the desired aggregation temporality of the new metric.
 
 The name for the new metric will be `<original metric name>_sum`. The fields that are copied are: `timestamp`, `starttimestamp`, `attibutes`, and `description`. The new metric that is created will be passed to all functions in the metrics statements list.  Function conditions will apply.
 
-> **Note** This function may cause a metric to break semantics for [Sum metrics](https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/data-model.md#sums). Use at your own risk.
+> **Warning** This function may cause a metric to break semantics for [Sum metrics](https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/data-model.md#sums). Use only if you're confident you know what the resulting monotonicity and aggregation temporality should be.
 
 Examples:
 
-- `extract_sum_metric("delta", true)`
+- `extract_sum_metric(true, AGGREGATION_TEMPORALITY_DELTA)`
 
-
-- `extract_sum_metric("cumulative", false)`
+- `extract_sum_metric(false, AGGREGATION_TEMPORALITY_CUMULATIVE)`
 
 ### convert_summary_count_val_to_sum
 

processor/transformprocessor/internal/metrics/func_extract_sum_metric.go

@@ -15,8 +15,8 @@ import (
 )
 
 type extractSumMetricArguments struct {
-	AggTemp   ottl.Enum `ottlarg:"0"`
-	Monotonic bool      `ottlarg:"1"`
+	Monotonic bool      `ottlarg:"0"`
+	AggTemp   ottl.Enum `ottlarg:"1"`
 }
 
 func newExtractSumMetricFactory() ottl.Factory[ottlmetric.TransformContext] {
@@ -30,7 +30,7 @@ func createExtractSumMetricFunction(_ ottl.FunctionContext, oArgs ottl.Arguments
 		return nil, fmt.Errorf("extractSumMetricFactory args must be of type *extractSumMetricArguments")
 	}
 
-	return extractSumMetric(args.AggTemp, args.Monotonic)
+	return extractSumMetric(args.Monotonic, args.AggTemp)
 }
 
 // this interface helps unify the logic for extracting data from different histogram types
@@ -43,7 +43,7 @@ type SumCountDataPoint interface {
 	Timestamp() pcommon.Timestamp
 }
 
-func extractSumMetric(aggTempEnum ottl.Enum, monotonic bool) (ottl.ExprFunc[ottlmetric.TransformContext], error) {
+func extractSumMetric(monotonic bool, aggTempEnum ottl.Enum) (ottl.ExprFunc[ottlmetric.TransformContext], error) {
 	aggTemp := pmetric.AggregationTemporality(aggTempEnum)
 	switch aggTemp {
 	case pmetric.AggregationTemporalityDelta, pmetric.AggregationTemporalityCumulative:

processor/transformprocessor/internal/metrics/func_extract_sum_metric_test.go

@@ -408,7 +408,7 @@ func Test_extractSumMetric(t *testing.T) {
 			actualMetrics := pmetric.NewMetricSlice()
 			tt.input.CopyTo(actualMetrics.AppendEmpty())
 
-			evaluate, err := extractSumMetric(ottl.Enum(tt.temporality), tt.monotonicity)
+			evaluate, err := extractSumMetric(tt.monotonicity, ottl.Enum(tt.temporality))
 			assert.NoError(t, err)
 
 			_, err = evaluate(nil, ottlmetric.NewTransformContext(tt.input, actualMetrics, pcommon.NewInstrumentationScope(), pcommon.NewResource()))
@@ -435,7 +435,7 @@ func Test_extractSumMetric_validation(t *testing.T) {
 	}
 	for _, tt := range tests {
 		t.Run(tt.name, func(t *testing.T) {
-			_, err := extractSumMetric(tt.aggTemp, true)
+			_, err := extractSumMetric(true, tt.aggTemp)
 			assert.Error(t, err, "unknown aggregation temporality: not a real aggregation temporality")
 		})
 	}

processor/transformprocessor/internal/metrics/processor_test.go

@@ -100,7 +100,7 @@ func Test_ProcessMetrics_MetricContext(t *testing.T) {
 		want       func(pmetric.Metrics)
 	}{
 		{
-			statements: []string{`extract_sum_metric(AGGREGATION_TEMPORALITY_DELTA, true) where name == "operationB"`},
+			statements: []string{`extract_sum_metric(true, AGGREGATION_TEMPORALITY_DELTA) where name == "operationB"`},
 			want: func(td pmetric.Metrics) {
 				sumMetric := td.ResourceMetrics().At(0).ScopeMetrics().At(0).Metrics().AppendEmpty()
 				sumDp := sumMetric.SetEmptySum().DataPoints().AppendEmpty()