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[chore][processor/transform] clarify aggregate_on_attributes docs #46016

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[chore][processor/transform] clarify aggregate_on_attributes docs #46016

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11 changes: 9 additions & 2 deletions processor/transformprocessor/README.md
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Expand Up @@ -535,9 +535,15 @@ Examples:

`aggregate_on_attributes(function, Optional[attributes])`

The `aggregate_on_attributes` function aggregates all datapoints in the metric based on the supplied attributes. `function` is a case-sensitive string that represents the aggregation function and `attributes` is an optional list of attribute keys of type string to aggregate upon.
The `aggregate_on_attributes` function aggregates all data points in the metric.

`aggregate_on_attributes` function removes all attributes that are present in datapoints except the ones that are specified in the `attributes` parameter. If `attributes` parameter is not set, all attributes are removed from datapoints. Afterwards all datapoints are aggregated depending on the attributes left (none or the ones present in the list).
`function` is a case-sensitive string that represents the aggregation function to apply. `attributes` is an optional list of datapoint attribute keys (strings) to aggregate upon.

The optional `attributes` argument controls which datapoint attributes are kept before aggregation:

- omitted (`aggregate_on_attributes(function)`): all existing data point attributes are kept. Aggregation only combines data points that already share the same full attribute set.
- `[]` (empty list): all datapoint attributes are removed. Aggregation is performed across all data points in the metric.
- `[...]` (list of attribute keys): only the specified data point attributes are kept. All other attributes are removed, and aggregation is performed by grouping on the remaining attributes.

**NOTE:** This function is supported only in `metric` context.

Expand All @@ -563,6 +569,7 @@ Examples:

- `aggregate_on_attributes("sum", ["attr1", "attr2"]) where metric.name == "system.memory.usage"`
- `aggregate_on_attributes("max") where metric.name == "system.memory.usage"`
- `aggregate_on_attributes("max", []) where metric.name == "system.memory.usage"`

The `aggregate_on_attributes` function can also be used in conjunction with
[keep_matching_keys](https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/pkg/ottl/ottlfuncs#keep_matching_keys) or
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