> For the complete documentation index, see [llms.txt](https://docs.zenlytic.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zenlytic.com/data-modeling/symmetric_aggregates.md).

# Symmetric Aggregates

Use distinct-key aggregates to avoid double counting when joins duplicate metric values.

Symmetric aggregates allow Zenlytic to calculate your metrics accurately even when there's a situation where the joins make that very difficult by duplicating the values to aggregate.

We could go in-depth into how we do this, but we're obviously not the first to do this, and Looker has already written the best piece of content about this [here](https://cloud.google.com/looker/docs/best-practices/understanding-symmetric-aggregates), which we strongly recommend checking out.

## Examples

You can use `distinct` aggregates to tell Zenlytic how to distinctly calculate your metric. For example, this measure is a sum, but uniquely for each `order_id`.

```yaml
- name: total_price_order_level
  field_type: measure
  type: sum_distinct
  sql_distinct_key: ${order_id}
  sql: ${price} 
```


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