> ## Documentation Index > Fetch the complete documentation index at: https://elementary-more-explicit-webhook-instructions.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # dimension_anomalies `elementary.dimension_anomalies` The test counts rows grouped by given `dimensions` (columns/expressions). This test practically monitors the frequency of values in the configured dimension over time, and alerts on unexpected changes in the distribution. It is best to configure it on low-cardinality fields. If `timestamp_column` is configured, the distribution is collected per `time_bucket`. If not, it counts the total rows per dimension. ### Test configuration *Required configuration: `dimensions`* {/* prettier-ignore */} 
  
    tests:
      -- elementary.dimension\_anomalies:
        dimensions: sql expression
        timestamp\_column: column name
        where\_expression: sql expression
        anomaly\_sensitivity: int
        anomaly\_direction: \[both | spike | drop]
        detection\_period:
          period: \[hour | day | week | month]
          count: int
        training\_period:
          period: \[hour | day | week | month]
          count: int
        time\_bucket:
          period: \[hour | day | week | month]
          count: int
        seasonality: day\_of\_week
        detection\_delay:
          period: \[hour | day | week | month]
          count: int
        ignore\_small\_changes:
          spike\_failure\_percent\_threshold: int
          drop\_failure\_percent\_threshold: int
        anomaly\_exclude\_metrics: \[SQL expression]
```yml Models models: - name: < model name > config: elementary: timestamp_column: < timestamp column > tests: - elementary.dimension_anomalies: dimensions: < columns or sql expressions of columns > # optional - configure a where a expression to accurate the dimension monitoring where_expression: < sql expression > time_bucket: # Daily by default period: < time period > count: < number of periods > ``` ```yml Models example models: - name: login_events config: elementary: timestamp_column: "loaded_at" tests: - elementary.dimension_anomalies: dimensions: - event_type - country_name where_expression: "event_type in ('event_1', 'event_2') and country_name != 'unwanted country'" time_bucket: period: hour count: 4 # optional - use tags to run elementary tests on a dedicated run tags: ["elementary"] config: # optional - change severity severity: warn - name: users # if no timestamp is configured, elementary will monitor without time filtering tests: - elementary.dimension_anomalies: dimensions: - event_type tags: ["elementary"] ```