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

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]
    exclude_final_results: [SQL expression]