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Documentation Index

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Level of Detail (LoD) fields control the granularity at which an aggregation is computed. When used as a dimension, an LoD produces a categorical value — one row per level of detail — which lets you perform an additional layer of aggregation (e.g., average customer lifetime spend).
You can also create LoD fields in the workbook! In the field browser of a query tab, click the on a dimension and then Modeling > New level of detail field.

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How it works

The easiest way to understand an LoD dimension is to read it as SQL. For example, this max_age_in_country LoD finds the maximum user age within each country and attaches it to every user row: 
max_age_in_country:
  sql: ${users.age}
  level_of_detail:
    aggregate_type: max
    fixed: [country]
The fixed: [country] clause corresponds to the GROUP BY country in the inner query — one row per country, the level of detail. The join then carries that country-level value back to each user row, which is why the LoD behaves like a categorical dimension: every user in the same country shares the same max_age_in_country value.

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Syntax

<dimension_name>:
  level_of_detail:
    aggregate_type: <aggregation>
    <grouping_strategy>: [<field_name>]
    custom_primary_key_sql: <field_reference>
    cancel_query_filters: <true_false>
    filters:
      <field>:
        <filter_operator>: <value>
        cancel_query_filter: <true_false>

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Properties

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dimension_name
object
The name of the dimension. Dimension names must:
  • Be unique within the view
  • Start with a letter
  • Contain only alphanumeric characters and underscores

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Examples

Customer lifetime spend
customer_lifetime_spend:
  sql: ${sale_price}
  label: Customer Lifetime Spend
  level_of_detail:
    aggregate_type: sum
    always_include: [user_id]
    cancel_query_filters: true
Fixed level of detail
category_total:
  sql: ${revenue}
  level_of_detail:
    aggregate_type: sum
    fixed: [category]
Exclude dimensions from grouping
overall_average:
  sql: ${score}
  level_of_detail:
    aggregate_type: average
    always_exclude: [region]
Sum distinct on with custom primary key
sum_by_order:
  sql: ${order_items.amount}
  level_of_detail:
    aggregate_type: sum_distinct_on
    custom_primary_key_sql: ${order_items.order_id}
    fixed: []
Selectively ignore a specific global filter
arr_balance_by_logo:
  sql: ${test_query_view.arr_cumulative}
  level_of_detail:
    aggregate_type: max
    fixed: [logo, date]
    filters:
      date:
        cancel_query_filter: true  # Ignores global date filter for this level of detail only
Replace a cancelled filter with a different value
compare_to_california:
  sql: ${revenue}
  level_of_detail:
    aggregate_type: sum
    fixed: [state]
    filters:
      state:
        is: California  # Replaces any global state filter with California
        cancel_query_filter: true
Compare with cancel_query_filters (all-or-nothing)
customer_lifetime_spend:
  sql: ${sale_price}
  level_of_detail:
    aggregate_type: sum
    always_include: [user_id]
    cancel_query_filters: true  # Ignores all global filters