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test_orders_extended_new_name.view.lkml
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include: "*.view.lkml"
view: orders_extended {
# extends: [orders]
dimension: id {
}
measure: sum_of_somethings {
type: sum
sql: ${id} ;;
}
measure: avg_of_things {
type: average
sql: ${id} ;;
}
# view: orders_extended {
# # You can specify the table name if it's different from the view name:
# sql_table_name: my_schema_name.tester ;;
#
# # Define your dimensions and measures here, like this:
# dimension: user_id {
# description: "Unique ID for each user that has ordered"
# type: number
# sql: ${TABLE}.user_id ;;
# }
#
# dimension: lifetime_orders {
# description: "The total number of orders for each user"
# type: number
# sql: ${TABLE}.lifetime_orders ;;
# }
#
# dimension_group: most_recent_purchase {
# description: "The date when each user last ordered"
# type: time
# timeframes: [date, week, month, year]
# sql: ${TABLE}.most_recent_purchase_at ;;
# }
#
# measure: total_lifetime_orders {
# description: "Use this for counting lifetime orders across many users"
# type: sum
# sql: ${lifetime_orders} ;;
# }
}
# view: orders_extended {
# # Or, you could make this view a derived table, like this:
# derived_table: {
# sql: SELECT
# user_id as user_id
# , COUNT(*) as lifetime_orders
# , MAX(orders.created_at) as most_recent_purchase_at
# FROM orders
# GROUP BY user_id
# ;;
# }
#
# # Define your dimensions and measures here, like this:
# dimension: user_id {
# description: "Unique ID for each user that has ordered"
# type: number
# sql: ${TABLE}.user_id ;;
# }
#
# dimension: lifetime_orders {
# description: "The total number of orders for each user"
# type: number
# sql: ${TABLE}.lifetime_orders ;;
# }
#
# dimension_group: most_recent_purchase {
# description: "The date when each user last ordered"
# type: time
# timeframes: [date, week, month, year]
# sql: ${TABLE}.most_recent_purchase_at ;;
# }
#
# measure: total_lifetime_orders {
# description: "Use this for counting lifetime orders across many users"
# type: sum
# sql: ${lifetime_orders} ;;
# }
# }