view: stmt_db_pl_cells {
   sql_table_name: pl_cells ;;


   dimension: cell_id {
     description: "Row ID"
     type: number
     hidden: yes
     sql: ${TABLE}.cell_id ;;
     primary_key: yes
   }

   dimension: list_id {
     description: "Joins to the pl_storelist"
     type: number
     hidden: yes
     sql: ${TABLE}.list_id ;;
   }

  dimension_group: date {
    view_label: "Date"
    label: "Activity"
    type: time
    timeframes: [month, quarter, year]
    convert_tz: no
    sql: ${TABLE}.activity_date ;;
    description: "Period of the report"
  }

   measure: status {
    view_label: "PL"
    description: "Current status of the report"
     type: string
     sql: ${TABLE}.status ;;
   }

}

# view: stmt_db_pl_cells {
#   # 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} ;;
#   }
# }