un-pdt
Change-Id: Ia53bfdfa99b4be0ff6f9cd14e712d80fe5bc55b4
diff --git a/explores/revenue_pdt_explore.view.lkml b/explores/revenue_pdt_explore.view.lkml
index d2d602f..e42960a 100644
--- a/explores/revenue_pdt_explore.view.lkml
+++ b/explores/revenue_pdt_explore.view.lkml
@@ -2,44 +2,5 @@
include: "../views/*.view.lkml"
explore: revenue_pdt_explore {
view_name: revenue_pdt
- label: "revenue_pdt_explore label bis"
+ label: "revenue_pdt_explore label ter"
}
-
-# view: revenue_pdt_explore {
-# # 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} ;;
-# }
-# }
diff --git a/views/revenue_pdt.view.lkml b/views/revenue_pdt.view.lkml
index 165617b..043e20d 100644
--- a/views/revenue_pdt.view.lkml
+++ b/views/revenue_pdt.view.lkml
@@ -9,8 +9,8 @@
format_timestamp('%F %T', current_timestamp(), 'America/Los_Angeles') pdt_time_bis
FROM gcc_internal.revenue
;;
- sql_trigger_value: SELECT EXTRACT(HOUR FROM CURRENT_TIMESTAMP());;
- publish_as_db_view: yes
+ # sql_trigger_value: SELECT EXTRACT(HOUR FROM CURRENT_TIMESTAMP());;
+ # publish_as_db_view: yes
}
#
# # Define your dimensions and measures here, like this:
