关于“使用 LookML 建立測量指標和維度”的评价

view: order_items { sql_table_name: `cloud-training-demos.looker_ecomm.order_items` ;; drill_fields: [order_item_id] dimension: order_item_id { primary_key: yes type: number sql: ${TABLE}.id ;; } dimension_group: created { type: time timeframes: [ raw, time, date, week, month, quarter, year ] sql: ${TABLE}.created_at ;; } dimension_group: delivered { type: time timeframes: [ raw, date, week, month, quarter, year ] convert_tz: no datatype: date sql: ${TABLE}.delivered_at ;; } dimension: shipping_days { type: number sql: DATE_DIFF(${shipped_date}, ${created_date}, DAY);; } dimension: inventory_item_id { type: number # hidden: yes sql: ${TABLE}.inventory_item_id ;; } dimension: order_id { type: number sql: ${TABLE}.order_id ;; } dimension_group: returned { type: time timeframes: [ raw, time, date, week, month, quarter, year ] sql: ${TABLE}.returned_at ;; } dimension: sale_price { type: number sql: ${TABLE}.sale_price ;; } dimension_group: shipped { type: time timeframes: [ raw, date, week, month, quarter, year ] convert_tz: no datatype: date sql: ${TABLE}.shipped_at ;; } dimension: status { type: string sql: ${TABLE}.status ;; } dimension: user_id { type: number # hidden: yes sql: ${TABLE}.user_id ;; } measure: average_sale_price { type: average sql: ${sale_price} ;; drill_fields: [detail*] value_format_name: usd_0 } measure: order_item_count { type: count drill_fields: [detail*] } measure: order_count { type: count_distinct sql: ${order_id} ;; } measure: total_sales { type: sum sql: ${sale_price} ;; value_format_name: usd_0 } measure: count_distinct_orders { type: count_distinct sql: ${order_id} ;; } measure: total_revenue { type: sum sql: ${sale_price} ;; value_format_name: usd } measure: total_revenue_from_completed_orders { type: sum sql: ${sale_price} ;; filters: [status: "Complete"] value_format_name: usd } measure: total_sales_email_users { type: sum sql: ${sale_price} ;; filters: [users.traffic_source: "Email"] } measure: percentage_sales_email_source { type: number value_format_name: percent_2 sql: 1.0*${total_sales_email_users} / NULLIF(${total_sales}, 0) ;; } # ----- Sets of fields for drilling ------ set: detail { fields: [ order_item_id, users.last_name, users.id, users.first_name, inventory_items.id, inventory_items.product_name ] } }

Tiến Dũng Đ. · 评论12 months之前

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Good Handson Lab on LookML

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