pacing.json

{
  "script":{
    "released":"2018-01-12",
    "copyright":"Copyright 2020 Google LLC",
    "icon":"directions_run",
    "title":"DV360 Pacing",
    "description":"Pace the spend of DV360 campaigns to hit targets.",
    "redo":"https://team.git.corp.google.com/cse-dclk/whiterun/+/refs/heads/master/src/dag/bestbuy.py",
    "from":["dv360", "sheets"],
    "to":["bigquery", "datastudio"],
    "pitches":[
      "Optimize spend to prevent under spend.",
      "Optimize spend to prevent over spend.",
      "Allow client traders to enter budgets.",
      "Allow client traders to categorize spend."
    ],
    "impacts":{
      "spend optimization":100,
      "spend growth":80,
      "time savings":60,
      "account health":80,
      "csat improvement":90
    },
    "instructions":[
      "Provide a TRIX URL, we'll add new sheets with instructions.",
      "Wait for the pacing tables to be createdin the **{field:dataset}** dataset.",
      "Copy and connect each datastudio source to it's respective table...",
      "Copy [Pacing Template LI Breakdown](https://datastudio.google.com/open/0BxNSN-sP1UmzUzdobUhITUxKY0E).",
      "Copy [Pacing Template Advertiser Spend Rollup](https://datastudio.google.com/open/0BxNSN-sP1UmzWjU4ckl3ZUZrZE0).",
      "Copy [Pacing Template Pacing Impressions](https://datastudio.google.com/open/0BxNSN-sP1UmzcEFzVEw3ZnM0WVk).",
      "Copy [Pacing Template Pacing Datasource](https://datastudio.google.com/open/0BxNSN-sP1Umzd1BRVjV4QVFLd2M).",
      "After the above datasets are set up...",
      "Copy [Pacing Sample Report](https://datastudio.google.com/open/0BxNSN-sP1UmzMk5lVlVjR29KdFk).",
      "Select the data sources you created in the steps above.",
      "Or give these intructions to the client."
    ],
    "authors":["mauriciod@google.com"]
  },
  "setup":{
    "day":["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"],
    "hour":[2, 6, 8, 12]
  },
  "tasks":[
    { "dataset":{
      "hour":[2],
      "auth":{"field":{ "name":"auth_write", "kind":"authentication", "order":1, "default":"service", "description":"Credentials used for writing data." }},
      "dataset":{"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }}
    }},
    { "entity":{
      "hour":[2, 8],
      "auth":{"field":{ "name":"auth_read", "kind":"authentication", "order":1, "default":"user", "description":"Credentials used for reading data." }},
      "accounts": {"field":{ "name":"dbm_accounts", "kind":"integer_list", "order":2, "description":"Comma seperated list of DV360 partner ids." }},
      "entities": ["LineItem", "InsertionOrder", "Advertiser"],
      "out": {
        "bigquery":{
          "auth":{"field":{ "name":"auth_write", "kind":"authentication", "order":1, "default":"service", "description":"Credentials used for writing data." }},
          "dataset": {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }}
        }
      }
    }},
    { "dbm": {
      "hour":[2],
      "auth": "user",
      "delete":true,
      "report": {
        "name":{"field":{ "name":"dataset", "kind":"string", "prefix":"Pacing_" }},
        "timezone":{"field":{ "name":"timezone", "kind":"timezone", "prefix":"Pacing_" }},
        "type":"TYPE_CROSS_PARTNER",
        "data_range":"LAST_365_DAYS",
        "accounts":{"field":{ "name":"dbm_accounts", "kind":"integer_list", "order":2, "description":"Comma seperated list of DV360 partner ids." }},
        "dimensions":[
          "FILTER_DATE",
          "FILTER_PARTNER",
          "FILTER_ADVERTISER",
          "FILTER_INSERTION_ORDER",
          "FILTER_LINE_ITEM"
        ],
        "metrics": [
          "METRIC_TOTAL_MEDIA_COST_ADVERTISER",
          "METRIC_REVENUE_ADVERTISER",
          "METRIC_IMPRESSIONS",
          "METRIC_CLICKS"
        ]
      }
    }},
    { "dbm": {
      "hour":[6, 12],
      "auth": "user",
      "report": {
        "name":{"field":{ "name":"dataset", "kind":"string", "prefix":"Pacing_" }}
      },
      "out": {
        "bigquery": {
          "dataset":{"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          "table": "Pacing_Spend_Report",
          "schema":[
            { "name":"Report_Day", "type":"STRING" },
            { "name":"Partner", "type":"STRING" },
            { "name":"Partner_ID", "type":"INTEGER" },
            { "name":"Partner_Status", "type":"STRING", "mode":"NULLABLE" },
            { "name":"Advertiser", "type":"STRING" },
            { "name":"Advertiser_ID", "type":"INTEGER" },
            { "name":"Advertiser_Status", "type":"STRING", "mode":"NULLABLE" },
            { "name":"Advertiser_Integration_Code", "type":"STRING", "mode":"NULLABLE" },
            { "name":"Insertion_Order", "type":"STRING" },
            { "name":"Insertion_Order_ID", "type":"INTEGER" },
            { "name":"Insertion_Order_Status", "type":"STRING", "mode":"NULLABLE" },
            { "name":"Insertion_Order_Integration_Code", "type":"STRING", "mode":"NULLABLE" },
            { "name":"Line_Item", "type":"STRING", "mode":"NULLABLE" },
            { "name":"Line_Item_ID", "type":"INTEGER", "mode":"NULLABLE" },
            { "name":"Line_Item_Status", "type":"STRING", "mode":"NULLABLE" },
            { "name":"Line_Item_Integration_Code", "type":"STRING", "mode":"NULLABLE" },
            { "name":"Targeted_Data_Providers", "type":"STRING", "mode":"NULLABLE" },
            { "name":"Advertiser_Currency", "type":"STRING" },
            { "name":"Cost",  "type":"FLOAT" },
            { "name":"Revenue",  "type":"FLOAT" },
            { "name":"Impressions", "type":"INTEGER" },
            { "name":"Clicks", "type":"INTEGER" }
          ]
        }
      }
    }},
    { "sheets":{
      "hour":[6, 12],
      "auth":{"field":{ "name":"auth_read", "kind":"authentication", "order":1, "default":"user", "description":"Credentials used for reading data." }},
      "template":{
        "sheet":"https://docs.google.com/spreadsheets/d/1OG3_6hPCGXjcH90hxzqMWZRZ7BV40bLqONwRdKx13pg/edit?usp=sharing",
        "tab":"Pacing_Traders"
      },
      "sheet":{"field":{ "name":"sheet_url", "kind":"string", "order":4, "description":"URL for sheet storing ids." }},
      "tab":"Pacing_Traders",
      "range":"A1:C",
      "header":true,
      "out":{
        "bigquery":{
          "dataset":{"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          "table":"Pacing_Traders",
          "schema":[
            { "name":"Trader", "type":"STRING" },
            { "name":"Insertion_Order_ID", "type":"INTEGER" },
            { "name":"Insertion_Order", "type":"STRING", "mode":"NULLABLE" }
          ]
        }
      }
    }},
    { "sheets":{
      "hour":[6, 12],
      "auth":{"field":{ "name":"auth_read", "kind":"authentication", "order":1, "default":"user", "description":"Credentials used for reading data." }},
      "template":{
        "sheet":"https://docs.google.com/spreadsheets/d/1OG3_6hPCGXjcH90hxzqMWZRZ7BV40bLqONwRdKx13pg/edit?usp=sharing",
        "tab":"Pacing_Budget"
      },
      "sheet":{"field":{ "name":"sheet_url", "kind":"string", "order":4, "description":"URL for sheet storing ids." }},
      "tab":"Pacing_Budget",
      "range":"A1:F",
      "header":true,
      "out":{
        "bigquery":{
          "dataset":{"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          "table":"Pacing_Budget",
          "schema":[
            { "name":"Trader", "type":"STRING" },
            { "name":"Advertiser_ID", "type":"INTEGER" },
            { "name":"Advertiser", "type":"STRING", "mode":"NULLABLE" },
            { "name":"Budget_Quarter", "type":"FLOAT", "mode":"NULLABLE" },
            { "name":"Budget_Year", "type":"FLOAT", "mode":"NULLABLE" }
          ]
        }
      }
    }},
    { "bigquery": {
      "hour":[6, 12],
      "auth": "service",
      "to": {
        "dataset":{"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
        "table": "Pacing_Yesterday_Spend"
      },
      "from": {
        "query": "SELECT Report_Day, Partner, Advertiser, Insertion_Order, Insertion_Order_ID, Insertion_Order_Status, Insertion_Order_Integration_Code, Line_Item, Line_Item_ID, Line_Item_Status, Line_Item_Integration_Code, Targeted_Data_Providers, Advertiser_Currency, Cost, Revenue, Impressions FROM [PARAMETER].Pacing_Spend_Report WHERE Report_Day = (SELECT STRFTIME_UTC_USEC(DATE_ADD(NOW(), -1, 'DAY'), '%Y/%m/%d'))",
        "parameters":[
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }}
        ]
      }
    }},
    { "bigquery": {
      "hour":[6, 12],
      "auth": "service",
      "to": {
        "dataset":{"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
        "table": "Pacing_Pacing_View"
      },
      "from": {
        "query": "SELECT u.adv_id adv_id, u.adv_trader adv_trader, u.io_trader io_trader, u.advertiser advertiser, u.io io, u.io_id io_id, u.days_passed days_passed, u.days_left days_left, GREATEST(u.budget_left, 0) budget_left, u.spend spend, u.budget budget, u.expected_spend expected_spend, GREATEST(u.expected_spend - u.spend, 0) ammount_behind, u.previous_day_spend previous_day_spend, GREATEST(u.budget_left / u.days_left, 0) target_daily_spend, u.spend / u.days_passed avg_daily_spend, LEAST(u.previous_day_spend / GREATEST(u.budget_left / u.days_left, 1), 1) percent_daily_target, u.previous_day_spend / GREATEST(u.budget_left / u.days_left, 1) percent_daily_target_uncapped, GREATEST(LEAST(u.spend / u.expected_spend, 1), 0) pacing, GREATEST(u.spend / u.expected_spend, 0) pacing_uncapped, CASE WHEN ROUND(u.spend / u.expected_spend, 2) BETWEEN 0 AND 0.25 THEN '1(0-25%)' WHEN ROUND(u.spend / u.expected_spend, 2) BETWEEN 0.26 AND 0.5 THEN '2(26-50%)' WHEN ROUND(u.spend / u.expected_spend, 2) BETWEEN 0.51 AND 0.75 THEN '3(51-75%)' WHEN ROUND(u.spend / u.expected_spend, 2) BETWEEN 0.76 AND 1 THEN '4(76-100%)' WHEN ROUND(u.spend / u.expected_spend, 2) BETWEEN 1.01 AND 1.25 THEN '5(101-125%)' WHEN ROUND(u.spend / u.expected_spend, 2) BETWEEN 1.26 AND 1.5 THEN '6(126-150%)' WHEN ROUND(u.spend / u.expected_spend, 2) BETWEEN 1.51 AND 1.75 THEN '7(151-175%)' WHEN ROUND(u.spend / u.expected_spend, 2) BETWEEN 1.76 AND 2 THEN '8(176-200%)' WHEN ROUND(u.spend / u.expected_spend, 2) > 2 THEN '9(200%+)' ELSE 'UNKNOWN' END pacing_breakout, u.clicks clicks, u.impressions impressions, u.ctr ctr, 1 ct FROM ( SELECT COALESCE(t.adv_trader, 'Unknown') adv_trader, COALESCE(t.io_trader, 'Unknown') io_trader, t.io_id io_id, t.io io, t.start_day start_day, t.end_day end_day, t.flight_days flight_days, t.days_left days_left, t.days_left / t.flight_days flight_percent_remaining, t.adv_id adv_id, t.advertiser advertiser, COALESCE(t.previous_day_spend, 0) previous_day_spend, MAX(t.budget) budget, SUM(t.spend) spend, MAX(t.budget) / t.flight_days daily_budget, t.flight_days - t.days_left days_passed, ( MAX(t.budget) / t.flight_days ) * ( t.flight_days - t.days_left ) expected_spend, MAX(t.budget) - SUM(t.spend) budget_left, MAX(t.impressions) impressions, MAX(t.clicks) clicks, MAX(t.clicks) / MAX(t.impressions) ctr FROM ( SELECT adv_budget.trader adv_trader, trader.trader io_trader, io.common_data.id io_id, io.common_data.NAME io, io.advertiser_id adv_id, adv.common_data.NAME advertiser, STRFTIME_UTC_USEC(io.scheduled_segments.start_time_usec, '%Y/%m/%d') start_day, STRFTIME_UTC_USEC(io.scheduled_segments.end_time_usec, '%Y/%m/%d') end_day, DATEDIFF(io.scheduled_segments.end_time_usec, io.scheduled_segments.start_time_usec) flight_days, GREATEST(DATEDIFF(io.scheduled_segments.end_time_usec, GREATEST(io.scheduled_segments.start_time_usec, INTEGER(NOW()))), 0 ) days_left, ( io.scheduled_segments.max_spend_advertiser_micros / 1000000 ) budget, spend.spend spend, pd.previous_day_spend previous_day_spend, spend.impressions impressions, spend.clicks clicks FROM FLATTEN([PARAMETER].Entity_InsertionOrder, scheduled_segments) io INNER JOIN [PARAMETER].Entity_Advertiser adv ON adv.common_data.id = io.advertiser_id LEFT JOIN ( SELECT Insertion_Order_ID io_id, SUM(Revenue) previous_day_spend FROM [PARAMETER].Pacing_Yesterday_Spend GROUP BY io_id) pd ON pd.io_id = io.common_data.id LEFT JOIN ( SELECT Advertiser_ID adv_id, Trader trader FROM [[PARAMETER].Pacing_Budget]) adv_budget ON adv_budget.adv_id = adv.common_data.id LEFT JOIN ( SELECT Trader trader, Insertion_Order_ID io_id FROM [[PARAMETER].Pacing_Traders]) trader ON trader.io_id = io.common_data.id CROSS JOIN ( SELECT Report_Day date, Insertion_Order_Id io_id, SUM(Impressions) impressions, SUM(Clicks) clicks, SUM(Revenue) spend FROM [PARAMETER].Pacing_Spend_Report WHERE Insertion_Order_ID IN ( SELECT common_data.id io_id FROM FLATTEN([[PARAMETER].Entity_InsertionOrder], scheduled_segments) WHERE NOW() BETWEEN scheduled_segments.start_time_usec AND scheduled_segments.end_time_usec GROUP BY io_id) GROUP BY date, io_id) spend WHERE io.common_data.id = spend.io_id AND spend.date BETWEEN STRFTIME_UTC_USEC(io.scheduled_segments.start_time_usec, '%Y/%m/%d') AND STRFTIME_UTC_USEC(io.scheduled_segments.end_time_usec, '%Y/%m/%d') AND NOW() BETWEEN io.scheduled_segments.start_time_usec AND io.scheduled_segments.end_time_usec) t GROUP BY adv_trader, io_trader, io_id, io, start_day, end_day, flight_days, t.flight_days, days_left, t.days_left, flight_percent_remaining, adv_id, advertiser, days_passed, previous_day_spend) u WHERE u.days_left > 0",
        "parameters":[
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }}
        ]
      }
    }},
    { "bigquery": {
      "hour":[6, 12],
      "auth": "service",
      "to": {
        "dataset":{"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
        "table": "Pacing_LI_Breakdown_Foundation"
      },
      "from": {
        "query": "SELECT adv.common_data.id adv_id, adv.common_data.name adv, io.common_data.id io_id, io.common_data.name io, li_spend.li_id li_id, li_spend.li li, li_spend.spend spend, adv_budget.trader adv_trader, trader.trader io_trader FROM FLATTEN([PARAMETER].Entity_InsertionOrder, scheduled_segments) io INNER JOIN [PARAMETER].Entity_Advertiser adv ON io.advertiser_id = adv.common_data.id INNER JOIN ( SELECT Report_Day date, Insertion_Order_ID io_id, Line_Item_ID li_id, Line_Item li, FLOAT(Revenue) spend FROM [PARAMETER].Pacing_Spend_Report) li_spend ON io.common_data.id = li_spend.io_id LEFT JOIN ( SELECT Advertiser_ID adv_id, trader trader FROM [[PARAMETER].Pacing_Budget] ) adv_budget ON adv_budget.adv_id = adv.common_data.id LEFT JOIN ( SELECT Insertion_Order_ID io_id, Trader trader FROM [[PARAMETER].Pacing_Traders]) trader ON trader.io_id = io.common_data.id WHERE NOW() BETWEEN io.scheduled_segments.start_time_usec AND io.scheduled_segments.end_time_usec AND li_spend.date BETWEEN STRFTIME_UTC_USEC(io.scheduled_segments.start_time_usec, '%Y/%m/%d') AND STRFTIME_UTC_USEC(io.scheduled_segments.end_time_usec, '%Y/%m/%d')",
        "parameters":[
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }}
        ]
      }
    }},
    { "bigquery": {
      "hour":[6, 12],
      "auth": "service",
      "to": {
        "dataset":{"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
        "table": "Pacing_LI_Breakdown"
      },
      "from": {
        "query": "SELECT li_spend.adv_trader adv_trader, li_spend.io_trader io_trader, li_spend.adv_id adv_id, li_spend.adv adv, li_spend.io_id io_id, li_spend.io io, li_spend.li_id li_id, li_spend.li li, li_spend.spend li_spend, io_spend.spend io_spend, li_yesterday_spend.yesterday_spend yesterday_spend, li.budget_cap budget_cap, li.pacing_cap pacing_cap, li.pacing_type pacing_type FROM ( SELECT adv_id, adv, io_id, io, li_id, li, adv_trader, io_trader, SUM(spend) spend FROM [PARAMETER].Pacing_LI_Breakdown_Foundation GROUP BY adv_id, adv, io_id, io, li_id, li, adv_trader, io_trader) li_spend INNER JOIN ( SELECT io_id, SUM(spend) spend FROM [PARAMETER].Pacing_LI_Breakdown_Foundation GROUP BY io_id) io_spend ON io_spend.io_id = li_spend.io_id INNER JOIN ( SELECT FLOAT(Revenue) yesterday_spend, Line_Item_ID li_id FROM [[PARAMETER].Pacing_Yesterday_Spend] ) li_yesterday_spend ON li_spend.li_id = li_yesterday_spend.li_id INNER JOIN ( SELECT common_data.id li_id, budget.pacing_max_spend_advertiser_micros / 1000000 pacing_cap, CASE WHEN budget.pacing_type = 0 THEN 'ASAP' WHEN budget.pacing_type = 1 THEN 'Daily' WHEN budget.pacing_type = 2 THEN 'Monthly' END pacing_type, budget.max_spend_advertiser_micros / 1000000 budget_cap FROM [[PARAMETER].Entity_LineItem] ) li ON li.li_id = li_spend.li_id",
        "parameters":[
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }}
        ]
      }
    }},
    { "bigquery": {
      "hour":[6, 12],
      "auth": "service",
      "to": {
        "dataset":{"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
        "table": "Pacing_Adv_Rollup"
      },
      "from": {
        "query": "SELECT adv_budget.adv_id adv_id, adv_budget.adv_name adv_name, adv_budget.trader trader, quarter_info.quarter_budget quarter_budget, quarter_info.quarter_spend quarter_spend, quarter_info.quarter_spend / (quarter_info.quarter_budget * quarter_info.pct_quarter) quarter_pacing, year_info.year_spend year_spend, year_info.year_spend / (year_info.year_budget * year_info.pct_year) year_pacing, year_info.year_budget year_budget FROM ( SELECT Advertiser_ID adv_id, Advertiser adv_name, Trader trader FROM [PARAMETER].Pacing_Budget) adv_budget LEFT JOIN ( SELECT quarter_budget.adv_id adv_id, quarter_budget.quarter_budget quarter_budget, quarter_spend.quarter_spend quarter_spend, quarter_budget.pct_quarter pct_quarter FROM ( SELECT advertiser_ID adv_id, SUM(((scheduled_segments.max_spend_advertiser_micros) / 1000000) * ( DATEDIFF( USEC_TO_TIMESTAMP(LEAST( INTEGER(PARSE_UTC_USEC( CASE WHEN QUARTER(NOW()) = 1 THEN STRING(YEAR(NOW())) + '-03-31 23:59:59' WHEN QUARTER(NOW()) = 2 THEN STRING(YEAR(NOW())) + '-06-30 23:59:59' WHEN QUARTER(NOW()) = 3 THEN STRING(YEAR(NOW())) + '-09-30 23:59:59' WHEN QUARTER(NOW()) = 4 THEN STRING(YEAR(NOW())) + '-12-31 23:59:59' END)), INTEGER(scheduled_segments.end_time_usec))), USEC_TO_TIMESTAMP(GREATEST( INTEGER(PARSE_UTC_USEC( CASE WHEN QUARTER(NOW()) = 1 THEN STRING(YEAR(NOW())) + '-01-01 00:00:00' WHEN QUARTER(NOW()) = 2 THEN STRING(YEAR(NOW())) + '-04-01 00:00:00' WHEN QUARTER(NOW()) = 3 THEN STRING(YEAR(NOW())) + '-07-01 00:00:00' WHEN QUARTER(NOW()) = 4 THEN STRING(YEAR(NOW())) + '-10-01 00:00:00' END)), INTEGER(scheduled_segments.start_time_usec)) )) / DATEDIFF(scheduled_segments.end_time_usec, scheduled_segments.start_time_usec))) quarter_budget, ( DATEDIFF( NOW(), PARSE_UTC_USEC( CASE WHEN QUARTER(NOW()) = 1 THEN STRING(YEAR(NOW())) + '-01-01 00:00:00' WHEN QUARTER(NOW()) = 2 THEN STRING(YEAR(NOW())) + '-04-01 00:00:00' WHEN QUARTER(NOW()) = 3 THEN STRING(YEAR(NOW())) + '-07-01 00:00:00' WHEN QUARTER(NOW()) = 4 THEN STRING(YEAR(NOW())) + '-10-01 00:00:00' END)) / CASE WHEN QUARTER(NOW()) = 1 THEN DATEDIFF(PARSE_UTC_USEC(STRING(YEAR(NOW())) + '-03-31 23:59:59'), PARSE_UTC_USEC(STRING(YEAR(NOW())) + '-01-01 00:00:00')) WHEN QUARTER(NOW()) = 2 THEN DATEDIFF(PARSE_UTC_USEC(STRING(YEAR(NOW())) + '-06-30 23:59:59'), PARSE_UTC_USEC(STRING(YEAR(NOW())) + '-04-01 00:00:00')) WHEN QUARTER(NOW()) = 3 THEN DATEDIFF(PARSE_UTC_USEC(STRING(YEAR(NOW())) + '-09-30 23:59:59'), PARSE_UTC_USEC(STRING(YEAR(NOW())) + '-07-01 00:00:00')) WHEN QUARTER(NOW()) = 4 THEN DATEDIFF(PARSE_UTC_USEC(STRING(YEAR(NOW())) + '-12-31 23:59:59'), PARSE_UTC_USEC(STRING(YEAR(NOW())) + '-10-01 00:00:00')) END) pct_quarter FROM FLATTEN([PARAMETER].Entity_InsertionOrder, scheduled_segments) WHERE (STRFTIME_UTC_USEC(scheduled_segments.start_time_usec, '%Y%m%d') BETWEEN CASE WHEN QUARTER(NOW()) = 1 THEN STRING(YEAR(NOW())) + '0101' WHEN QUARTER(NOW()) = 2 THEN STRING(YEAR(NOW())) + '0401' WHEN QUARTER(NOW()) = 3 THEN STRING(YEAR(NOW())) + '0701' WHEN QUARTER(NOW()) = 4 THEN STRING(YEAR(NOW())) + '1001' END AND CASE WHEN QUARTER(NOW()) = 1 THEN STRING(YEAR(NOW())) + '0331' WHEN QUARTER(NOW()) = 2 THEN STRING(YEAR(NOW())) + '0630' WHEN QUARTER(NOW()) = 3 THEN STRING(YEAR(NOW())) + '0930' WHEN QUARTER(NOW()) = 4 THEN STRING(YEAR(NOW())) + '1231' END) OR (STRFTIME_UTC_USEC(scheduled_segments.end_time_usec, '%Y%m%d') BETWEEN CASE WHEN QUARTER(NOW()) = 1 THEN STRING(YEAR(NOW())) + '0101' WHEN QUARTER(NOW()) = 2 THEN STRING(YEAR(NOW())) + '0401' WHEN QUARTER(NOW()) = 3 THEN STRING(YEAR(NOW())) + '0701' WHEN QUARTER(NOW()) = 4 THEN STRING(YEAR(NOW())) + '1001' END AND CASE WHEN QUARTER(NOW()) = 1 THEN STRING(YEAR(NOW())) + '0331' WHEN QUARTER(NOW()) = 2 THEN STRING(YEAR(NOW())) + '0630' WHEN QUARTER(NOW()) = 3 THEN STRING(YEAR(NOW())) + '0930' WHEN QUARTER(NOW()) = 4 THEN STRING(YEAR(NOW())) + '1231' END) GROUP BY adv_id ) quarter_budget INNER JOIN ( SELECT SUM(FLOAT(spend.Revenue)) quarter_spend, adv.adv_id adv_id FROM [[PARAMETER].Pacing_Spend_Report] spend INNER JOIN ( SELECT common_data.id io_id, advertiser_id adv_id FROM [[PARAMETER].Entity_InsertionOrder] ) adv ON spend.Insertion_Order_ID = adv.io_id WHERE REPLACE(spend.Report_Day, '/', '') BETWEEN CASE WHEN QUARTER(NOW()) = 1 THEN STRING(YEAR(NOW())) + '0101' WHEN QUARTER(NOW()) = 2 THEN STRING(YEAR(NOW())) + '0401' WHEN QUARTER(NOW()) = 3 THEN STRING(YEAR(NOW())) + '0701' WHEN QUARTER(NOW()) = 4 THEN STRING(YEAR(NOW())) + '1001' END AND CASE WHEN QUARTER(NOW()) = 1 THEN STRING(YEAR(NOW())) + '0331' WHEN QUARTER(NOW()) = 2 THEN STRING(YEAR(NOW())) + '0630' WHEN QUARTER(NOW()) = 3 THEN STRING(YEAR(NOW())) + '0930' WHEN QUARTER(NOW()) = 4 THEN STRING(YEAR(NOW())) + '1231' END GROUP BY adv_id ) quarter_spend ON quarter_spend.adv_id = quarter_budget.adv_id) quarter_info ON quarter_info.adv_id = adv_budget.adv_id LEFT JOIN ( SELECT year_budget.adv_id adv_id, year_budget.year_budget year_budget, year_spend.year_spend year_spend, year_budget.pct_year pct_year FROM ( SELECT Advertiser_ID adv_id, SUM((scheduled_segments.max_spend_advertiser_micros / 1000000) * ( DATEDIFF( USEC_TO_TIMESTAMP(LEAST( INTEGER(PARSE_UTC_USEC( STRING(YEAR(NOW())) + '-12-31 23:59:59')), INTEGER(scheduled_segments.end_time_usec))), USEC_TO_TIMESTAMP(GREATEST( INTEGER(PARSE_UTC_USEC( STRING(YEAR(NOW())) + '-01-01 00:00:00')), INTEGER(scheduled_segments.start_time_usec)) )) / DATEDIFF(scheduled_segments.end_time_usec, scheduled_segments.start_time_usec))) year_budget, ( DATEDIFF( NOW(), PARSE_UTC_USEC(STRING(YEAR(NOW())) + '-01-01 00:00:00')) / DATEDIFF(PARSE_UTC_USEC(STRING(YEAR(NOW())) + '-12-31 23:59:59'), PARSE_UTC_USEC(STRING(YEAR(NOW())) + '-01-01 00:00:00'))) pct_year FROM FLATTEN([PARAMETER].Entity_InsertionOrder, scheduled_segments) WHERE STRFTIME_UTC_USEC(scheduled_segments.start_time_usec, '%Y%m%d') BETWEEN STRING(YEAR(NOW())) + '0101' AND STRING(YEAR(NOW())) + '3112' AND STRFTIME_UTC_USEC(scheduled_segments.end_time_usec, '%Y%m%d') BETWEEN STRING(YEAR(NOW())) + '0101' AND STRING(YEAR(NOW())) + '3112' GROUP BY adv_id ) year_budget INNER JOIN ( SELECT SUM(FLOAT(spend.Revenue)) year_spend, adv.adv_id adv_id FROM [[PARAMETER].Pacing_Spend_Report] spend INNER JOIN ( SELECT common_data.id io_id, advertiser_id adv_id FROM [[PARAMETER].Entity_InsertionOrder] ) adv ON spend.Insertion_Order_ID = adv.io_id WHERE REPLACE(spend.Report_Day, '/', '') BETWEEN STRING(YEAR(NOW())) + '0101' AND STRING(YEAR(NOW())) + '3112' GROUP BY adv_id ) year_spend ON year_spend.adv_id = year_budget.adv_id) year_info ON year_info.adv_id = adv_budget.adv_id WHERE quarter_spend IS NOT NULL",
        "parameters":[
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }}
        ]
      }
    }},
    { "bigquery": {
      "auth": "service",
      "to": {
        "dataset":{"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
        "table": "Pacing_View_Impressions"
      },
      "from": {
        "query": "SELECT u.adv_trader adv_trader, u.io_trader io_trader, u.advertiser advertiser, u.io io, u.io_id io_id, u.days_passed days_passed, u.days_left days_left, GREATEST(u.impressions_left, 0) impressions_left, u.impressions impressions, u.budgeted_impressions budgeted_impressions, u.expected_impressions expected_impressions, GREATEST(u.expected_impressions - u.impressions, 0) impressions_behind, u.expected_impressions - u.impressions impressions_behind_uncapped, u.previous_day_impressions previous_day_impressions, GREATEST(u.impressions_left / u.days_left, 0) target_daily_impressions, u.impressions / u.days_passed avg_daily_impressions, LEAST(u.previous_day_impressions / GREATEST(u.impressions_left / u.days_left, 1), 1) percent_daily_target, GREATEST(LEAST(u.impressions / u.expected_impressions, 1), 0) pacing, u.impressions / u.expected_impressions pacing_uncapped, CASE WHEN ROUND(u.impressions / u.expected_impressions, 2) BETWEEN 0 AND 0.25 THEN '1(0-25%)' WHEN ROUND(u.impressions / u.expected_impressions, 2) BETWEEN 0.26 AND 0.5 THEN '2(26-50%)' WHEN ROUND(u.impressions / u.expected_impressions, 2) BETWEEN 0.51 AND 0.75 THEN '3(51-75%)' WHEN ROUND(u.impressions / u.expected_impressions, 2) BETWEEN 0.76 AND 1 THEN '4(76-100%)' WHEN ROUND(u.impressions / u.expected_impressions, 2) BETWEEN 1.01 AND 1.25 THEN '5(101-125%)' WHEN ROUND(u.impressions / u.expected_impressions, 2) BETWEEN 1.26 AND 1.5 THEN '6(126-150%)' WHEN ROUND(u.impressions / u.expected_impressions, 2) BETWEEN 1.51 AND 1.75 THEN '7(151-175%)' WHEN ROUND(u.impressions / u.expected_impressions, 2) BETWEEN 1.76 AND 2 THEN '8(176-200%)' WHEN ROUND(u.impressions / u.expected_impressions, 2) > 2 THEN '9(200%+)' ELSE 'UNKNOWN' END pacing_breakout, 1 ct FROM ( SELECT t.adv_trader adv_trader, t.io_trader io_trader, t.io_id io_id, t.io io, t.start_day start_day, t.end_day end_day, t.flight_days flight_days, t.days_left days_left, t.days_left / t.flight_days flight_percent_remaining, t.adv_id adv_id, t.advertiser advertiser, COALESCE(t.previous_day_impressions, 0) previous_day_impressions, MAX(t.budgeted_impressions) budgeted_impressions, SUM(t.impressions) impressions, MAX(t.budgeted_impressions) / t.flight_days daily_budgeted_impressions, t.flight_days - t.days_left days_passed, ( MAX(t.budgeted_impressions) / t.flight_days ) * ( t.flight_days - t.days_left ) expected_impressions, MAX(t.budgeted_impressions) - SUM(t.impressions) impressions_left FROM ( SELECT io.common_data.id io_id, io.common_data.NAME io, io.advertiser_id adv_id, adv.common_data.NAME advertiser, STRFTIME_UTC_USEC(io.scheduled_segments.start_time_usec, '%Y/%m/%d') start_day, STRFTIME_UTC_USEC(io.scheduled_segments.end_time_usec, '%Y/%m/%d') end_day, DATEDIFF(io.scheduled_segments.end_time_usec, io.scheduled_segments.start_time_usec) flight_days, GREATEST(DATEDIFF(io.scheduled_segments.end_time_usec, GREATEST(io.scheduled_segments.start_time_usec, INTEGER(NOW()))), 0 ) days_left, io.scheduled_segments.max_impressions budgeted_impressions, spend.impressions impressions, pd.impressions previous_day_impressions, adv_budget.trader adv_trader, trader.trader io_trader FROM FLATTEN([PARAMETER].Entity_InsertionOrder, scheduled_segments) io INNER JOIN [PARAMETER].Entity_Advertiser adv ON adv.common_data.id = io.advertiser_id LEFT JOIN ( SELECT insertion_order_id io_id, SUM(FLOAT(impressions)) impressions FROM [PARAMETER].Pacing_Yesterday_Spend GROUP BY io_id) pd ON pd.io_id = io.common_data.id LEFT JOIN ( SELECT Advertiser_ID adv_id, Trader trader FROM [[PARAMETER].Pacing_Budget]) adv_budget ON adv_budget.adv_id = adv.common_data.id LEFT JOIN ( SELECT Trader trader, Insertion_Order_ID io_id FROM [[PARAMETER].Pacing_Traders]) trader ON trader.io_id = io.common_data.id CROSS JOIN ( SELECT Report_Day date, insertion_order_id io_id, SUM(impressions) impressions FROM [PARAMETER].Pacing_Spend_Report WHERE Insertion_Order_ID IN ( SELECT common_data.id io_id FROM FLATTEN([[PARAMETER].Entity_InsertionOrder], scheduled_segments) WHERE NOW() BETWEEN scheduled_segments.start_time_usec AND scheduled_segments.end_time_usec GROUP BY io_id) GROUP BY date, io_id) spend WHERE io.common_data.id = spend.io_id AND io.scheduled_segments.max_impressions IS NOT NULL AND spend.date BETWEEN STRFTIME_UTC_USEC(io.scheduled_segments.start_time_usec, '%Y/%m/%d') AND STRFTIME_UTC_USEC(io.scheduled_segments.end_time_usec, '%Y/%m/%d') AND NOW() BETWEEN io.scheduled_segments.start_time_usec AND io.scheduled_segments.end_time_usec) t GROUP BY io_id, io, start_day, end_day, flight_days, t.flight_days, days_left, t.days_left, flight_percent_remaining, adv_id, advertiser, days_passed, adv_trader, io_trader, previous_day_impressions) u WHERE u.days_left > 0 AND u.days_passed > 0",
        "parameters":[
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }},
          {"field":{ "name":"dataset", "kind":"string", "description":"Place where tables will be created in BigQuery." }}
        ]
      }
    }}
  ]
}