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“LAKSHMIRPILLAI”
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Update Super mode query for epic views
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‎super-mode-calculator/src/lib/build-query.ts

+60-87
Original file line numberDiff line numberDiff line change
@@ -31,117 +31,90 @@ export const buildQueryForSuperMode = (
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WITH
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acquisitions_with_regions AS (SELECT *,${regionSql('country_Code')}
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FROM datatech-platform-${stage.toLowerCase()}.datalake.fact_acquisition_event
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WHERE
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DATE (event_timestamp) >= '${dateString}'
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AND
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event_timestamp >= TIMESTAMP '${dateHourString}' AND event_timestamp < TIMESTAMP '${endDateHourString}'),
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WHERE DATE (event_timestamp) >= '${dateString}' AND
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event_timestamp >= TIMESTAMP '${dateHourString}' AND event_timestamp < TIMESTAMP '${endDateHourString}'),
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exchange_rates AS (
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SELECT target, date, (1/rate) AS reverse_rate
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FROM datatech-platform-${stage.toLowerCase()}.datalake.fixer_exchange_rates
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WHERE date = '${format(dateForCurrencyConversionTable, 'yyyy-MM-dd')}'),
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gbp_rate AS (
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SELECT
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rate, date
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SELECT rate, date
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FROM datatech-platform-${stage.toLowerCase()}.datalake.fixer_exchange_rates
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WHERE target = 'GBP'
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AND date = '${format(dateForCurrencyConversionTable, 'yyyy-MM-dd')}'),
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WHERE target = 'GBP' AND date = '${format(
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dateForCurrencyConversionTable,
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'yyyy-MM-dd',
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)}'),
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acquisitions AS (
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SELECT
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CASE product
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WHEN 'SUPPORTER_PLUS' THEN
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CASE currency
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WHEN 'GBP' THEN
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CASE payment_frequency
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WHEN 'MONTHLY' THEN 12
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WHEN 'ANNUAL' THEN 120
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END
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WHEN 'USD' THEN
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CASE payment_frequency
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WHEN 'MONTHLY' THEN 15
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WHEN 'ANNUAL' THEN 150
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END
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WHEN 'AUD' THEN
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CASE payment_frequency
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WHEN 'MONTHLY' THEN 20
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WHEN 'ANNUAL' THEN 200
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END
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WHEN 'EUR' THEN
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CASE payment_frequency
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WHEN 'MONTHLY' THEN 12
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WHEN 'ANNUAL' THEN 120
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END
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WHEN 'NZD' THEN
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CASE payment_frequency
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WHEN 'MONTHLY' THEN 20
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WHEN 'ANNUAL' THEN 200
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END
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WHEN 'CAD' THEN
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CASE payment_frequency
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WHEN 'MONTHLY' THEN 15
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WHEN 'ANNUAL' THEN 150
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END
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END
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WHEN 'CONTRIBUTION' THEN amount
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WHEN 'RECURRING_CONTRIBUTION' THEN amount
86-
END
50+
WHEN 'SUPPORTER_PLUS' THEN
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CASE currency
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WHEN 'GBP' THEN
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CASE payment_frequency
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WHEN 'MONTHLY' THEN 12
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WHEN 'ANNUAL' THEN 120
56+
END
57+
WHEN 'USD' THEN
58+
CASE payment_frequency
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WHEN 'MONTHLY' THEN 15
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WHEN 'ANNUAL' THEN 150
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END
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WHEN 'AUD' THEN
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CASE payment_frequency
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WHEN 'MONTHLY' THEN 20
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WHEN 'ANNUAL' THEN 200
66+
END
67+
WHEN 'EUR' THEN
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CASE payment_frequency
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WHEN 'MONTHLY' THEN 12
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WHEN 'ANNUAL' THEN 120
71+
END
72+
WHEN 'NZD' THEN
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CASE payment_frequency
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WHEN 'MONTHLY' THEN 20
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WHEN 'ANNUAL' THEN 200
76+
END
77+
WHEN 'CAD' THEN
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CASE payment_frequency
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WHEN 'MONTHLY' THEN 15
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WHEN 'ANNUAL' THEN 150
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END
82+
END
83+
WHEN 'CONTRIBUTION' THEN amount
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WHEN 'RECURRING_CONTRIBUTION' THEN amount
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END
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AS amount, product, currency, country_code, referrer_url, payment_frequency,
88-
FROM datatech-platform-${stage.toLowerCase()}.datalake.fact_acquisition_event AS acq
89-
WHERE event_timestamp >= TIMESTAMP '${dateHourString}' AND event_timestamp < TIMESTAMP '${endDateHourString}'),
87+
FROM datatech-platform-${stage.toLowerCase()}.datalake.fact_acquisition_event AS acq
88+
WHERE event_timestamp >= TIMESTAMP '${dateHourString}' AND event_timestamp < TIMESTAMP '${endDateHourString}'),
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acquisitions_with_av AS (
91-
SELECT
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acq.*, date, CASE payment_frequency
90+
SELECT acq.*, date, CASE payment_frequency
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WHEN 'ONE_OFF' THEN amount * exch.reverse_rate
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WHEN 'MONTHLY' THEN (amount * exch.reverse_rate)*12
9593
WHEN 'ANNUAL' THEN amount * exch.reverse_rate
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END
97-
AS av_eur, exch.reverse_rate
98-
FROM acquisitions AS acq
99-
JOIN exchange_rates AS exch
100-
ON acq.currency = exch.target
101-
),
95+
AS av_eur, exch.reverse_rate FROM acquisitions AS acq JOIN exchange_rates AS exch ON acq.currency = exch.target),
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acquisitions_with_av_gbp AS (
103-
SELECT
104-
acq_av.*, CASE acq_av.currency
105-
WHEN 'GBP' THEN av_eur
106-
ELSE av_eur * (gbp_rate.rate)
97+
SELECT acq_av.*, CASE acq_av.currency
98+
WHEN 'GBP' THEN av_eur ELSE av_eur * (gbp_rate.rate)
10799
END
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AS av_gbp
109-
FROM acquisitions_with_av AS acq_av
110-
JOIN gbp_rate
111-
ON acq_av.date = gbp_rate.date
112-
),
100+
AS av_gbp FROM acquisitions_with_av AS acq_av JOIN gbp_rate ON acq_av.date = gbp_rate.date),
113101
acquisitions_agg AS (
114-
SELECT
115-
country_code, referrer_url, SUM (av_gbp) sum_av_gbp, COUNT (*) acquisitions
102+
SELECT country_code, referrer_url, SUM (av_gbp) sum_av_gbp, COUNT (*) acquisitions
116103
FROM acquisitions_with_av_gbp
117-
GROUP BY 1, 2
118-
),
104+
GROUP BY 1, 2),
119105
av AS (
120-
SELECT
121-
acq_agg.referrer_url AS url, acq_region.region AS region, SUM ( acq_agg.sum_av_gbp) AS total_av,
122-
FROM
123-
acquisitions_with_regions as acq_region
124-
JOIN acquisitions_agg AS acq_agg
125-
ON acq_region.region =acq_agg.country_code
106+
SELECT acq_agg.referrer_url AS url, acq_region.region AS region, SUM ( acq_agg.sum_av_gbp) AS total_av,
107+
FROM acquisitions_with_regions as acq_region JOIN acquisitions_agg AS acq_agg ON acq_region.region =acq_agg.country_code
126108
GROUP BY 1, 2),
127109
views_with_regions AS (
128110
SELECT *, ${regionSql('country_key')}
129-
FROM
130-
datatech-platform-${stage.toLowerCase()}.online_traffic.fact_page_view_anonymised
131-
CROSS JOIN UNNEST(component_event_array) as ce
132-
WHERE received_date >= DATE_SUB('${dateString}'
133-
, INTERVAL 1 DAY)
134-
AND received_date <= '${dateString}'
135-
AND
136-
ce.event_timestamp >= TIMESTAMP '${dateHourString}' AND ce.event_timestamp < TIMESTAMP '${endDateHourString}')
137-
,
111+
FROM datatech-platform-${stage.toLowerCase()}.online_traffic.fact_page_view_anonymised CROSS JOIN UNNEST(component_event_array) as ce
112+
WHERE received_date >= DATE_SUB('${dateString}', INTERVAL 1 DAY) AND received_date <= '${dateString}' AND ce.component_type = 'ACQUISITIONS_EPIC' AND ce.event_action = 'VIEW' AND
113+
ce.event_timestamp >= TIMESTAMP '${dateHourString}' AND ce.event_timestamp < TIMESTAMP '${endDateHourString}') ,
138114
views AS (
139-
SELECT
140-
referrer_url_raw AS url, region, COUNT (*) AS total_views
141-
FROM
142-
views_with_regions
143-
GROUP BY 1, 2
144-
)
115+
SELECT referrer_url_raw AS url, region, COUNT (*) AS total_views
116+
FROM views_with_regions
117+
GROUP BY 1, 2)
145118
SELECT av.url,
146119
av.region,
147120
av.total_av AS totalAv,

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