41 lines
2.1 KiB
SQL
41 lines
2.1 KiB
SQL
-- 处理逻辑说明
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-- 1.用到了first_user 和 lately_user 这两个表来计算ltv
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-- first_user是用户首次登陆时间
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-- lately_user是用户最后一次登陆时间
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-- 2.用户首次登陆去关联用户最后一次登陆时间他们的时间差就是用户的流失时间
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INSERT INTO ads.user_retention ( relation_id,prodid,ds,num,ltv1,ltv2,ltv3,ltv4,ltv5,ltv6,ltv7,ltv14,ltv30,ltv60,ltv90,ltv150,ltv300)
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select
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t1.relation_id
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,t1.prodid
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,t1.ds
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,count(distinct t1.user_id) AS num
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,SUM(CASE WHEN (t2.ds_date-t1.ds_date) = 1 then 1 ELSE 0 END) AS ltv1
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,SUM(CASE WHEN (t2.ds_date-t1.ds_date) = 2 then 1 ELSE 0 END) AS ltv2
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,SUM(CASE WHEN (t2.ds_date-t1.ds_date) = 3 then 1 ELSE 0 END) AS ltv3
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,SUM(CASE WHEN (t2.ds_date-t1.ds_date) = 4 then 1 ELSE 0 END) AS ltv4
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,SUM(CASE WHEN (t2.ds_date-t1.ds_date) = 5 then 1 ELSE 0 END) AS ltv5
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,SUM(CASE WHEN (t2.ds_date-t1.ds_date) = 6 then 1 ELSE 0 END) AS ltv6
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,SUM(CASE WHEN (t2.ds_date-t1.ds_date) = 7 then 1 ELSE 0 END) AS ltv7
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,SUM(CASE WHEN (t2.ds_date-t1.ds_date) = 14 then 1 ELSE 0 END) AS ltv14
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,SUM(CASE WHEN (t2.ds_date-t1.ds_date) = 30 then 1 ELSE 0 END) AS ltv30
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,SUM(CASE WHEN (t2.ds_date-t1.ds_date) = 60 then 1 ELSE 0 END) AS ltv60
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,SUM(CASE WHEN (t2.ds_date-t1.ds_date) = 90 then 1 ELSE 0 END) AS ltv90
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,SUM(CASE WHEN (t2.ds_date-t1.ds_date) = 150 then 1 ELSE 0 END) AS ltv150
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,SUM(CASE WHEN (t2.ds_date-t1.ds_date) = 300 then 1 ELSE 0 END) AS ltv300
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from
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dim.first_user t1
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left join
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dwd.active_df t2
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on t1.relation_id=t2.relation_id
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and t1.user_id=t2.user_id
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AND t2.ds_date-t1.ds_date IN (1,2,3,4,5,6,7,14,30,60,90,150,300)
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where t1.ds>='${300_days_later}'
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group by t1.relation_id
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,t1.prodid
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,t1.ds
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ON CONFLICT (relation_id,prodid,ds)
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DO UPDATE SET num = EXCLUDED.num,ltv1 = EXCLUDED.ltv1,ltv2 = EXCLUDED.ltv2,ltv3 = EXCLUDED.ltv3,ltv4 = EXCLUDED.ltv4,ltv5 = EXCLUDED.ltv5,ltv6 = EXCLUDED.ltv6,ltv7 = EXCLUDED.ltv7,ltv14 = EXCLUDED.ltv14,ltv30 = EXCLUDED.ltv30,ltv60 = EXCLUDED.ltv60
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,ltv90 = EXCLUDED.ltv90,ltv150 = EXCLUDED.ltv150,ltv300 = EXCLUDED.ltv300
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; |