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add workflow 市场News-Agents调度,dev

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root 2026-03-05 14:38:06 +08:00
parent 2747e86030
commit 043a0da645
1 changed files with 5 additions and 2 deletions
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7
dev/workflow/TK_Cust/agents_market_newsletter/news_letter/dysql_news_letter_info.sql
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@ -74,11 +74,12 @@ order by p1.tek_opportunity_id,status_last_update desc,p1.as_of_date asc;
delete from p60_mart.news_letter_info delete from p60_mart.news_letter_info
where source_system='market_summary'; where source_system='market_summary';
INSERT INTO p60_mart.news_letter_info INSERT INTO p60_mart.news_letter_info
(account_name, saler_name, whitelist_flag, newsletter_title, summary, key_products, tek_relevance, industry, prov_name, city_name, district, contact_qty, total_funnel, report_amt,source_url,business_type,create_tm,source_system,data_source) (account_name, saler_name, whitelist_flag, newsletter_title, summary, key_products, tek_relevance, industry, prov_name, city_name, district, contact_qty, total_funnel, report_amt,source_url,business_type,create_tm,source_system,data_source,portal_url,zip_url)
select distinct on (p1.company_name,p1.source_url) p1.company_name account_name, coalesce(saler_name,''), whitelist_flag, newsletter_title, summary select distinct on (p1.company_name,p1.source_url) p1.company_name account_name, coalesce(saler_name,''), whitelist_flag, newsletter_title, summary
, case when p5.data_json::text like '{%' then replace(replace(replace(p5.data_json->>'主营产品'::text,'"',''),'[',''),']','') , case when p5.data_json::text like '{%' then replace(replace(replace(p5.data_json->>'主营产品'::text,'"',''),'[',''),']','')
when p5.data_json::text like '[%' then replace(replace(replace(p5.data_json::text,'"',''),'[',''),']','') else '' end when p5.data_json::text like '[%' then replace(replace(replace(p5.data_json::text,'"',''),'[',''),']','') else '' end
,coalesce(p5.recomend_product_series::text,'') tek_relevance, industry, coalesce(prov_name,''), coalesce(city_name), district,coalesce(p2.contact_qty,0) contact_qty, coalesce(total_amt,0)+coalesce(total_amount,0) total_funnel,coalesce(total_amt,0) report_amt,p1.source_url,p1.business_type,p1.create_tm,'market_summary',p1.data_source from newsletter_t1 p1 ,coalesce(p5.recomend_product_series::text,'') tek_relevance, industry, coalesce(prov_name,''), coalesce(city_name), district,coalesce(p2.contact_qty,0) contact_qty, coalesce(total_amt,0)+coalesce(total_amount,0) total_funnel,coalesce(total_amt,0) report_amt,p1.source_url,p1.business_type,p1.create_tm,'market_summary',p1.data_source,p6.门户资源包,p6.压缩包链接
from newsletter_t1 p1
left join (select company,count(*) contact_qty from newsletter_contact_t1 group by 1 ) p2 left join (select company,count(*) contact_qty from newsletter_contact_t1 group by 1 ) p2
on p1.company_name=p2.company on p1.company_name=p2.company
left join (select customer_name,sum(total_amt) total_amt from newsletter_funnel_one_t1 group by 1) p3 left join (select customer_name,sum(total_amt) total_amt from newsletter_funnel_one_t1 group by 1) p3
@ -87,6 +88,8 @@ left join (select account_name,sum(total_amount) total_amount from newsletter_fu
on p1.company_name=p4.account_name on p1.company_name=p4.account_name
left join p70_ai_intelligence.agent_recommendation_cache p5 left join p70_ai_intelligence.agent_recommendation_cache p5
on p1.company_name=p5.company_name on p1.company_name=p5.company_name
left join p70_ai_intelligence.key_recommendation p6
on regexp_replace(p5.matched_keys, '[^\u4e00-\u9fa5]', '', 'g')like '%'||regexp_replace(p6.关键词, '[^\u4e00-\u9fa5]', '', 'g') ||'%'
order by p1.company_name,p1.source_url,p1.create_tm desc,p5.created_at desc; order by p1.company_name,p1.source_url,p1.create_tm desc,p5.created_at desc;
drop table if exists newsletter_funnel_one_t2; drop table if exists newsletter_funnel_one_t2;