🏆

高薪企业排行榜

基于职位薪资 + 用户分享综合计算，真实反映企业薪酬水平

🌏 全国 · 住宿和餐饮业 共 7 家上榜企业 薪资来源：职位发布（橙色）+ 用户匿名分享（绿色），加权平均计算
职位发布 用户分享
1
1
信阳南雷酒店管理有限公司
🏭 住宿和餐饮业📍 平桥区 📊 1条薪资数据 💼 1个在招职位
职位 1 条 · ¥0K
¥0K
平均月薪
2
2
信阳市浉河区茶山驿站文旅有限责任公司
🏭 住宿和餐饮业📍 浉河区 📊 1条薪资数据 💼 1个在招职位
职位 1 条 · ¥0K
¥0K
平均月薪
3
3
信阳隐觅餐饮管理有限公司
🏭 住宿和餐饮业📍 羊山区 📊 3条薪资数据 💼 4个在招职位
职位 3 条 · ¥0K
¥0K
平均月薪
4
4
信阳市鑫源饮食服务有限责任公司
🏭 住宿和餐饮业📍 浉河区 📊 2条薪资数据 💼 2个在招职位
职位 2 条 · ¥0K
¥0K
平均月薪
5
5
信阳市星瑞餐饮有限公司
🏭 住宿和餐饮业📍 羊山区 📊 1条薪资数据 💼 1个在招职位
职位 1 条 · ¥0K
¥0K
平均月薪
6
6
信阳世纪星酒店有限公司
🏭 住宿和餐饮业📍 浉河区 📊 1条薪资数据 💼 1个在招职位
职位 1 条 · ¥0K
¥0K
平均月薪
7
7
简阳市海捞餐饮管理有限公司信阳市第二分公司
🏭 住宿和餐饮业📍 羊山区 📊 1条薪资数据 💼 1个在招职位
职位 1 条 · ¥0K
¥0K
平均月薪
基本 文件 流程 错误 SQL 调试
  1. 请求信息 : 2026-04-29 21:37:15 HTTP/2.0 GET : https://youjupin.cn/enterprise/ranking?industry=%E4%BD%8F%E5%AE%BF%E5%92%8C%E9%A4%90%E9%A5%AE%E4%B8%9A
  2. 运行时间 : 0.081585s [ 吞吐率：12.26req/s ] 内存消耗：605.56kb 文件加载：129
  3. 缓存信息 : 0 reads,0 writes
  4. 会话信息 : SESSION_ID=66d2b8e87d054a65e4580feb0cd8d922
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  78. /www/wwwroot/zhaopin/vendor/topthink/framework/src/think/Cache.php ( 4.92 KB )
  79. /www/wwwroot/zhaopin/vendor/psr/simple-cache/src/CacheInterface.php ( 4.71 KB )
  80. /www/wwwroot/zhaopin/vendor/topthink/think-helper/src/helper/Arr.php ( 16.63 KB )
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  92. /www/wwwroot/zhaopin/vendor/topthink/framework/src/think/contract/SessionHandlerInterface.php ( 0.87 KB )
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  104. /www/wwwroot/zhaopin/app/controller/EnterpriseController.php ( 20.53 KB )
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  109. /www/wwwroot/zhaopin/vendor/topthink/think-orm/src/db/connector/Mysql.php ( 5.44 KB )
  110. /www/wwwroot/zhaopin/vendor/topthink/think-orm/src/db/PDOConnection.php ( 52.56 KB )
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  127. /www/wwwroot/zhaopin/runtime/view/3789788358217b6fb264f30c3098eedd.php ( 80.69 KB )
  128. /www/wwwroot/zhaopin/vendor/topthink/framework/src/think/facade/Session.php ( 1.79 KB )
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  1. CONNECT:[ UseTime:0.000663s ] mysql:host=127.0.0.1;port=3306;dbname=zhaopin;charset=utf8mb4
  2. SELECT COUNT(*) AS cnt FROM (SELECT m.enterprise_id, COALESCE(e.name, '-') AS enterprise_name, e.industry, e.city, e.scale, e.logo, e.score_overall, e.review_count, e.position_count, COALESCE(m.pos_cnt, 0) AS pos_cnt, COALESCE(m.ss_cnt, 0) AS ss_cnt, (COALESCE(m.pos_cnt, 0) + COALESCE(m.ss_cnt, 0)) AS total_cnt, ROUND(m.weighted_avg) AS avg_salary FROM ( SELECT enterprise_id, pos_cnt, ss_cnt, (pos_cnt * pos_avg + ss_cnt * ss_avg) / (pos_cnt + ss_cnt) AS weighted_avg FROM ( SELECT COALESCE(a.enterprise_id, b.enterprise_id) AS enterprise_id, COALESCE(a.pos_cnt, 0) AS pos_cnt, COALESCE(b.ss_cnt, 0) AS ss_cnt, a.pos_avg, b.ss_avg FROM (SELECT p.enterprise_id, COUNT(*) AS pos_cnt, ROUND(AVG((IFNULL(p.min_salary,0)+IFNULL(p.max_salary,0))/2)) AS pos_avg FROM position p INNER JOIN enterprise e ON e.id = p.enterprise_id AND e.status = 1 WHERE p.status = 1 AND (p.min_salary > 0 OR p.max_salary > 0) AND e.industry LIKE '%住宿和餐饮业%' GROUP BY p.enterprise_id) a LEFT JOIN (SELECT ss.enterprise_id, COUNT(*) AS ss_cnt, ROUND(AVG(ss.month_salary)) AS ss_avg FROM salary_share ss INNER JOIN enterprise e ON e.id = ss.enterprise_id AND e.status = 1 WHERE ss.status = 1 AND ss.month_salary > 0 AND e.industry LIKE '%住宿和餐饮业%' GROUP BY ss.enterprise_id) b ON a.enterprise_id = b.enterprise_id UNION SELECT COALESCE(a.enterprise_id, b.enterprise_id) AS enterprise_id, COALESCE(a.pos_cnt, 0), COALESCE(b.ss_cnt, 0), a.pos_avg, b.ss_avg FROM (SELECT p.enterprise_id, COUNT(*) AS pos_cnt, ROUND(AVG((IFNULL(p.min_salary,0)+IFNULL(p.max_salary,0))/2)) AS pos_avg FROM position p INNER JOIN enterprise e ON e.id = p.enterprise_id AND e.status = 1 WHERE p.status = 1 AND (p.min_salary > 0 OR p.max_salary > 0) AND e.industry LIKE '%住宿和餐饮业%' GROUP BY p.enterprise_id) a RIGHT JOIN (SELECT ss.enterprise_id, COUNT(*) AS ss_cnt, ROUND(AVG(ss.month_salary)) AS ss_avg FROM salary_share ss INNER JOIN enterprise e ON e.id = ss.enterprise_id AND e.status = 1 WHERE ss.status = 1 AND ss.month_salary > 0 AND e.industry LIKE '%住宿和餐饮业%' GROUP BY ss.enterprise_id) b ON a.enterprise_id = b.enterprise_id ) AS u WHERE (COALESCE(pos_cnt,0) + COALESCE(ss_cnt,0)) >= 1 ) AS m INNER JOIN enterprise e ON e.id = m.enterprise_id ORDER BY m.weighted_avg DESC) AS t [ RunTime:0.002861s ]
  3. SELECT * FROM (SELECT m.enterprise_id, COALESCE(e.name, '-') AS enterprise_name, e.industry, e.city, e.scale, e.logo, e.score_overall, e.review_count, e.position_count, COALESCE(m.pos_cnt, 0) AS pos_cnt, COALESCE(m.ss_cnt, 0) AS ss_cnt, (COALESCE(m.pos_cnt, 0) + COALESCE(m.ss_cnt, 0)) AS total_cnt, ROUND(m.weighted_avg) AS avg_salary FROM ( SELECT enterprise_id, pos_cnt, ss_cnt, (pos_cnt * pos_avg + ss_cnt * ss_avg) / (pos_cnt + ss_cnt) AS weighted_avg FROM ( SELECT COALESCE(a.enterprise_id, b.enterprise_id) AS enterprise_id, COALESCE(a.pos_cnt, 0) AS pos_cnt, COALESCE(b.ss_cnt, 0) AS ss_cnt, a.pos_avg, b.ss_avg FROM (SELECT p.enterprise_id, COUNT(*) AS pos_cnt, ROUND(AVG((IFNULL(p.min_salary,0)+IFNULL(p.max_salary,0))/2)) AS pos_avg FROM position p INNER JOIN enterprise e ON e.id = p.enterprise_id AND e.status = 1 WHERE p.status = 1 AND (p.min_salary > 0 OR p.max_salary > 0) AND e.industry LIKE '%住宿和餐饮业%' GROUP BY p.enterprise_id) a LEFT JOIN (SELECT ss.enterprise_id, COUNT(*) AS ss_cnt, ROUND(AVG(ss.month_salary)) AS ss_avg FROM salary_share ss INNER JOIN enterprise e ON e.id = ss.enterprise_id AND e.status = 1 WHERE ss.status = 1 AND ss.month_salary > 0 AND e.industry LIKE '%住宿和餐饮业%' GROUP BY ss.enterprise_id) b ON a.enterprise_id = b.enterprise_id UNION SELECT COALESCE(a.enterprise_id, b.enterprise_id) AS enterprise_id, COALESCE(a.pos_cnt, 0), COALESCE(b.ss_cnt, 0), a.pos_avg, b.ss_avg FROM (SELECT p.enterprise_id, COUNT(*) AS pos_cnt, ROUND(AVG((IFNULL(p.min_salary,0)+IFNULL(p.max_salary,0))/2)) AS pos_avg FROM position p INNER JOIN enterprise e ON e.id = p.enterprise_id AND e.status = 1 WHERE p.status = 1 AND (p.min_salary > 0 OR p.max_salary > 0) AND e.industry LIKE '%住宿和餐饮业%' GROUP BY p.enterprise_id) a RIGHT JOIN (SELECT ss.enterprise_id, COUNT(*) AS ss_cnt, ROUND(AVG(ss.month_salary)) AS ss_avg FROM salary_share ss INNER JOIN enterprise e ON e.id = ss.enterprise_id AND e.status = 1 WHERE ss.status = 1 AND ss.month_salary > 0 AND e.industry LIKE '%住宿和餐饮业%' GROUP BY ss.enterprise_id) b ON a.enterprise_id = b.enterprise_id ) AS u WHERE (COALESCE(pos_cnt,0) + COALESCE(ss_cnt,0)) >= 1 ) AS m INNER JOIN enterprise e ON e.id = m.enterprise_id ORDER BY m.weighted_avg DESC) AS t LIMIT 20 OFFSET 0 [ RunTime:0.002339s ]
  4. SELECT e.city, COUNT(DISTINCT e.id) AS cnt, ROUND(AVG(t.wa)) AS avg_k FROM ( SELECT enterprise_id, (pos_cnt * pos_avg + ss_cnt * ss_avg) / (pos_cnt + ss_cnt) AS wa FROM ( SELECT COALESCE(a.enterprise_id, b.enterprise_id) AS enterprise_id, COALESCE(a.pos_cnt, 0) AS pos_cnt, COALESCE(b.ss_cnt, 0) AS ss_cnt, a.pos_avg, b.ss_avg FROM (SELECT p.enterprise_id, COUNT(*) AS pos_cnt, ROUND(AVG((IFNULL(p.min_salary,0)+IFNULL(p.max_salary,0))/2)) AS pos_avg FROM position p INNER JOIN enterprise e ON e.id = p.enterprise_id AND e.status = 1 WHERE p.status = 1 AND (p.min_salary > 0 OR p.max_salary > 0) AND e.industry LIKE '%住宿和餐饮业%' GROUP BY p.enterprise_id) a LEFT JOIN (SELECT ss.enterprise_id, COUNT(*) AS ss_cnt, ROUND(AVG(ss.month_salary)) AS ss_avg FROM salary_share ss INNER JOIN enterprise e ON e.id = ss.enterprise_id AND e.status = 1 WHERE ss.status = 1 AND ss.month_salary > 0 AND e.industry LIKE '%住宿和餐饮业%' GROUP BY ss.enterprise_id) b ON a.enterprise_id = b.enterprise_id UNION SELECT COALESCE(a.enterprise_id, b.enterprise_id), COALESCE(a.pos_cnt, 0), COALESCE(b.ss_cnt, 0), a.pos_avg, b.ss_avg FROM (SELECT p.enterprise_id, COUNT(*) AS pos_cnt, ROUND(AVG((IFNULL(p.min_salary,0)+IFNULL(p.max_salary,0))/2)) AS pos_avg FROM position p INNER JOIN enterprise e ON e.id = p.enterprise_id AND e.status = 1 WHERE p.status = 1 AND (p.min_salary > 0 OR p.max_salary > 0) AND e.industry LIKE '%住宿和餐饮业%' GROUP BY p.enterprise_id) a RIGHT JOIN (SELECT ss.enterprise_id, COUNT(*) AS ss_cnt, ROUND(AVG(ss.month_salary)) AS ss_avg FROM salary_share ss INNER JOIN enterprise e ON e.id = ss.enterprise_id AND e.status = 1 WHERE ss.status = 1 AND ss.month_salary > 0 AND e.industry LIKE '%住宿和餐饮业%' GROUP BY ss.enterprise_id) b ON a.enterprise_id = b.enterprise_id ) AS u WHERE (COALESCE(pos_cnt,0)+COALESCE(ss_cnt,0))>=1 ) AS t INNER JOIN enterprise e ON e.id = t.enterprise_id WHERE e.city <> '' GROUP BY e.city HAVING cnt >= 2 ORDER BY avg_k DESC LIMIT 10 [ RunTime:0.002197s ]
  5. SELECT e.industry, COUNT(DISTINCT e.id) AS cnt, ROUND(AVG(t.wa)/1000, 1) AS avg_k FROM ( SELECT enterprise_id, (pos_cnt*pos_avg+ss_cnt*ss_avg)/(pos_cnt+ss_cnt) AS wa FROM ( SELECT COALESCE(a.enterprise_id,b.enterprise_id) AS enterprise_id, COALESCE(a.pos_cnt,0) AS pos_cnt, COALESCE(b.ss_cnt,0) AS ss_cnt, a.pos_avg, b.ss_avg FROM (SELECT p.enterprise_id, COUNT(*) AS pos_cnt, ROUND(AVG((IFNULL(p.min_salary,0)+IFNULL(p.max_salary,0))/2)) AS pos_avg FROM position p INNER JOIN enterprise e ON e.id = p.enterprise_id AND e.status = 1 WHERE p.status = 1 AND (p.min_salary > 0 OR p.max_salary > 0) GROUP BY p.enterprise_id) a LEFT JOIN (SELECT ss.enterprise_id, COUNT(*) AS ss_cnt, ROUND(AVG(ss.month_salary)) AS ss_avg FROM salary_share ss INNER JOIN enterprise e ON e.id = ss.enterprise_id AND e.status = 1 WHERE ss.status = 1 AND ss.month_salary > 0 GROUP BY ss.enterprise_id) b ON a.enterprise_id = b.enterprise_id UNION SELECT COALESCE(a.enterprise_id,b.enterprise_id) AS enterprise_id, COALESCE(a.pos_cnt,0) AS pos_cnt, COALESCE(b.ss_cnt,0) AS ss_cnt, a.pos_avg, b.ss_avg FROM (SELECT p.enterprise_id, COUNT(*) AS pos_cnt, ROUND(AVG((IFNULL(p.min_salary,0)+IFNULL(p.max_salary,0))/2)) AS pos_avg FROM position p INNER JOIN enterprise e ON e.id = p.enterprise_id AND e.status = 1 WHERE p.status = 1 AND (p.min_salary > 0 OR p.max_salary > 0) GROUP BY p.enterprise_id) a RIGHT JOIN (SELECT ss.enterprise_id, COUNT(*) AS ss_cnt, ROUND(AVG(ss.month_salary)) AS ss_avg FROM salary_share ss INNER JOIN enterprise e ON e.id = ss.enterprise_id AND e.status = 1 WHERE ss.status = 1 AND ss.month_salary > 0 GROUP BY ss.enterprise_id) b ON a.enterprise_id = b.enterprise_id ) AS u WHERE (COALESCE(pos_cnt,0)+COALESCE(ss_cnt,0))>=1 ) AS t INNER JOIN enterprise e ON e.id = t.enterprise_id WHERE e.industry <> '' GROUP BY e.industry HAVING cnt >= 1 ORDER BY avg_k DESC LIMIT 10 [ RunTime:0.054845s ]
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