SELECT b.id as userId , 2 as userPos, c.state, c.id contractId, c.start_time FROM ( SELECT su.id,suo.org_id FROM autost_user.sys_user su LEFT JOIN autost_user.sys_user_org suo on suo.user_id = su.id LEFT JOIN autost_user.sys_user_pos sup on sup.user_id = su.id WHERE sup.pos_value = 21 ) b LEFT JOIN( SELECT a.*,so1.parent_ids FROM ( SELECT oc.id, oc.start_time, IF(DATEDIFF(oc.`end_time`,NOW()) > 0,0,2) as state, so.org_area_id FROM autost_epms.org_contract oc LEFT JOIN autost_user.sys_organization so on so.id = oc.org_id WHERE oc.del_flag = 0 AND so.del_flag = 0 AND oc.`status`=3 AND oc.due_time_type = 0 AND oc.`cancel_flag`=0 AND oc.end_time is not null AND DATEDIFF(oc.`end_time`,NOW())<=60 AND so.category is not null ORDER BY DATEDIFF(oc.`end_time`,NOW()) DESC ) a LEFT JOIN autost_user.sys_organization so1 ON a.org_area_id = so1.id ) c ON FIND_IN_SET(b.org_id,c.parent_ids);可以优化么

根据您提供的查询语句，我注意到您使用了子查询和连接操作，这可能导致查询性能较低。以下是一种可能的优化方法：

1. 避免不必要的子查询：您可以尝试将子查询中的逻辑合并到主查询中，以减少查询的复杂性和开销。

2. 使用内连接代替左连接：如果您确定两个表之间的关联数据是必须匹配的，可以考虑使用内连接（INNER JOIN）而不是左连接（LEFT JOIN），这样可以减少不必要的结果集大小。

3. 添加索引：根据查询中涉及的表和字段，考虑添加适当的索引以提高查询性能。索引可以加速数据检索和连接操作。

以下是优化后的查询语句示例：

SELECT 
    b.id as userId,
    2 as userPos,
    IF(DATEDIFF(c.end_time, NOW()) > 0, 0, 2) as state,
    c.id as contractId,
    c.start_time
FROM autost_user.sys_user b
LEFT JOIN autost_user.sys_user_org suo ON suo.user_id = b.id
LEFT JOIN autost_user.sys_user_pos sup ON sup.user_id = b.id AND sup.pos_value = 21
LEFT JOIN (
    SELECT 
        oc.id, 
        oc.start_time, 
        oc.end_time,
        so.org_area_id
    FROM autost_epms.org_contract oc
    LEFT JOIN autost_user.sys_organization so ON so.id = oc.org_id
    WHERE oc.del_flag = 0
        AND so.del_flag = 0
        AND oc.status = 3
        AND oc.due_time_type = 0 
        AND oc.cancel_flag = 0 
        AND oc.end_time IS NOT NULL
        AND DATEDIFF(oc.end_time, NOW()) <= 60
        AND so.category IS NOT NULL
    ORDER BY DATEDIFF(oc.end_time, NOW()) DESC
) c ON FIND_IN_SET(suo.org_id, c.parent_ids);

请注意，优化后的查询语句仅供参考。根据您的数据量、表结构和索引情况，实际性能可能会有所不同。建议在应用到生产环境之前，先进行测试和验证。