UPDATE test_copy1_copy1_copy1 SET id = (SELECT GROUP_CONCAT(b.id,',',c.id) FROM test_copy1 b JOIN test_copy1_copy1 c on b.id_card = c.id_card GROUP BY b.id_card,c.id_card)
时间: 2023-05-15 15:06:26 浏览: 98
这是一个 SQL 语句,它的作用是将 test_copy1_copy1_copy1 表中的 id 字段更新为 test_copy1 表和 test_copy1_copy1 表中 id_card 相同的记录的 id 字段的组合。具体实现需要根据数据库的具体情况进行调整。
相关问题
UPDATE data_catalog_dept_group_statistics_temp t, ( SELECT c.cata_group_id AS group_id, count( 1 ) AS cata_amount FROM data_catalog c WHERE is_del = 0 AND cata_group_id LIKE CONCAT('3071140224','%') GROUP BY c.cata_group_id )tmp set t.base_cata_amount = tmp.cata_amount where t.group_id = tmp.group_id; 语法哪里有问题
这段 SQL 语句的语法是有问题的,问题在于子查询的 SELECT 子句中,GROUP BY 子句最后缺少了一个空格。正确的写法应该是:
```
UPDATE
data_catalog_dept_group_statistics_temp t,
(
SELECT
c.cata_group_id AS group_id,
count(1) AS cata_amount
FROM
data_catalog c
WHERE
is_del = 0 AND
cata_group_id LIKE CONCAT('3071140224', '%')
GROUP BY
c.cata_group_id
) tmp
SET
t.base_cata_amount = tmp.cata_amount
WHERE
t.group_id = tmp.group_id;
```
在子查询中,GROUP BY 子句最后的 AS 子句之后需要加一个空格,否则会被认为是一个新的字段,导致语法错误。
select a.*, b.name activityName, c.name productName, c.member_max memberMax, d.status as complete, group_concat(if(e.face_value is null, "", e.face_value) separator "\n") as rewardAmount, group_concat(if(e.coupon_code is null, "", e.coupon_code ) separator "\n") as couponCode , group_concat(if(e.coupon_id is null, "", e.coupon_id) separator "\n") as caId from marketing_group_tool_group_member a left join marketing_group_tool_group_info d on a.group_id = d.id left join marketing_group_tool_activity b on a.activity_id = b.activity_id left join marketing_group_tool_product_base c on a.product_id = c.product_id left join marketing_group_tool_send_coupon_record e on (a.group_id = e.group_id and a.card_no = e.card_no) left join wx_recommend_organization organization on b.organization_id = organization.id where ((organization.tree_id between 2002000000000000 and 2002999999999999) or (organization.tree_id between 1000000000000000 and 1999999999999999) or (organization.tree_id between 2000000000000000 and 2999999999999999) or (organization.tree_id between 3000000000000000 and 3999999999999999) or (organization.tree_id between 4000000000000000 and 4999999999999999) or (organization.tree_id between 6000000000000000 and 6999999999999999) or (organization.tree_id between 5000000000000000 and 5999999999999999) or (organization.tree_id between 10000000000000000 and 10999999999999999) or (organization.tree_id between 8000000000000000 and 8999999999999999) or (organization.tree_id between 9000000000000000 and 9999999999999999) or (organization.tree_id between 11000000000000000 and 11999999999999999) or (organization.tree_id between 12000000000000000 and 12999999999999999) or (organization.tree_id between 13000000000000000 and 13999999999999999) or (organization.tree_id between 14000000000000000 and 14999999999999999) or (organization.tree_id between 15000000000000000 and 15999999999999999) or (organization.tree_id between 16000000000000000 and 16999999999999999) or (organization.tree_id between 17000000000000000 and 17999999999999999) ) and 1 = 1 group by a.id, a.activity_id , a.group_id , a.product_id , a.activity_referral_code, a.product_referral_code , a.openid , a.unionid , a.nickname , a.head_img , a.mobile , a.is_sub_buy , a.is_sub_progress , a.is_sub_success , a.sort , a.card_no , a.create_time , a.is_received_notice , a.is_received_progress , a.is_received_success , b.name, c.name, c.member_max , d.status order by a.id desc limit 0,20;
这是一个比较复杂的 SQL 查询语句,有很多连表和条件。要想对其进行优化,需要结合具体的环境和数据情况进行分析。
这里提供一些常见的 SQL 优化建议:
1. 确保表上有合适的索引,包括主键、唯一键和常用查询条件的索引,可以通过 `explain` 命令来查看查询计划和索引使用情况。
2. 避免使用 `select *`,只选择需要的字段,可以减少数据量和网络传输开销。
3. 尽量避免使用 `group_concat`,这会导致 MySQL 在内部生成临时表,会消耗大量的内存和 CPU 时间,可以考虑在应用层进行拼接。
4. 将复杂查询拆分成多个简单查询,每个查询只涉及少量表和字段,可以利用缓存和减轻数据库负担。
5. 对于复杂的查询条件,可以考虑使用全文索引、分词和搜索引擎等技术,以提高查询效率和准确性。
总之,SQL 优化需要根据具体情况进行分析和实践,需要综合考虑数据量、表结构、索引设计、查询条件等多个因素。
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