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lenmore
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73 天前 回复了 Hozoy 创建的主题 › NAS › 最近比较火的国产免费 NAS 系统 fnOS，大家怎么看？ |
买了 unraid 正版，我认为 unraid 的存储模式是最适合家用的。
79 天前 回复了 zf1968 创建的主题 › MySQL › 技术问题， mysql， 如果某表某字段离散度很小，但分布及不均匀， 如仅有‘是’、’否‘两种数值， 但‘是’的数据可能仅为 100 个以内的数量， 全部数据有 100 万或更多， 现在需要查询状态为‘是’的数据，如何优化查询。 |
如果只查询 “是”，大胆的建索引吧，效率非常高。查询“否”，配合其他字段建组合索引，效率同样杠杠的。我们上亿的表都这么干，一点问题没有。
121 天前 回复了 SkywalkerJi 创建的主题 › 问与答 › 你们会在电子产品停产前屯几个为了自己未来替换吗？ |
囤了两个米动 1S 手表
135 天前 回复了 cesign 创建的主题 › 程序员 › raid0，有办法把一个盘(100G，实际只用了 20G)热迁移到另外一块盘(30G)吗？ |
如果大小不一的盘组逻辑盘，我理解你用的只是 LVM 。
LVM 是可以做到数据盘热迁移的。
参考：
https://www.thegeekdiary.com/centos-rhel-how-to-migrate-storage-lvm-with-pvmove-command/
LVM 是可以做到数据盘热迁移的。
参考：
https://www.thegeekdiary.com/centos-rhel-how-to-migrate-storage-lvm-with-pvmove-command/
242 天前 回复了 godloveplay 创建的主题 › 程序员 › 请问厂里面一物一码的二维码重复校验，一般怎么做？ |
没必要 redis 。几千万数据，建好索引，MySQL 没有任何问题。
278 天前 回复了 msmmbl 创建的主题 › 问与答 › mongo 自建高可用，一定是 3 台服务器起步吗 |
推荐 3 个节点
但是预算实在紧张，可以考虑 1 主 1 从 + 1 个 Arbiter ，参考： https://www.mongodb.com/docs/manual/core/replica-set-arbiter/
但是预算实在紧张，可以考虑 1 主 1 从 + 1 个 Arbiter ，参考： https://www.mongodb.com/docs/manual/core/replica-set-arbiter/
331 天前 回复了 NeverBelieveMe 创建的主题 › 程序员 › 现有数据库生成数据库文档的工具有哪些？ |
MySQL 可以试下这个，以前写的应付检查的……
导出成 excel ，去掉表头就行了。
SET @table_schema='test';
SELECT column_name, DATA_TYPE, COLUMN_COMMENT
FROM (
SELECT table_name, '' AS column_name, '' AS DATA_TYPE, '' AS COLUMN_COMMENT, -4 AS ORDINAL_POSITION FROM information_schema.tables WHERE table_schema=@table_schema
UNION
SELECT table_name, CONCAT('表名：', table_name) AS column_name, '' AS DATA_TYPE, '' AS COLUMN_COMMENT, -3 AS ORDINAL_POSITION FROM information_schema.tables WHERE table_schema=@table_schema
UNION
SELECT table_name, CONCAT('用途：', table_comment) AS column_name, '' AS DATA_TYPE, '' AS COLUMN_COMMENT, -2 AS ORDINAL_POSITION FROM information_schema.tables WHERE table_schema=@table_schema
UNION
SELECT table_name, '字段名' AS column_name, '字段类型' AS DATA_TYPE, '描述' AS COLUMN_COMMENT, -1 AS ORDINAL_POSITION FROM information_schema.tables WHERE table_schema=@table_schema
UNION
SELECT table_name, column_name, CONCAT(DATA_TYPE, CASE WHEN CHARACTER_MAXIMUM_LENGTH IS NOT NULL THEN CONCAT('(', CHARACTER_MAXIMUM_LENGTH, ')') WHEN NUMERIC_PRECISION IS NOT NULL THEN CONCAT('(',NUMERIC_PRECISION, CASE WHEN NUMERIC_SCALE>0 THEN CONCAT(',',NUMERIC_SCALE) ELSE '' END , ')') WHEN DATETIME_PRECISION > 0 THEN CONCAT('(', DATETIME_PRECISION, ')') ELSE '' END) AS DATA_TYPE, COLUMN_COMMENT,ORDINAL_POSITION FROM information_schema.columns WHERE table_schema=@table_schema
) AS t
ORDER BY table_name, ORDINAL_POSITION;
导出成 excel ，去掉表头就行了。
SET @table_schema='test';
SELECT column_name, DATA_TYPE, COLUMN_COMMENT
FROM (
SELECT table_name, '' AS column_name, '' AS DATA_TYPE, '' AS COLUMN_COMMENT, -4 AS ORDINAL_POSITION FROM information_schema.tables WHERE table_schema=@table_schema
UNION
SELECT table_name, CONCAT('表名：', table_name) AS column_name, '' AS DATA_TYPE, '' AS COLUMN_COMMENT, -3 AS ORDINAL_POSITION FROM information_schema.tables WHERE table_schema=@table_schema
UNION
SELECT table_name, CONCAT('用途：', table_comment) AS column_name, '' AS DATA_TYPE, '' AS COLUMN_COMMENT, -2 AS ORDINAL_POSITION FROM information_schema.tables WHERE table_schema=@table_schema
UNION
SELECT table_name, '字段名' AS column_name, '字段类型' AS DATA_TYPE, '描述' AS COLUMN_COMMENT, -1 AS ORDINAL_POSITION FROM information_schema.tables WHERE table_schema=@table_schema
UNION
SELECT table_name, column_name, CONCAT(DATA_TYPE, CASE WHEN CHARACTER_MAXIMUM_LENGTH IS NOT NULL THEN CONCAT('(', CHARACTER_MAXIMUM_LENGTH, ')') WHEN NUMERIC_PRECISION IS NOT NULL THEN CONCAT('(',NUMERIC_PRECISION, CASE WHEN NUMERIC_SCALE>0 THEN CONCAT(',',NUMERIC_SCALE) ELSE '' END , ')') WHEN DATETIME_PRECISION > 0 THEN CONCAT('(', DATETIME_PRECISION, ')') ELSE '' END) AS DATA_TYPE, COLUMN_COMMENT,ORDINAL_POSITION FROM information_schema.columns WHERE table_schema=@table_schema
) AS t
ORDER BY table_name, ORDINAL_POSITION;
2022-09-13 11:29:16 +08:00 回复了 hemingyang 创建的主题 › MySQL › 请问 SQL 怎么统计前四分之一的人数分数最大值，还有后四分之人数分数最大值？ |
用 percent_rank 窗口函数，然后对 pct 分组，统计出各组的平均分。
e.g.
select floor(pct*100 /25) as grp, avg(n)
from (
select n, percent_rank() over(order by n) as pct
from public.global_number order by n
) as t
group by floor(pct*100 /25)
order by grp
e.g.
select floor(pct*100 /25) as grp, avg(n)
from (
select n, percent_rank() over(order by n) as pct
from public.global_number order by n
) as t
group by floor(pct*100 /25)
order by grp
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