SQL难点解决：直观分组
1、 对位分组
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示例 1：按顺序分别列出使用 Chinese、English、French 作为官方语言的国家数量
MySQL8:
with t(name,ord) as (select 'Chinese',1
union all select 'English',2
union all select 'French',3)
select t.name, count(countrycode) cnt
from t left join world.countrylanguage s on t.name=s.language
where s.isofficial='T'
group by name,ord
order by ord;
注意：表的字符集和数据库会话的字符集要保持一致。
(1) show variables like 'character_set_connection'查看当前会话字符集
(2) show create table world.countrylanguage查看表的字符集
(3) set character_set_connection=[字符集]更新当前会话字符集
集算器SPL:
| A | |
| 1 | =connect("mysql") |
| 2 | =A1.query@x("select * from world.countrylanguage where isofficial='T'") |
| 3 | [Chinese,English,French] |
| 4 | =A2.align@a(A3,Language) |
| 5 | =A4.new(A3(#):name, ~.len():cnt) |
A1: 连接数据库
A2: 查询出所有官方语言的记录
A3: 需要列出的语言
A4: 将所有记录按Language对位到A3相应位置
A5: 构造以语言和使用此语言为官方语言的国家数量的序表
示例 2：按顺序分别列出使用 Chinese、English、French 及其它语言作为官方语言的国家数量
MySQL8:
with t(name,ord) as (select 'Chinese',1 union all select 'English',2
union all select 'French',3 union all select 'Other', 4),
s(name, cnt) as (
select language, count(countrycode) cnt
from world.countrylanguage s
where s.isofficial='T' and language in ('Chinese','English','French')
group by language
union all
select 'Other', count(distinct countrycode) cnt
from world.countrylanguage s
where isofficial='T' and language not in ('Chinese','English','French')
)
select t.name, s.cnt
from t left join s using (name)
order by t.ord;
集算器SPL:
| A | |
| 1 | =connect("mysql") |
| 2 | =A1.query@x("select * from world.countrylanguage where isofficial='T'") |
| 3 | [Chinese,English,French,Other] |
| 4 | =A2.align@an(A3.to(3),Language) |
| 5 | =A4.new(A3(#):name, if(#<=3,~.len(), ~.icount(CountryCode)):cnt) |
A4: 将所有记录按Language对位到A3.to(3)相应位置，并追加一组用于存放不能对位的记录
A5: 第4组计算不同CountryCode的数量
2、 枚举分组
示例 1：按顺序列出各类型城市的数量
MySQL8:
with t as (select * from world.city where CountryCode='CHN'),
segment(class,start,end) as (select 'tiny', 0, 200000
union all select 'small', 200000, 1000000
union all select 'medium', 1000000, 2000000
union all select 'big', 2000000, 100000000
)
select class, count(1) cnt
from segment s join t on t.population>=s.start and t.population group by class, start order by start; 集算器SPL: A3: ${…}宏替换，以大括号内表达式的结果作为新表达式进行计算，结果为序列["?<200000","?<1000000","?<2000000","?<100000000"] A5: 针对 A2 中每条记录，寻找 A3 中第 1 个成立的条件，并追加到对应的组中 示例 2：列出华东地区大型城市数量、其它地区大型城市数量、非大型城市数量 MySQL8: with t as (select * from world.city where CountryCode='CHN') select 'East&Big' class, count(*) cnt from t where population>=2000000 and district in ('Shanghai','Jiangshu', 'Shandong','Zhejiang','Anhui','Jiangxi') union all select 'Other&Big', count(*) from t where population>=2000000 and district not in ('Shanghai','Jiangshu','Shandong','Zhejiang','Anhui','Jiangxi') union all select 'Not Big', count(*) from t where population<2000000; 集算器SPL: A5: enum@n将不满足 A4 中所有条件的记录存放到追加的最后一组中 示例 3：列出所有地区大型城市数量、华东地区大型城市数量、非大型城市数量 MySQL8: with t as (select * from world.city where CountryCode='CHN') select 'Big' class, count(*) cnt from t where population>=2000000 union all select 'East&Big' class, count(*) cnt from t where population>=2000000 and district in ('Shanghai','Jiangshu','Shandong','Zhejiang','Anhui','Jiangxi') union all select 'Not Big' class, count(*) cnt from t where population<2000000; 集算器SPL: A6: 若A2中记录满足A4中多个条件时，enum@r会将其追加到对应的每个组中 3、 返回值直接作为序号进行定位分组 示例 1: 按顺序列出各类型城市的数量 MySQL8: 参见“枚举分组”中 SQL 集算器SPL: A5: 先计算 A2.Population 在 A3 中段号，然后根据段号进行定位分组 4、 原序保持下的相邻记录分组 示例 1: 列出前 10 届奥运金牌榜 (olympic 表中只有历届成绩前 3 名的信息，且没有奖牌完全相同的情况) MySQL8: with t1 as (select *,rank() over(partition by game order by gold*1000000+silver*1000+copper desc) rn from olympic where game<=10) select game,nation,gold,silver,copper from t1 where rn=1; 集算器SPL: A3: 按原序分到各组，每组取第 1 条记录组成新序表 示例 2: 求奥运会国家总成绩蝉联第 1 的最长届数 MySQL8: with t1 as (select *,rank() over(partition by game order by gold*1000000+silver*1000+copper desc) rn from olympic), t2 as (select game,ifnull(nation<>lag(nation) over(order by game),0)neq from t1 where rn=1), t3 as (select sum(neq) over(order by game) acc from t2), t4 as (select count(acc) cnt from t3 group by acc) select max(cnt) cnt from t4; t1: 求出成绩排名 t2: 列出历届第1名，并根据nation是否与上届不同置标志neq(不同置1，相同置0) t3: 累积标志neq到acc，可以保证相邻nation相同的acc相同，不相邻nation的acc不相同 集算器SPL: A4: 将相邻nation相同的记录按原序分到同组 A5: 求各组长度的最大值即最大届数 示例3：列出奥运会总成绩排名第一最长蝉联时的各届信息 MySQL: with t1 as (select *,rank() over(partition by game order by gold*1000000+silver*1000+copper desc) rn from olympic), t2 as (select *,ifnull(nation<>lag(nation) over(order by game),0)neq from t1 where rn=1), t3 as (select *, sum(neq) over(order by game) acc from t2), t4 as (select acc,count(acc) cnt from t3 group by acc), t5 as (select * from t4 where cnt=(select max(cnt) cnt from t4)) select game,nation,gold,silver,copper from t3 join t5 using (acc); 集算器SPL: A5: 求出长度最大组 示例 4：求奥运会前3名金牌总数连续增长的最大届数 MySQL8: with t1 as (select game,sum(gold) gold from olympic group by game), t2 as (select game,gold, gold<=lag(gold,1,-1) over(order by game) lt from t1), t3 as (select game, sum(lt) over(order by game) acc from t2), t4 as (select count(*) cnt from t3 group by acc) select max(cnt)-1 cnt from t4; 集算器SPL: A3: 根据条件值按原序分组，若gold小于等于上一个gold则产生新分组A 1 =connect("mysql") 2 =A1.query@x("select * from world.city where CountryCode='CHN'") 3 =${string([20,100,200,10000].(~*10000).("?<"/~))} 4 [tiny,small,medium,big] 5 =A2.enum(A3,Population) 6 =A5.new(A4(#):class, ~.len():cnt) 
A 1 =connect("mysql") 2 =A1.query@x("select * from world.city where CountryCode='CHN'") 3 [Shanghai,Jiangshu, Shandong,Zhejiang,Anhui,Jiangxi] 4 [?(1)>=2000000 && A3.contain(?(2)), ?(1)>=2000000 && !A3.contain(?(2))] 5 [East&Big,Other&Big, Not Big] 6 =A2.enum@n(A4, [Population,District]) 7 =A6.new(A5(#):class, A6(#).len():cnt) 
A 1 =connect("mysql") 2 =A1.query@x("select * from world.city where CountryCode='CHN'") 3 [Shanghai,Jiangshu, Shandong,Zhejiang,Anhui,Jiangxi] 4 [?(1)>=2000000, ?(1)>=2000000 && A3.contain(?(2))] 5 [Big, East&Big, Not Big] 6 =A2.enum@rn(A4, [Population,District]) 7 =A6.new(A5(#):class, A6(#).len():cnt) 
A 1 =connect("mysql") 2 =A1.query@x("select * from world.city where CountryCode='CHN'") 3 =[0,20,100,200].(~*10000) 4 [tiny,small,medium,big] 5 =A2.group@n(A3.pseg(Population)) 6 =A5.new(A4(#):class, ~.len():cnt) A 1 =connect("mysql") 2 =A1.query("select * from olympic where game<=10 order by game, gold*1000000+silver*1000+copper desc") 3 =A2.group@o1(game) 
A 1 =connect("mysql") 2 =A1.query("select * from olympic order by game, gold*1000000+silver*1000+copper desc") 3 =A2.group@o1(game) 4 =A3.group@o(nation) 5 =A4.max(~.len()) 
A 1 =connect("mysql") 2 =A1.query("select * from olympic order by game, gold*1000000+silver*1000+copper desc") 3 =A2.group@o1(game) 4 =A3.group@o(nation) 5 =A4.maxp(~.len()) 
A 1 =connect("mysql") 2 =A1.query("select game,sum(gold) gold from olympic group by game order by game") 3 =A2.group@i(gold<=gold[-1]) 4 =A3.max(~.len())-1 
新闻标题：SQL难点解决：直观分组
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