创建测试数据
1 2 3 4 5 6 7 8 |
create table nayi224_180824(col_1 varchar2(10), col_2 varchar2(10), col_3 varchar2(10)); insert into nayi224_180824 select 1, 2, 3 from dual union all select 1, 2, 3 from dual union all select 5, 2, 3 from dual union all select 10, 20, 30 from dual ; commit ; select * from nayi224_180824; |
1 | 2 | 3 |
1 | 2 | 3 |
5 | 2 | 3 |
10 | 20 | 30 |
针对指定列,查出去重后的结果集
distinct
1 |
select distinct t1.* from nayi224_180824 t1; |
10 | 20 | 30 |
1 | 2 | 3 |
5 | 2 | 3 |
方法局限性很大,因为它只能对全部查询的列做去重。如果我想对col_2,col3去重,那我的结果集中就只能有col_2,col_3列,而不能有col_1列。
1 |
select distinct t1.col_2, col_3 from nayi224_180824 t1 |
2 | 3 |
20 | 30 |
不过它也是最简单易懂的写法。
row_number()
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select * from ( select t1.*, row_number() over(partition by t1.col_2, t1.col_3 order by 1) rn from nayi224_180824 t1) t1 where t1.rn = 1 ; |
1 | 2 | 3 | 1 |
10 | 20 | 30 | 1 |
写法上要麻烦不少,但是有更大的灵活性。
针对指定列,查出所有重复的行
count having
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select * from nayi224_180824 t where (t.col_2, t.col_3) in ( select t1.col_2, t1.col_3 from nayi224_180824 t1 group by t1.col_2, t1.col_3 having count (1) > 1) |
1 | 2 | 3 |
1 | 2 | 3 |
5 | 2 | 3 |
要查两次表,效率会比较低。不推荐。
count over
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select * from ( select t1.*, count (1) over(partition by t1.col_2, t1.col_3) rn from nayi224_180824 t1) t1 where t1.rn > 1 ; |
1 | 2 | 3 | 3 |
1 | 2 | 3 | 3 |
5 | 2 | 3 | 3 |
只需要查一次表,推荐。
删除所有重复的行
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delete from nayi224_180824 t where t.rowid in ( select rid from ( select t1.rowid rid, count (1) over(partition by t1.col_2, t1.col_3) rn from nayi224_180824 t1) t1 where t1.rn > 1); |
就是上面的语句稍作修改。
删除重复数据并保留一条
分析函数法
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delete from nayi224_180824 t where t.rowid in ( select rid from ( select t1.rowid rid, row_number() over(partition by t1.col_2, t1.col_3 order by 1) rn from nayi224_180824 t1) t1 where t1.rn > 1); |
拥有分析函数一贯的灵活性高的特点。可以为所欲为的分组,并通过改变orderby从句来达到像]保留最大id[这样的要求。
group by
1 2 3 |
delete from nayi224_180824 t where t.rowid not in ( select max (rowid) from nayi224_180824 t1 group by t1.col_2, t1.col_3); |
牺牲了一部分灵活性,换来了更高的效率。
总结
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原文链接:https://blog.csdn.net/nayi_224/article/details/82020913
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