从多个表中选择 count(*)

SELECT  (
        SELECT COUNT(*)
        FROM   tab1
        ) AS count1,
        (
        SELECT COUNT(*)
        FROM   tab2
        ) AS count2
FROM    dual

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作为附加信息，要在 SQL Server 中完成同样的事情，您只需删除查询的“FROM dual”部分。

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只是因为它略有不同：

SELECT 'table_1' AS table_name, COUNT(*) FROM table_1
UNION
SELECT 'table_2' AS table_name, COUNT(*) FROM table_2
UNION
SELECT 'table_3' AS table_name, COUNT(*) FROM table_3

它给出了转置的答案（每表一行而不是一列），否则我认为它没有太大不同。我认为在性能方面它们应该是等效的。

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我的经验是使用 SQL Server，但你能做到：

select (select count(*) from table1) as count1,
  (select count(*) from table2) as count2

在 SQL Server 中，我得到了你想要的结果。

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    select 
    t1.Count_1,t2.Count_2
    from 
(SELECT count(1) as Count_1 FROM tab1) as t1, 
(SELECT count(1) as Count_2 FROM tab2) as t2

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其他略有不同的方法：

with t1_count as (select count(*) c1 from t1),
     t2_count as (select count(*) c2 from t2)
select c1,
       c2
from   t1_count,
       t2_count
/

select c1,
       c2
from   (select count(*) c1 from t1) t1_count,
       (select count(*) c2 from t2) t2_count
/

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一个快速的尝试想出了：

Select (select count(*) from Table1) as Count1, (select count(*) from Table2) as Count2

注意：我在 SQL Server 中对此进行了测试，因此不需要 From Dual（因此存在差异）。

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为了完整起见 - 此查询将创建一个查询，为您提供给定所有者的所有表的计数。

select 
  DECODE(rownum, 1, '', ' UNION ALL ') || 
  'SELECT ''' || table_name || ''' AS TABLE_NAME, COUNT(*) ' ||
  ' FROM ' || table_name  as query_string 
 from all_tables 
where owner = :owner;

输出类似于

SELECT 'TAB1' AS TABLE_NAME, COUNT(*) FROM TAB1
 UNION ALL SELECT 'TAB2' AS TABLE_NAME, COUNT(*) FROM TAB2
 UNION ALL SELECT 'TAB3' AS TABLE_NAME, COUNT(*) FROM TAB3
 UNION ALL SELECT 'TAB4' AS TABLE_NAME, COUNT(*) FROM TAB4

然后你可以运行它来获得你的计数。有时它只是一个方便的脚本。

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因为我看不到任何其他答案提出这个问题。

如果您不喜欢子查询并且每个表中都有主键，您可以这样做：

select count(distinct tab1.id) as count_t1,
       count(distinct tab2.id) as count_t2
    from tab1, tab2

但在性能方面，我相信 Quassnoi 的解决方案更好，也是我会使用的解决方案。

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SELECT (SELECT COUNT(*) FROM table1) + (SELECT COUNT(*) FROM table2) FROM dual;

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下面是我的分享

选项 1 - 从不同表的相同域计数

select distinct(select count(*) from domain1.table1) "count1", (select count(*) from domain1.table2) "count2" 
from domain1.table1, domain1.table2;

选项 2 - 从同一个表的不同域计数

select distinct(select count(*) from domain1.table1) "count1", (select count(*) from domain2.table1) "count2" 
from domain1.table1, domain2.table1;

选项 3 - 使用“联合所有”从不同域对同一个表进行计数以具有计数行

select 'domain 1'"domain", count(*) 
from domain1.table1 
union all 
select 'domain 2', count(*) 
from domain2.table1;

享受 SQL，我总是这样做 :)

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select (select count(*) from tab1) count_1, (select count(*) from tab2) count_2 from dual;

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如果表（或至少一个键列）属于同一类型，只需先进行联合然后计数。

select count(*) 
  from (select tab1key as key from schema.tab1 
        union all 
        select tab2key as key from schema.tab2
       )

或者把你的satement放在它周围再放一个sum()。

select sum(amount) from
(
select count(*) amount from schema.tab1 union all select count(*) amount from schema.tab2
)

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--============= FIRST WAY (Shows as Multiple Row) ===============
SELECT 'tblProducts' [TableName], COUNT(P.Id) [RowCount] FROM tblProducts P
UNION ALL
SELECT 'tblProductSales' [TableName], COUNT(S.Id) [RowCount] FROM tblProductSales S


--============== SECOND WAY (Shows in a Single Row) =============
SELECT  
(SELECT COUNT(Id) FROM   tblProducts) AS ProductCount,
(SELECT COUNT(Id) FROM   tblProductSales) AS SalesCount

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Declare @all int
SET @all = (select COUNT(*) from tab1) + (select count(*) from tab2)
Print @all

或者

SELECT (select COUNT(*) from tab1) + (select count(*) from tab2)

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加入不同的表

SELECT COUNT(*) FROM (  
SELECT DISTINCT table_a.ID  FROM table_a JOIN table_c ON table_a.ID  = table_c.ID   );

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SELECT  (
        SELECT COUNT(*)
        FROM   tbl1
        )
        +
        (
        SELECT COUNT(*)
        FROM   tbl2
        ) 
    as TotalCount

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select (select count() from tab1 where field like 'value') + (select count() from tab2 where field like 'value') count

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select @count = sum(data) from
(
select count(*)  as data from #tempregion
union 
select count(*)  as data from #tempmetro
union
select count(*)  as data from #tempcity
union
select count(*)  as data from #tempzips
) a

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