如何使用CTE将两个表分组
我有三个表（Oracle）：
sales_order
-------------
int so_key (pk)
int part_key (fk)
int condition_key (fk)
number unit_price
int qty_ordered
number unit_cost
date entry_date
quote
-------------
int q_key (pk)
int part_key (fk)
int condition_key (fk)
number unit_price
int qty_quoted
date entry_date
stock
-------------
int stock_key (pk)
int part_key (fk)
int condition (fk)
int qty_available
number unit_cost
这三个都有这两个表的外键引用：
part
-------------
int part_key (pk)
condition
-------------
int condition_key (pk)
我正在撰写一个查询，将数据汇总到按part和condition分组的行中。但是，我无法弄清楚如何按part和condition进行分组。以下是我仅按part分组的（功能）查询：
WITH
ctePart_Quotes AS
(
SELECT q.part_key
, COUNT(*) AS quotes_count
, SUM(q.unit_price * q.qty_quoted) AS quotes_amt_total
, SUM(q.qty_quoted) AS quotes_qty_total
FROM quote q
WHERE q.entry_date BETWEEN TO_DATE('01-Jan-2011', 'dd-mm-yyyy') AND TO_DATE('31-Dec-2011', 'dd-mm-yyyy')
GROUP BY q.part_key
)
, ctePart_Sales AS
(
SELECT so.part_key
, COUNT(*) AS sales_count
, SUM(so.unit_price * so.qty_ordered) AS sales_amt_total
, SUM(so.qty_ordered) AS sales_qty_total
, SUM(so.qty_ordered * so.unit_cost) AS cost_total
FROM sales_order so
WHERE so.entry_date BETWEEN TO_DATE('01-Jan-2011', 'dd-mm-yyyy') AND TO_DATE('31-Dec-2011', 'dd-mm-yyyy')
GROUP BY so.part_key
)
, ctePart_Stock AS
(
SELECT stm.part_key
, SUM(stm.qty_available) AS total_available
, SUM(stm.qty_available * stm.unit_cost) AS inv_cost
FROM stock stm
GROUP BY stm.part_key
)
SELECT p.part_key,
part_stock.total_available,
part_stock.inv_cost,
sales.sales_amt_total,
sales.sales_qty_total,
sales.sales_count,
sales.cost_total,
quotes.quotes_amt_total,
quotes.quotes_qty_total,
quotes.quotes_count
FROM parts p
LEFT OUTER JOIN ctePart_Quotes quotes
ON quotes.part_key = p.part_key
LEFT OUTER JOIN ctePart_Sales sales
ON sales.part_key = p.part_key
LEFT OUTER JOIN ctePart_Stock part_stock
ON part_stock.part_key = p.part_key
WHERE NOT(sales_amt_total IS NULL
AND sales_qty_total IS NULL
AND sales_count IS NULL
AND cost_total IS NULL
AND quotes_amt_total IS NULL
AND quotes_qty_total IS NULL
AND quotes_count IS NULL)
AND SALES_AMT_TOTAL > 10000
此查询生成此输出（按part_key分组的总计）：
part_key | total_available | inv_cost | sales_amt_total | ...
---------|-----------------|----------|-----------------| ...
234 | 59 | 4923.90 | 29403.48 | ...
185 | 21 | 192.64 | 9034.95 | ...
102 | 102 | 8738.34 | 50382.20 | ...
...
但我正在尝试修改查询以生成此项（总计按part_key和condition_key分组）：
part_key | condition_key | total_available | inv_cost | sales_amt_total | ...
---------|---------------|-----------------|----------|-----------------| ...
234 | 3 | 24 | 2360.50 | 16947.18 | ...
234 | 7 | 35 | 2563.40 | 12456.30 | ...
...
你是怎么做到的？
编辑：澄清：
复杂性在于：你如何join最终选择中的条件？因为您选择FROM part，但condition关系是通过其他表（sales_order等）。因此，您必须join通过每个表（LEFT OUTER JOIN condition cond ON quotes.condition_key = cond.condition_key等），但这些联接都是单独的列。
编辑＃2：有人提供了数据模型的良好形象，说明了部分/条件之间的（正确的，合法的）关系，但也解决了这个问题所面临的微妙复杂性：
3 个答案:
答案 0 :(得分：2)
这里的主要问题似乎是您的数据模型。将您的问题的表“描述”转换为DDL代码，并将其转换为关系模型（使用Oracle Datamodeler），我们发现如下所示：
DDL代码
create table part ( part_key number primary key ) ;
create table condition ( condition_key number primary key ) ;
create table sales_order (
so_key number generated always as identity start with 3000 primary key
, part_key number references part
, condition_key number references condition
, unit_price number
, qty_ordered number
, unit_cost number
, entry_date date ) ;
create table quote (
q_key number generated always as identity start with 4000 primary key
, part_key number references part
, condition_key number references condition
, qty_quoted number
, unit_price number
, entry_date date );
create table stock (
stock_key number generated always as identity start with 5000 primary key
, part_key number references part
, condition_key number references condition
, qty_available number
, unit_cost number ) ;
关系模型（Oracle SQL Developer Data Modeler）
观察模型，很明显每个PART都有几个条件。因此，可能有必要（由您）决定您所指的是哪种情况。这可能并不容易。假设我们有一个部分（带有part_key）1000。现在，我们可以记录3个不同的条件，并为查询中提到的3个表中的每个表使用特定条件。
-- one part, 3 conditions
begin
insert into part ( part_key ) values ( 1000 ) ;
insert into condition( condition_key ) values ( 2001 ) ;
insert into condition( condition_key ) values ( 2002 ) ;
insert into condition( condition_key ) values ( 2003 ) ;
insert into sales_order ( part_key, condition_key ) values ( 1000, 2001 ) ;
insert into quote ( part_key, condition_key ) values ( 1000, 2002 ) ;
insert into stock ( part_key, condition_key ) values ( 1000, 2003 ) ;
end ;
/
查询中应该使用3个条件中的哪一个？很难说。
-- not using WITH (subquery factoring) here - for clarity
select
P.part_key
, SO.condition_key
, Q.condition_key
, ST.condition_key
from part P
join sales_order SO on SO.part_key = P.part_key
join quote Q on Q.part_key = P.part_key
join stock ST on ST.part_key = P.part_key
;
-- output
PART_KEY CONDITION_KEY CONDITION_KEY CONDITION_KEY
1000 2001 2002 2003
嗯 - 我们可以选择其中一个条件，我们不能。但是，同一部分可能存在更多条件......
begin
insert into condition( condition_key ) values ( 2004 ) ;
insert into condition( condition_key ) values ( 2005 ) ;
insert into condition( condition_key ) values ( 2006 ) ;
insert into sales_order ( part_key, condition_key ) values ( 1000, 2004 ) ;
insert into quote ( part_key, condition_key ) values ( 1000, 2005 ) ;
insert into stock ( part_key, condition_key ) values ( 1000, 2006 ) ;
end ;
/
-- Same query as above now gives us:
PART_KEY CONDITION_KEY CONDITION_KEY CONDITION_KEY
1000 2001 2005 2006
1000 2001 2005 2003
1000 2001 2002 2006
1000 2001 2002 2003
1000 2004 2005 2006
1000 2004 2005 2003
1000 2004 2002 2006
1000 2004 2002 2003
结论：修复您的数据模型。 （我们知道这有时说起来容易做起来难......）然后，对你的查询做更多的工作是有意义的。
<强> __更新__
既然我们知道无法对表和约束做任何事情，那么以下查询可能会给你一个起点。我们没有适当的测试数据，所以我们只需在表格中添加一些随机值...
-- PART and CONDITION -> 1000 integers each
begin
for i in 1 .. 1000
loop
insert into part ( part_key ) values ( i ) ;
insert into condition( condition_key ) values ( i ) ;
end loop;
end ;
/
表格引用
-- 2 12s, 2 18s
SQL> select * from quote ;
Q_KEY PART_KEY CONDITION_KEY QTY_QUOTED UNIT_PRICE ENTRY_DATE
4000 10 100 55 500 01-MAY-11
4001 12 120 55 500 01-MAY-11
4002 12 37 56 501 01-MAY-11
4003 14 140 55 500 01-MAY-11
4004 15 46 56 501 01-MAY-11
4005 16 160 55 500 01-MAY-11
4006 18 180 55 500 01-MAY-11
4007 18 55 56 501 01-MAY-11
4008 20 200 55 500 01-MAY-11
表SALES_ORDER
SQL> select * from sales_order ;
SO_KEY PART_KEY CONDITION_KEY UNIT_PRICE QTY_ORDERED UNIT_COST ENTRY_DATE
3000 10 100 500 55 400 05-MAY-11
3001 12 120 500 55 400 05-MAY-11
3002 14 140 500 55 400 05-MAY-11
3003 16 160 500 55 400 05-MAY-11
3004 18 180 500 55 400 05-MAY-11
3005 20 200 500 55 400 05-MAY-11
表格
SQL> select * from stock ;
STOCK_KEY PART_KEY CONDITION_KEY QTY_AVAILABLE UNIT_COST
5000 10 100 10 400
5001 12 120 10 400
5002 14 140 10 400
5003 14 100 12 402
5004 16 160 10 400
5005 18 180 10 400
5006 20 200 10 400
假设只记录有效的声部/条件组合，我们可以使用FULL OUTER JOIN来获得第一张照片。
SQL> select
2 Q.part_key q_part , Q.condition_key q_cond
3 , SO.part_key so_part, SO.condition_key so_cond
4 , ST.part_key st_part, ST.condition_key st_cond
5 from quote Q
6 full join sales_order SO
7 on SO.part_key = Q.part_key and SO.condition_key = Q.condition_key
8 full join stock ST
9 on ST.part_key = SO.part_key and ST.condition_key = SO.condition_key
10 ;
-- result
Q_PART Q_COND SO_PART SO_COND ST_PART ST_COND
10 100 10 100 10 100
12 120 12 120 12 120
12 37 NULL NULL NULL NULL
14 140 14 140 14 140
15 46 NULL NULL NULL NULL
16 160 16 160 16 160
18 180 18 180 18 180
18 55 NULL NULL NULL NULL
20 200 20 200 20 200
NULL NULL NULL NULL 14 100
然后，我们可以使用分析函数进行各种计算。请注意，我们这里不使用GROUP BY，分组是通过Q.part_key，Q.condition_key ...分区完成的（更多关于分析函数：Oracle documentation和示例here ）。
-- Skeleton query ...
-- Note that you will have need to write over(...) several times.
-- Add a WHERE clause and conditions as required.
select
Q.part_key as q_part, Q.condition_key as q_cond,
count( Q.part_key ) over ( partition by Q.part_key, Q.condition_key ) as q_count
--
-- Q example sums
-- , sum( Q.unit_price * Q.qty_quoted )
-- over ( partition by Q.part_key, Q.condition_key ) as qat -- quotes_amt_total
-- , sum( Q.qty_quoted )
-- over ( partition by Q.part_key, Q.condition_key ) as qqt -- quotes_qty_total
--
, SO.part_key as so_part, SO.condition_key as so_cond
, count( SO.part_key ) over ( partition by SO.part_key, SO.condition_key ) as so_count
--
-- SO sums here
--
, ST.part_key as st_part, ST.condition_key as st_cond
, count( ST.part_key ) over ( partition by ST.part_key, ST.condition_key ) as st_count
from sales_order SO
full join quote Q
on SO.part_key = Q.part_key and SO.condition_key = Q.condition_key
full join stock ST
on ST.part_key = SO.part_key and ST.condition_key = SO.condition_key
-- where ...
;
<强>结果
-- output
Q_PART Q_COND Q_COUNT SO_PART SO_COND SO_COUNT ST_PART ST_COND ST_COUNT
10 100 1 10 100 1 10 100 1
12 37 1 NULL NULL 0 NULL NULL 0
12 120 1 12 120 1 12 120 1
14 140 1 14 140 1 14 140 1
15 46 1 NULL NULL 0 NULL NULL 0
16 160 1 16 160 1 16 160 1
18 55 1 NULL NULL 0 NULL NULL 0
18 180 1 18 180 1 18 180 1
20 200 1 20 200 1 20 200 1
NULL NULL 0 NULL NULL 0 14 100 1
答案 1 :(得分：1)
诀窍是首先创建一个Carthesian产品（condition表只有~30行），可能以后抑制不需要的结果行：
这可能看起来不太理想，但它会避免COALESCE() d关键字段上的连接，这可能会表现不佳。
WITH
ctePart_Quotes AS
(
SELECT q.part_key, q.condition_key
, COUNT(*) AS quotes_count
, SUM(q.unit_price * q.qty_quoted) AS quotes_amt_total
, SUM(q.qty_quoted) AS quotes_qty_total
FROM quote q
WHERE q.entry_date BETWEEN TO_DATE('01-Jan-2011', 'dd-mm-yyyy') AND TO_DATE('31-Dec-2011', 'dd-mm-yyyy')
GROUP BY q.part_key, q.condition_key
)
, ctePart_Sales AS
(
SELECT so.part_key, so.condition_key
, COUNT(*) AS sales_count
, SUM(so.unit_price * so.qty_ordered) AS sales_amt_total
, SUM(so.qty_ordered) AS sales_qty_total
, SUM(so.qty_ordered * so.unit_cost) AS cost_total
FROM sales_order so
WHERE so.entry_date BETWEEN TO_DATE('01-Jan-2011', 'dd-mm-yyyy') AND TO_DATE('31-Dec-2011', 'dd-mm-yyyy')
GROUP BY so.part_key, so.condition_key
)
, ctePart_Stock AS
(
SELECT stm.part_key, stm.condition_key
, SUM(stm.qty_available) AS total_available
, SUM(stm.qty_available * stm.unit_cost) AS inv_cost
FROM stock stm
GROUP BY stm.part_key, stm.condition_key
)
SELECT p.part_key,
c.condition_key,
part_stock.total_available,
part_stock.inv_cost,
sales.sales_amt_total,
sales.sales_qty_total,
sales.sales_count,
sales.cost_total,
quotes.quotes_amt_total,
quotes.quotes_qty_total,
quotes.quotes_count
FROM parts p
CROSS JOIN condition c -- <<-- Here
LEFT OUTER JOIN ctePart_Quotes quotes
ON quotes.part_key = p.part_key
AND quotes.condition_key = c.condition_key -- <<-- Here
LEFT OUTER JOIN ctePart_Sales sales
ON sales.part_key = p.part_key
AND sales.condition_key = c.condition_key -- <<-- Here
LEFT OUTER JOIN ctePart_Stock part_stock
ON part_stock.part_key = p.part_key
AND part_stock.condition_key = c.condition_key -- <<-- Here
WHERE NOT(sales_amt_total IS NULL
AND sales_qty_total IS NULL
AND sales_count IS NULL
AND cost_total IS NULL
AND quotes_amt_total IS NULL
AND quotes_qty_total IS NULL
AND quotes_count IS NULL) -- <<-- And maybe Here, too
AND SALES_AMT_TOTAL > 10000
;
答案 2 :(得分：0)
也许这适合你：
WITH
ctePart_Quotes AS
(
SELECT q.part_key,
q.condition_key
, COUNT(*) AS quotes_count
, SUM(q.unit_price * q.qty_quoted) AS quotes_amt_total
, SUM(q.qty_quoted) AS quotes_qty_total
FROM quote q
WHERE q.entry_date BETWEEN TO_DATE('01-Jan-2011', 'dd-mm-yyyy') AND TO_DATE('31-Dec-2011', 'dd-mm-yyyy')
GROUP BY q.part_key,
q.condition_key
)
, ctePart_Sales AS
(
SELECT so.part_key,
so.condition_key
, COUNT(*) AS sales_count
, SUM(so.unit_price * so.qty_ordered) AS sales_amt_total
, SUM(so.qty_ordered) AS sales_qty_total
, SUM(so.qty_ordered * so.unit_cost) AS cost_total
FROM sales_order so
WHERE so.entry_date BETWEEN TO_DATE('01-Jan-2011', 'dd-mm-yyyy') AND TO_DATE('31-Dec-2011', 'dd-mm-yyyy')
GROUP BY so.part_key,
so.condition_key
)
, ctePart_Stock AS
(
SELECT stm.part_key,
stm.condition_key
, SUM(stm.qty_available) AS total_available
, SUM(stm.qty_available * stm.unit_cost) AS inv_cost
FROM stock stm
GROUP BY stm.part_key,
stm.condition_key
)
SELECT p.part_key,
cte.condition_key,
cte.total_available,
cte.inv_cost,
cte.sales_amt_total,
cte.sales_qty_total,
cte.sales_count,
cte.cost_total,
cte.quotes_amt_total,
cte.quotes_qty_total,
cte.quotes_count
FROM parts p
LEFT OUTER JOIN (SELECT coalesce(quotes.part_key, sales.part_key, part_stock.part_key) part_key,
coalesce(quotes.condition_key, sales.condition_key, part_stock.condition_key) condition_key,
quotes.quotes_count,
quotes.quotes_amt_total,
quotes.quotes_qty_total,
sales.sales_count,
sales.sales_amt_total,
sales.sales_qty_total,
sales.cost_total,
part_stock.total_available,
part_stock.inv_cost
FROM ctePart_Quotes quotes
FULL JOIN ctePart_Sales sales
ON sales.part_key = quotes.part_key
AND sales.condition_key = quotes.condition_key
FULL JOIN ctePart_Stock part_stock
ON part_stock.part_key = sales.part_key
AND part_stock.condition_key = sales.condition_key) cte
ON cte.part_key = p.part_key
WHERE NOT(sales_amt_total IS NULL
AND cte.sales_qty_total IS NULL
AND cte.sales_count IS NULL
AND cte.cost_total IS NULL
AND cte.quotes_amt_total IS NULL
AND cte.quotes_qty_total IS NULL
AND cte.quotes_count IS NULL)
AND SALES_AMT_TOTAL > 10000;
它还在CTE中按condition_key进行分组。然后使用FULL JOIN将CTE coalesce放在一起，以补偿第一个表格中null或part_key的{{1}}值（但也许没有，如果其中一个表中存在的condition_key和part_key的每个组合也存在于相应的两个表中。）。然后使用condition_key将结果LEFT JOIN添加到part。
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