当我使用具有数据类型为==>的param字段的yz表时出错CLOB。这是我的疑问:
WITH t AS
(SELECT x.order_id,x.customer_name,y.ncli,y.ndem2,y.ndem1,y.nd2,z.status_resume,y.nd1,yz.param
,MAX(y.seq) AS seq2
,MAX(y.extern_order_status) AS extern
FROM t_order_demand x
JOIN t_order_log y
ON x.order_id = y.order_id
JOIN p_catalog_status z
ON z.status_code_sc = y.extern_order_status
JOIN t_order_demand_eai yz
ON yz.order_id = y.order_id
AND y.order_id =1294
GROUP BY x.order_id,x.customer_name,y.ncli,y.ndem2,y.ndem1,y.nd2,y.nd1,z.status_resume,yz.param)
SELECT *
FROM t
WHERE (t.seq2 || t.extern) IN (SELECT MAX(tt.seq2 || tt.extern) FROM t tt)
这是错误:
ORA-00932: inconsistent datatypes: expected - got CLOB
00932. 00000 - "inconsistent datatypes: expected %s got %s"
任何人都可以帮我解决这个错误吗?感谢...
答案 0 :(得分:2)
最后我得到了答案,只需在select和group by中添加 dbms_lob.substr(yz.param,4000,1)。
WITH t AS
(SELECT x.order_id,x.customer_name,y.ncli,y.ndem2,y.ndem1,y.nd2,z.status_resume,y.nd1,dbms_lob.substr(yz.param,4000,1)
,MAX(y.seq) AS seq2
,MAX(y.extern_order_status) AS extern
FROM t_order_demand x
JOIN t_order_log y
ON x.order_id = y.order_id
JOIN p_catalog_status z
ON z.status_code_sc = y.extern_order_status
JOIN t_order_demand_eai yz
ON yz.order_id = x.order_id
AND y.order_id =1290
GROUP BY x.order_id,x.customer_name,y.ncli,y.ndem2,y.ndem1,y.nd2,y.nd1,z.status_resume,dbms_lob.substr(yz.param,4000,1))
SELECT *
FROM t
WHERE (t.seq2 || t.extern) IN (SELECT MAX(tt.seq2 || tt.extern) FROM t tt)
感谢您的回复
的固定强>
答案 1 :(得分:0)
WITH t AS
(SELECT x.order_id,x.customer_name,y.ncli,y.ndem2,y.ndem1,y.nd2,z.status_resume,y.nd1,yz.param
,MAX(y.seq) AS seq2
,MAX(y.extern_order_status) AS extern
FROM t_order_demand x
JOIN t_order_log y
ON x.order_id = y.order_id
JOIN p_catalog_status z
ON z.status_code_sc = y.extern_order_status
JOIN t_order_demand_eai yz
ON yz.order_id = y.order_id
AND y.order_id =1294
GROUP BY x.order_id,x.customer_name,y.ncli,y.ndem2,y.ndem1,y.nd2,y.nd1,z.status_resume)
SELECT *
FROM t
WHERE (t.seq2 || t.extern) IN (SELECT MAX(tt.seq2 || tt.extern) FROM t tt)
lob fields can not be used as a group by