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MYSQL教程 MySQL利用profile分析慢sql详解（group left join效率高于子查询）

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使用profile来分析慢sql

mysql 的 sql 性能分析器主要用途是显示 sql 执行的整个过程中各项资源的使用情况。分析器可以更好的展示出不良 SQL 的性能问题所在。最近遇到一个查询比较慢的sql语句，用了子查询，大概需要0.8秒左右，这个消耗时间比较长，严重影响了性能，所以需要进行优化。单独查询单表或者子查询记录都很快，下面来看看详细的介绍。

开启profile

mysql> show profiles; -- 查看是否开启
Empty set, 1 warning (0.00 sec)

mysql> set profiling=1; -- 开启profile
Query OK, 0 rows affected, 1 warning (0.00 sec)

mysql> show profiles;
Empty set, 1 warning (0.00 sec)

mysql>

执行查询，方便profile跟踪记录

mysql> SELECT SQL_NO_CACHE
 ->     t1.amount,
 ->     t1.count,
 ->     t1.date ,
 ->     (SELECT (CONCAT(t2.APPROVE_ID,'|' ,t2.PATH)) AS RECEIPT FROM TB_BIS_MERCHANT_SETTLEMENT t2 WHERE t2.`MERCHANT_ID` = t1.`MERCHANT_ID` AND t2.`DATE`=t1.DATE AND t2.APPROVE_STATUS=5) AS receipts
 ->    FROM
 ->     TB_BIS_MERCHANT_TURNOVER t1
 ->    WHERE t1.MERCHANT_ID='64884DE062BC11E682B00017FA000202'
 ->         ORDER BY t1.date DESC
 -> 
 -> LIMIT 0,100;
+-----------+-------+----------+------------------------------------------------------------------------------------------------------------+
| amount | count | date  | receipts                         |
+-----------+-------+----------+------------------------------------------------------------------------------------------------------------+
| 15800.00 |  1 | 20170105 | 0DDFD555F93B45BEB0905B1E6DE89D29|img/20170602/k320qfb20j2.jpg |
| 1245.00 |  1 | 20170104 | 0DDFD555F93B45BEB0905B1E6DE89D29|img/20170602/13el0d5mrqa.jpg |
| 14766.00 |  4 | 20170103 | EC481757CFDB445092D16D6B616350C8|img/20170602/chjfmwj50u4.jpg |
| 32449.00 |  2 | 20170102 | 0DDFD555F93B45BEB0905B1E6DE89D29|img/20170602/14c3txb1ne2.jpg |
| 37246.00 |  5 | 20170101 | 0DDFD555F93B45BEB0905B1E6DE89D29|img/20170602/ysmtkoosaxy.jpg |
| 105094.00 |  2 | 20161231 | EC481757CFDB445092D16D6B616350C8|img/20170602/iwzymvvmcbd.jpg |
| 88032.00 |  3 | 20161230 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/xlm22jg0stq.jpg |
| 3845.00 |  1 | 20161229 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/lluzstqlgkw.jpg |
| 2118.00 |  4 | 20161228 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/ox4jssddq3y.jpg |
| 2980.00 |  1 | 20161227 | EC481757CFDB445092D16D6B616350C8|img/20170602/jrgsm22igp0.jpg |
| 1080.00 |  1 | 20161226 | 667E240C44B4469892C261CE9243A8C3|img/20170602/iu0cogddqyq.jpg |
| 2980.00 |  1 | 20161225 | 0DDFD555F93B45BEB0905B1E6DE89D29|img/20170602/5jpntz4tb00.jpg |
| 10201.00 |  1 | 20161224 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/btisissrsre.jpg |
| 3003.00 |  4 | 20161223 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/2d5owr5rcu0.jpg |
| 2698.00 |  1 | 20161222 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/lyhlh24b2gh.jpg |
| 990.00 |  1 | 20161221 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/kictghkeybd.jpg |
| 1427.00 |  1 | 20161220 | EC481757CFDB445092D16D6B616350C8|img/20170602/hqt1iymeboe.jpg |
| 2465.00 |  1 | 20161219 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/03eg4dl3gdd.jpg |
| 2360.00 |  1 | 20161218 | EC481757CFDB445092D16D6B616350C8|img/20170602/zhsop2qc2rv.jpg |
| 3998.00 |  1 | 20161217 | EC481757CFDB445092D16D6B616350C8|img/20170602/ifii3rdvorb.jpg |
|  0.00 |  0 | 20161216 | EC481757CFDB445092D16D6B616350C8|img/20170602/tksg1estpkg.jpg |
|  0.00 |  0 | 20161215 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/du0egzrcwkd.jpg |
| 9900.00 |  1 | 20161214 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/h0oktfzslce.jpg |
| 4320.00 |  1 | 20161213 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/zlvhs34ho0a.jpg |
| 8760.00 |  2 | 20161212 | EC481757CFDB445092D16D6B616350C8|img/20170602/nznlesagcne.jpg |
| 213335.00 |  4 | 20161211 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/jxxnux1ejdh.jpg |
| 47104.00 |  5 | 20161210 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/z0zpmwgu5tw.jpg |
| 6100.00 |  1 | 20161209 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/2enle32b4qr.jpg |
| 13515.00 |  2 | 20161208 | EC481757CFDB445092D16D6B616350C8|img/20170602/aibbgoem1my.jpg |
| 26769.00 |  4 | 20161207 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/agb5ox3dyq4.jpg |
|  0.00 |  0 | 20161206 | EC481757CFDB445092D16D6B616350C8|img/20170602/ubi3abs4cav.jpg |
|  0.00 |  0 | 20161205 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/joz4qzwbvd5.jpg |
| 20000.00 |  3 | 20161204 | EC481757CFDB445092D16D6B616350C8|img/20170602/banacvflpzo.jpg |
| 20275.00 |  4 | 20161203 | EC481757CFDB445092D16D6B616350C8|img/20170602/djzpe3wp4cu.jpg |
| 3988.00 |  1 | 20161202 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/tzr5h4v5pe0.jpg |
| 4460.00 |  1 | 20161201 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/bvorjtulkmf.jpg |
| 10498.00 |  2 | 20161130 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/xott511f2l5.jpg |
| 11080.00 |  2 | 20161129 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/yrsl0io4iat.jpg |
| 6100.00 |  1 | 20161128 | EC481757CFDB445092D16D6B616350C8|img/20170602/azmcqvpzo33.jpg |
| 5580.00 |  1 | 20161127 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/jqlafmhyn1e.jpg |
| 32630.00 |  2 | 20161126 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/ndwterunkv5.jpg |
| 9800.00 |  1 | 20161125 | EC481757CFDB445092D16D6B616350C8|img/20170602/ct4kinxy1mh.jpg |
| 32500.00 |  2 | 20161124 | EC481757CFDB445092D16D6B616350C8|img/20170602/zjey5sdk5sh.jpg |
| 2700.00 |  1 | 20161123 | EC481757CFDB445092D16D6B616350C8|img/20170602/qiamqxntk2d.jpg |
| 4580.00 |  1 | 20161122 | EC481757CFDB445092D16D6B616350C8|img/20170602/cf3g34f2mbx.jpg |
| 14120.00 |  1 | 20161121 | EC481757CFDB445092D16D6B616350C8|img/20170602/xx2typnadxd.jpg |
| 41510.00 |  2 | 20161120 | EC481757CFDB445092D16D6B616350C8|img/20170602/t5gwm2ldlsq.jpg |
| 7800.00 |  2 | 20161118 | C91D5E7905BA44C8A14045C9C228157F|img/20170602/2kpf0fkbrva.jpg |
+-----------+-------+----------+------------------------------------------------------------------------------------------------------------+
48 rows in set (0.75 sec)

mysql>

查看当前的profile记录，主要获得Query_ID值

mysql> show profiles;
+----------+------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Query_ID | Duration | Query                                                                          |
+----------+------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|  1 | 0.00009250 | show warning                                                                         |
|  2 | 0.00013125 | show warnings                                                                        |
|  3 | 0.00014375 | set profiling=1                                                                        |
|  4 | 0.75458525 | SELECT SQL_NO_CACHE
    t1.amount,
    t1.count,
    t1.date ,
     (SELECT (CONCAT(t2.APPROVE_ID,'|' ,t2.PATH)) AS RECEIPT FROM TB_BIS_MERCHANT_SETTLEMENT t2 WHERE t2.`MERCHANT_ID` = t1.`MERCHANT_ID` AND t2.`DATE`=t1.DATE AND t2.APPROVE_STATUS=5) AS r |
+----------+------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
4 rows in set, 1 warning (0.00 sec)

mysql>

查看刚才执行的Query_ID为4的跟踪记录

mysql> show profile for query 4;
+--------------------+----------+
| Status    | Duration |
+--------------------+----------+
| executing   | 0.000017 |
| Sending data  | 0.018048 |
| executing   | 0.000028 |
| Sending data  | 0.018125 |
| executing   | 0.000022 |
| Sending data  | 0.015749 |
| executing   | 0.000017 |
| Sending data  | 0.015633 |
| executing   | 0.000017 |
| Sending data  | 0.015382 |
| executing   | 0.000015 |
| Sending data  | 0.015707 |
| executing   | 0.000023 |
| Sending data  | 0.015890 |
| executing   | 0.000022 |
| Sending data  | 0.015908 |
| executing   | 0.000017 |
| Sending data  | 0.015761 |
| executing   | 0.000022 |
| Sending data  | 0.015542 |
| executing   | 0.000014 |
| Sending data  | 0.015561 |
| executing   | 0.000016 |
| Sending data  | 0.015546 |
| executing   | 0.000037 |
| Sending data  | 0.015555 |
| executing   | 0.000015 |
| Sending data  | 0.015779 |
| executing   | 0.000026 |
| Sending data  | 0.015815 |
| executing   | 0.000015 |
| Sending data  | 0.015468 |
| executing   | 0.000015 |
| Sending data  | 0.015457 |
| executing   | 0.000015 |
| Sending data  | 0.015457 |
| executing   | 0.000014 |
| Sending data  | 0.015500 |
| executing   | 0.000014 |
| Sending data  | 0.015557 |
| executing   | 0.000015 |
| Sending data  | 0.015537 |
| executing   | 0.000014 |
| Sending data  | 0.015395 |
| executing   | 0.000021 |
| Sending data  | 0.015416 |
| executing   | 0.000014 |
| Sending data  | 0.015416 |
| executing   | 0.000014 |
| Sending data  | 0.015399 |
| executing   | 0.000023 |
| Sending data  | 0.015407 |
| executing   | 0.000014 |
| Sending data  | 0.015585 |
| executing   | 0.000014 |
| Sending data  | 0.015385 |
| executing   | 0.000014 |
| Sending data  | 0.015412 |
| executing   | 0.000014 |
| Sending data  | 0.015408 |
| executing   | 0.000014 |
| Sending data  | 0.015753 |
| executing   | 0.000014 |
| Sending data  | 0.015376 |
| executing   | 0.000014 |
| Sending data  | 0.015416 |
| executing   | 0.000019 |
| Sending data  | 0.015368 |
| executing   | 0.000014 |
| Sending data  | 0.015481 |
| executing   | 0.000015 |
| Sending data  | 0.015619 |
| executing   | 0.000015 |
| Sending data  | 0.015662 |
| executing   | 0.000016 |
| Sending data  | 0.015574 |
| executing   | 0.000015 |
| Sending data  | 0.015566 |
| executing   | 0.000015 |
| Sending data  | 0.015488 |
| executing   | 0.000013 |
| Sending data  | 0.015493 |
| executing   | 0.000015 |
| Sending data  | 0.015386 |
| executing   | 0.000015 |
| Sending data  | 0.015485 |
| executing   | 0.000018 |
| Sending data  | 0.015760 |
| executing   | 0.000014 |
| Sending data  | 0.015386 |
| executing   | 0.000015 |
| Sending data  | 0.015418 |
| executing   | 0.000014 |
| Sending data  | 0.015458 |
| end    | 0.000016 |
| query end   | 0.000019 |
| closing tables  | 0.000018 |
| freeing items  | 0.000825 |
| logging slow query | 0.000067 |
| cleaning up  | 0.000025 |
+--------------------+----------+
100 rows in set, 1 warning (0.00 sec)

mysql>

根据分析结果可以看到，有大量的Sending data消耗，而且是持续不断的，这样的可以判断为子查询导致的，所以在这个case里面，子查询不适合用，效率太低。那该用什么来避免呢？

用group by + left join 改写

mysql> SELECT SQL_NO_CACHE DISTINCT
 ->     t1.amount,
 ->     t1.count,
 ->     t1.date, GROUP_CONCAT(CONCAT(t2.APPROVE_ID,'|' ,t2.PATH)) AS RECEIPT 
 ->    FROM
 ->     TB_BIS_MERCHANT_TURNOVER t1 LEFT JOIN TB_BIS_MERCHANT_SETTLEMENT t2 ON t2.`MERCHANT_ID` = t1.`MERCHANT_ID` AND t2.`DATE`=t1.DATE AND t2.APPROVE_STATUS=5
 ->    WHERE t1.MERCHANT_ID='64884DE062BC11E682B00017FA000202'
 ->    GROUP BY t1.amount,
 ->     t1.count,
 ->     t1.date
 ->         ORDER BY t1.date DESC
 -> 
 -> LIMIT 0,100;
+-----------+-------+----------+------------------------------------------------------------------------------------------------------------+
| amount | count | date  | RECEIPT                         |
+-----------+-------+----------+------------------------------------------------------------------------------------------------------------+
| 15800.00 |  1 | 20170105 | 0DDFD555F93B45BEB0905B1E6DE89D29|img/20170602/k320qfb20j2.jpg |
| 1245.00 |  1 | 20170104 | 0DDFD555F93B45BEB0905B1E6DE89D29|img/20170602/13el0d5mrqa.jpg |
| 14766.00 |  4 | 20170103 | EC481757CFDB445092D16D6B616350C8|img/20170602/chjfmwj50u4.jpg |
| 32449.00 |  2 | 20170102 | 0DDFD555F93B45BEB0905B1E6DE89D29|img/20170602/14c3txb1ne2.jpg |
| 37246.00 |  5 | 20170101 | 0DDFD555F93B45BEB0905B1E6DE89D29|img/20170602/ysmtkoosaxy.jpg |
| 105094.00 |  2 | 20161231 | EC481757CFDB445092D16D6B616350C8|img/20170602/iwzymvvmcbd.jpg |
| 88032.00 |  3 | 20161230 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/xlm22jg0stq.jpg |
| 3845.00 |  1 | 20161229 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/lluzstqlgkw.jpg |
| 2118.00 |  4 | 20161228 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/ox4jssddq3y.jpg |
| 2980.00 |  1 | 20161227 | EC481757CFDB445092D16D6B616350C8|img/20170602/jrgsm22igp0.jpg |
| 1080.00 |  1 | 20161226 | 667E240C44B4469892C261CE9243A8C3|img/20170602/iu0cogddqyq.jpg |
| 2980.00 |  1 | 20161225 | 0DDFD555F93B45BEB0905B1E6DE89D29|img/20170602/5jpntz4tb00.jpg |
| 10201.00 |  1 | 20161224 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/btisissrsre.jpg |
| 3003.00 |  4 | 20161223 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/2d5owr5rcu0.jpg |
| 2698.00 |  1 | 20161222 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/lyhlh24b2gh.jpg |
| 990.00 |  1 | 20161221 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/kictghkeybd.jpg |
| 1427.00 |  1 | 20161220 | EC481757CFDB445092D16D6B616350C8|img/20170602/hqt1iymeboe.jpg |
| 2465.00 |  1 | 20161219 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/03eg4dl3gdd.jpg |
| 2360.00 |  1 | 20161218 | EC481757CFDB445092D16D6B616350C8|img/20170602/zhsop2qc2rv.jpg |
| 3998.00 |  1 | 20161217 | EC481757CFDB445092D16D6B616350C8|img/20170602/ifii3rdvorb.jpg |
|  0.00 |  0 | 20161216 | EC481757CFDB445092D16D6B616350C8|img/20170602/tksg1estpkg.jpg |
|  0.00 |  0 | 20161215 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/du0egzrcwkd.jpg |
| 9900.00 |  1 | 20161214 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/h0oktfzslce.jpg |
| 4320.00 |  1 | 20161213 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/zlvhs34ho0a.jpg |
| 8760.00 |  2 | 20161212 | EC481757CFDB445092D16D6B616350C8|img/20170602/nznlesagcne.jpg |
| 213335.00 |  4 | 20161211 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/jxxnux1ejdh.jpg |
| 47104.00 |  5 | 20161210 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/z0zpmwgu5tw.jpg |
| 6100.00 |  1 | 20161209 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/2enle32b4qr.jpg |
| 13515.00 |  2 | 20161208 | EC481757CFDB445092D16D6B616350C8|img/20170602/aibbgoem1my.jpg |
| 26769.00 |  4 | 20161207 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/agb5ox3dyq4.jpg |
|  0.00 |  0 | 20161206 | EC481757CFDB445092D16D6B616350C8|img/20170602/ubi3abs4cav.jpg |
|  0.00 |  0 | 20161205 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/joz4qzwbvd5.jpg |
| 20000.00 |  3 | 20161204 | EC481757CFDB445092D16D6B616350C8|img/20170602/banacvflpzo.jpg |
| 20275.00 |  4 | 20161203 | EC481757CFDB445092D16D6B616350C8|img/20170602/djzpe3wp4cu.jpg |
| 3988.00 |  1 | 20161202 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/tzr5h4v5pe0.jpg |
| 4460.00 |  1 | 20161201 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/bvorjtulkmf.jpg |
| 10498.00 |  2 | 20161130 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/xott511f2l5.jpg |
| 11080.00 |  2 | 20161129 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/yrsl0io4iat.jpg |
| 6100.00 |  1 | 20161128 | EC481757CFDB445092D16D6B616350C8|img/20170602/azmcqvpzo33.jpg |
| 5580.00 |  1 | 20161127 | 98FDB31FE4B04C21BC7EBE8A22981DA0|img/20170602/jqlafmhyn1e.jpg |
| 32630.00 |  2 | 20161126 | 2154FDCDA51A4257811F1EA886AACD14|img/20170602/ndwterunkv5.jpg |
| 9800.00 |  1 | 20161125 | EC481757CFDB445092D16D6B616350C8|img/20170602/ct4kinxy1mh.jpg |
| 32500.00 |  2 | 20161124 | EC481757CFDB445092D16D6B616350C8|img/20170602/zjey5sdk5sh.jpg |
| 2700.00 |  1 | 20161123 | EC481757CFDB445092D16D6B616350C8|img/20170602/qiamqxntk2d.jpg |
| 4580.00 |  1 | 20161122 | EC481757CFDB445092D16D6B616350C8|img/20170602/cf3g34f2mbx.jpg |
| 14120.00 |  1 | 20161121 | EC481757CFDB445092D16D6B616350C8|img/20170602/xx2typnadxd.jpg |
| 41510.00 |  2 | 20161120 | EC481757CFDB445092D16D6B616350C8|img/20170602/t5gwm2ldlsq.jpg |
| 7800.00 |  2 | 20161118 | C91D5E7905BA44C8A14045C9C228157F|img/20170602/2kpf0fkbrva.jpg |
+-----------+-------+----------+------------------------------------------------------------------------------------------------------------+
48 rows in set (0.15 sec)

mysql>

可以看到，执行时间变成了0.15秒，提升了5倍的效率。再看profile的跟踪分析。

mysql> show profile for query 8;
+-------------------------------+----------+
| Status      | Duration |
+-------------------------------+----------+
| starting      | 0.000125 |
| checking permissions   | 0.000015 |
| checking permissions   | 0.000014 |
| Opening tables    | 0.000029 |
| init       | 0.000055 |
| System lock     | 0.000020 |
| Waiting for query cache lock | 0.000013 |
| System lock     | 0.000050 |
| optimizing     | 0.000023 |
| statistics     | 0.000087 |
| preparing      | 0.000066 |
| Creating tmp table   | 0.000062 |
| Creating tmp table   | 0.000028 |
| Sorting result    | 0.000016 |
| executing      | 0.000012 |
| Sending data     | 0.148283 |
| Creating sort index   | 0.000342 |
| Creating sort index   | 0.000223 |
| end       | 0.000015 |
| query end      | 0.000046 |
| removing tmp table   | 0.000017 |
| query end      | 0.000012 |
| removing tmp table   | 0.000062 |
| query end      | 0.000015 |
| closing tables    | 0.000017 |
| freeing items     | 0.000019 |
| removing tmp table   | 0.000025 |
| freeing items     | 0.000016 |
| Waiting for query cache lock | 0.000012 |
| freeing items     | 0.000915 |
| Waiting for query cache lock | 0.000015 |
| freeing items     | 0.000011 |
| storing result in query cache | 0.000013 |
| cleaning up     | 0.000024 |
+-------------------------------+----------+
34 rows in set, 1 warning (0.00 sec)

mysql>

可以看到，只有一次| Sending data | 0.148283 |的消耗，所以效率提升很快。

扩展部分

SELECT 
 NAME,
 VALUE 
FROM
 v $ parameter 
WHERE NAME IN (
 'pga_aggregate_target',
 'sga_target'
 ) 
UNION
SELECT 
 'maximum PGA allocated' AS NAME,
 TO_CHAR (VALUE) AS VALUE 
FROM
 v $ pgastat 
WHERE NAME = 'maximum PGA allocated' ;

-- insert data
insert into t1 select 1,'a' from db1.t2;
call db1.proc_get_fints

总结

以上就是这篇文章的全部内容了，希望本文的内容对大家的学习或者工作能带来一定的帮助，如果有疑问大家可以留言交流，谢谢大家对80vps的支持。

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