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[转载]常见端口详解及攻击策略

2011-04-23 14:34 169 查看
分组查询

mysql> select countrycode as total fromCity where id<10;
+-------+
| total |
+-------+
| AFG |
| AFG |
| AFG |
| AFG |
| NLD |
| NLD |
| NLD |
| NLD |
| NLD |
+-------+
9 rows in set (0.00 sec)

mysql> select countrycode,count(*) astotal from City where id<10 group by countrycode;
+-------------+-------+
| countrycode | total |
+-------------+-------+
| AFG | 4 |
| NLD | 5 |
+-------------+-------+
2 rows in set (0.00 sec)

把相同的字段进行分组,并对分组内的数据进行统计。

使用having过滤分组

Having用于分组之后过滤数据,where用于分组之前选择数据。

mysql> select countrycode,count(*) astotal from City where id<101 group by countrycode;
+-------------+-------+
| countrycode | total |
+-------------+-------+
| AFG | 4 |
| AGO | 5 |
| AIA | 2 |
| ALB | 1 |
| AND | 1 |
| ANT | 1 |
| ARE | 5 |
| ARG | 32 |
| ASM | 2 |
| ATG | 1 |
| DZA | 18 |
| NLD | 28 |
+-------------+-------+
12 rows in set (0.01 sec)

mysql> select countrycode,count(*) astotal from City where id<101 group by countrycode having count(*)>10;
+-------------+-------+
| countrycode | total |
+-------------+-------+
| ARG | 32 |
| DZA | 18 |
| NLD | 28 |
+-------------+-------+
3 rows in set (0.00 sec)

先选择数据,然后分组,然后having过滤数据。

在group by后求和
mysql> select countrycode,count(*) astotal from City where id<10 group by countrycode with rollup;
+-------------+-------+
| countrycode | total |
+-------------+-------+
| AFG | 4 |
| NLD | 5 |
| NULL | 9 |
+-------------+-------+
3 rows in set (0.00 sec)

在最后增加一行显示求和结果。

多字段分组

先按照第一个字段进行分组,按照分组内容进行第二个字段的分组。

限制查询结果行数量

mysql> select * from City limit 3;
+----+----------+-------------+----------+------------+
| ID | Name | CountryCode | District | Population |
+----+----------+-------------+----------+------------+
| 1| Kabul | AFG | Kabol | 1780000 |
| 2| Qandahar | AFG | Qandahar| 237500 |
| 3| Herat | AFG | Herat | 186800 |
+----+----------+-------------+----------+------------+
3 rows in set (0.00 sec)

前3行

mysql> select * from City limit 10,10;
+----+-------------------+-------------+---------------+------------+
| ID | Name | CountryCode | District | Population |
+----+-------------------+-------------+---------------+------------+
| 11 | Groningen | NLD | Groningen | 172701 |
| 12 | Breda | NLD | Noord-Brabant | 160398 |
| 13 | Apeldoorn | NLD | Gelderland | 153491 |
| 14 | Nijmegen | NLD | Gelderland | 152463 |
| 15 | Enschede | NLD | Overijssel | 149544 |
| 16 | Haarlem | NLD | Noord-Holland | 148772 |
| 17 | Almere | NLD | Flevoland | 142465 |
| 18 | Arnhem | NLD | Gelderland | 138020 |
| 19 | Zaanstad | NLD | Noord-Holland | 135621 |
| 20 | 麓s-Hertogenbosch | NLD | Noord-Brabant | 129170 |
+----+-------------------+-------------+---------------+------------+
10 rows in set (0.00 sec)

从10开始往后的10行。

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