MySQL-SQL基礎(chǔ)應(yīng)用(DQL基礎(chǔ)應(yīng)用--單表及多表查詢)

1、 select語句應(yīng)用

1.1 select（單表）的執(zhí)行邏輯

select   列1 , 列2 
from     表
where    條件
group by 條件
having   條件
order by 條件
limit    條件

1.2 select單表查詢

1> select單獨(dú)使用的情況（MySQL獨(dú)家）

（1）select @@參數(shù)名;
SELECT @@datadir; #查看數(shù)據(jù)存放的目錄

wenjuan[(none)]>SELECT @@datadir;
+------------------+
| @@datadir        |
+------------------+
| /data/3306/data/ |
+------------------+
1 row in set (0.00 sec)

wenjuan[(none)]>

SELECT @@port; #查看mysql的端口號(hào)

wenjuan[(none)]>SELECT @@port;
+--------+
| @@port |
+--------+
|   3306 |
+--------+
1 row in set (0.00 sec)

wenjuan[(none)]>

SELECT @@socket; #查看socket存放的目錄

wenjuan[(none)]>SELECT @@socket;
+-----------------+
| @@socket        |
+-----------------+
| /tmp/mysql.sock |
+-----------------+
1 row in set (0.00 sec)

wenjuan[(none)]>

SELECT @@innodb_flush_log_at_trx_commit;

wenjuan[(none)]>SELECT @@innodb_flush_log_at_trx_commit;
+----------------------------------+
| @@innodb_flush_log_at_trx_commit |
+----------------------------------+
|                                1 |
+----------------------------------+
1 row in set (0.00 sec)

wenjuan[(none)]>

SHOW VARIABLES LIKE '%trx%';

wenjuan[(none)]>SHOW VARIABLES LIKE '%trx%';
+--------------------------------+-------+
| Variable_name                  | Value |
+--------------------------------+-------+
| innodb_api_trx_level           | 0     |
| innodb_flush_log_at_trx_commit | 1     |
+--------------------------------+-------+
2 rows in set (0.00 sec)

wenjuan[(none)]>

SHOW VARIABLES; #513
（2）select 函數(shù)();
SELECT NOW(); 顯示當(dāng)前時(shí)間

wenjuan[(none)]>select now();
+---------------------+
| now()               |
+---------------------+
| 2019-08-08 09:44:17 |
+---------------------+
1 row in set (0.00 sec)

wenjuan[(none)]>

SELECT DATABASE(); 當(dāng)前在那個(gè)庫中

wenjuan[(none)]>use world;
Reading table information for completion of table and column names
You can turn off this feature to get a quicker startup with -A

Database changed
wenjuan[world]>select database();
+------------+
| database() |
+------------+
| world      |
+------------+
1 row in set (0.00 sec)

wenjuan[world]>

SELECT USER(); 當(dāng)前登錄的用戶

wenjuan[world]>SELECT USER(); 
+----------------+
| USER()         |
+----------------+
| root@localhost |
+----------------+
1 row in set (0.00 sec)

wenjuan[world]>

SELECT MONTH(NOW()); 顯示當(dāng)前月份

wenjuan[world]>SELECT MONTH(NOW());
+--------------+
| MONTH(NOW()) |
+--------------+
|            8 |
+--------------+
1 row in set (0.00 sec)

wenjuan[world]>

SELECT CONCAT(USER,"@",HOST) FROM mysql.user;

SELECT CONCAT("hello")  單獨(dú)使用沒什么意思，要結(jié)合多列才能顯示出效果

wenjuan[world]>SELECT CONCAT(USER,"@",HOST) FROM mysql.user;  
+-------------------------+
| CONCAT(USER,"@",HOST)   |
+-------------------------+
| root@10.0.0.%           |
| wwj@10.0.0.%            |
| wordpress@172.16.1.%    |
| mysql.session@localhost |
| mysql.sys@localhost     |
| root@localhost          |
+-------------------------+
6 rows in set (0.00 sec)

wenjuan[world]>

SELECT GROUP_CONCAT(USER,"@",HOST) FROM mysql.user; 列轉(zhuǎn)行

wenjuan[world]>SELECT GROUP_CONCAT(USER,"@",HOST) FROM mysql.user; 
+------------------------------------------------------------------------------------------------------------+
| GROUP_CONCAT(USER,"@",HOST)                                                                                |
+------------------------------------------------------------------------------------------------------------+
| root@10.0.0.%,wwj@10.0.0.%,wordpress@172.16.1.%,mysql.session@localhost,mysql.sys@localhost,root@localhost |
+------------------------------------------------------------------------------------------------------------+
1 row in set (0.00 sec)

wenjuan[world]>

2> from子句使用

（1）SELECT * FROM city;
相當(dāng)于Linux中的 cat /etc/passwd 等
（2）SELECT NAME,countrycode FROM city;
相當(dāng)于Linux中的awk取列

3> where子句應(yīng)用

（1）等值查詢
##查詢中國的城市信息抒寂？

wenjuan[world]>SELECT * FROM city WHERE CountryCode='CHN';
+------+---------------------+-------------+----------------+------------+
| ID   | Name                | CountryCode | District       | Population |
+------+---------------------+-------------+----------------+------------+
| 1890 | Shanghai            | CHN         | Shanghai       |    9696300 |
| 1891 | Peking              | CHN         | Peking         |    7472000 |
| 1892 | Chongqing           | CHN         | Chongqing      |    6351600 |
省略……

（2）不等值查詢

一般用于數(shù)字列查詢

##查詢?nèi)丝跀?shù)量小于100人的城市履澳？

wenjuan[world]>SELECT * FROM city WHERE population<100;
+------+-----------+-------------+----------+------------+
| ID   | Name      | CountryCode | District | Population |
+------+-----------+-------------+----------+------------+
| 2912 | Adamstown | PCN         | –        |         42 |
+------+-----------+-------------+----------+------------+
1 row in set (0.00 sec)

wenjuan[world]>

##查詢id小于10的城市信息？

wenjuan[world]>SELECT * FROM city WHERE id<10;
+----+----------------+-------------+---------------+------------+
| ID | Name           | CountryCode | District      | Population |
+----+----------------+-------------+---------------+------------+
|  1 | Kabul          | AFG         | Kabol         |    1780000 |
|  2 | Qandahar       | AFG         | Qandahar      |     237500 |
|  3 | Herat          | AFG         | Herat         |     186800 |
|  4 | Mazar-e-Sharif | AFG         | Balkh         |     127800 |
|  5 | Amsterdam      | NLD         | Noord-Holland |     731200 |
|  6 | Rotterdam      | NLD         | Zuid-Holland  |     593321 |
|  7 | Haag           | NLD         | Zuid-Holland  |     440900 |
|  8 | Utrecht        | NLD         | Utrecht       |     234323 |
|  9 | Eindhoven      | NLD         | Noord-Brabant |     201843 |
+----+----------------+-------------+---------------+------------+
9 rows in set (0.00 sec)

wenjuan[world]>

##查詢世界上不是中國的城市信息慌洪？

wenjuan[world]>SELECT * FROM city WHERE countryCode!='CHN';
+------+------------------------------------+-------------+------------------------+------------+
| ID   | Name                               | CountryCode | District               | Population |
+------+------------------------------------+-------------+------------------------+------------+
|    1 | Kabul                              | AFG         | Kabol                  |    1780000 |
|    2 | Qandahar                           | AFG         | Qandahar               |     237500 |
|    3 | Herat                              | AFG         | Herat                  |     186800 |
……

注意：盡量不使用不等于策严，可能不走索引穗慕，影響效率
（3）模糊查詢
##查詢國家代號(hào)為CH打頭的城市信息？

wenjuan[world]>SELECT * FROM city WHERE countryCode LIKE 'CH%';
+------+---------------------+-------------+----------------+------------+
| ID   | Name                | CountryCode | District       | Population |
+------+---------------------+-------------+----------------+------------+
| 3245 | Zürich              | CHE         | Zürich         |     336800 |
| 3246 | Geneve              | CHE         | Geneve         |     173500 |
| 3247 | Basel               | CHE         | Basel-Stadt    |     166700 |
| 3248 | Bern                | CHE         | Bern           |     122700 |
| 3249 | Lausanne            | CHE         | Vaud           |     114500 |
|  554 | Santiago de Chile   | CHL         | Santiago       |    4703954 |
|  555 | Puente Alto         | CHL         | Santiago       |     386236 |
……

注意：避免使用like中前面帶%的模糊查詢
（4）邏輯連接符（and妻导，or）
##查詢中國城市人口超過500萬的城市信息逛绵？

wenjuan[world]>SELECT * FROM city WHERE countryCode='CHN' AND population>5000000;
+------+-----------+-------------+-----------+------------+
| ID   | Name      | CountryCode | District  | Population |
+------+-----------+-------------+-----------+------------+
| 1890 | Shanghai  | CHN         | Shanghai  |    9696300 |
| 1891 | Peking    | CHN         | Peking    |    7472000 |
| 1892 | Chongqing | CHN         | Chongqing |    6351600 |
| 1893 | Tianjin   | CHN         | Tianjin   |    5286800 |
+------+-----------+-------------+-----------+------------+
4 rows in set (0.00 sec)

wenjuan[world]>

##查看山東省或河北省的城市信息？

wenjuan[world]>SELECT * FROM city WHERE District='shandong' OR District='hebei';
+------+--------------+-------------+----------+------------+
| ID   | Name         | CountryCode | District | Population |
+------+--------------+-------------+----------+------------+
| 1903 | Qingdao      | CHN         | Shandong |    2596000 |
| 1904 | Jinan        | CHN         | Shandong |    2278100 |
| 1907 | Shijiazhuang | CHN         | Hebei    |    2041500 |
| 1921 | Zibo         | CHN         | Shandong |    1140000 |
| 1924 | Tangshan     | CHN         | Hebei    |    1040000 |
| 1928 | Handan       | CHN         | Hebei    |     840000 |
| 1948 | Zhangjiakou  | CHN         | Hebei    |     530000 |
| 1955 | Baoding      | CHN         | Hebei    |     483155 |
| 1960 | Yantai       | CHN         | Shandong |     452127 |
…………

##查詢?nèi)丝跀?shù)量在500萬到600萬的城市倔韭？

wenjuan[world]>SELECT * FROM city WHERE population>5000000 AND population<6000000;
+------+----------------+-------------+----------------+------------+
| ID   | Name           | CountryCode | District       | Population |
+------+----------------+-------------+----------------+------------+
|  207 | Rio de Janeiro | BRA         | Rio de Janeiro |    5598953 |
| 1893 | Tianjin        | CHN         | Tianjin        |    5286800 |
| 2298 | Kinshasa       | COD         | Kinshasa       |    5064000 |
| 2823 | Lahore         | PAK         | Punjab         |    5063499 |
+------+----------------+-------------+----------------+------------+
4 rows in set (0.00 sec)

wenjuan[world]>

（5）where配合between……and……使用
##查詢?nèi)丝跀?shù)量在500萬到600萬的城市信息（包含500萬到600萬）术浪？

wenjuan[world]>SELECT * FROM city WHERE population BETWEEN 5000000 AND 6000000;
+------+----------------+-------------+----------------+------------+
| ID   | Name           | CountryCode | District       | Population |
+------+----------------+-------------+----------------+------------+
|  207 | Rio de Janeiro | BRA         | Rio de Janeiro |    5598953 |
| 1893 | Tianjin        | CHN         | Tianjin        |    5286800 |
| 2298 | Kinshasa       | COD         | Kinshasa       |    5064000 |
| 2823 | Lahore         | PAK         | Punjab         |    5063499 |
+------+----------------+-------------+----------------+------------+
4 rows in set (0.00 sec)

wenjuan[world]>

（6）where配合in使用
##查看山東省或河北省的城市信息？

SELECT * FROM city WHERE District IN ('shandong','hebei');

注意：in 對(duì)應(yīng)相反的是 not in寿酌，但盡量不要使用胰苏，不走索引

4>group by分組子句+聚合函數(shù)應(yīng)用

（1）什么是分組？
按照某個(gè)列進(jìn)行分組
（2）常用的聚合函數(shù)

COUNT()：計(jì)數(shù)
MAX()：最大值
MIN()：最小值
AVG()：平均值
SUM()：求和
GROUP_CONCAT()：列轉(zhuǎn)行

（3）實(shí)例：
##統(tǒng)計(jì)每個(gè)國家的城市個(gè)數(shù)醇疼？

wenjuan[world]>SELECT CountryCode,COUNT(id) FROM city GROUP BY CountryCode;
+-------------+-----------+
| CountryCode | COUNT(id) |
+-------------+-----------+
| ABW         |         1 |
| AFG         |         4 |
| AGO         |         5 |
| AIA         |         2 |
| ALB         |         1 |
…………

##統(tǒng)計(jì)每個(gè)國家的總?cè)丝跀?shù)硕并？

wenjuan[world]>SELECT CountryCode,SUM(population) FROM city GROUP BY CountryCode;
+-------------+-----------------+
| CountryCode | SUM(population) |
+-------------+-----------------+
| ABW         |           29034 |
| AFG         |         2332100 |
| AGO         |         2561600 |
| AIA         |            1556 |
| ALB         |          270000 |
| AND         |           21189 |
…………

##統(tǒng)計(jì)中國每個(gè)省的城市個(gè)數(shù)及省總?cè)丝跀?shù)？

wenjuan[world]>SELECT District,COUNT(NAME),SUM(population) FROM city WHERE countryCode='CHN'  GROUP BY District;
+----------------+-------------+-----------------+
| District       | COUNT(NAME) | SUM(population) |
+----------------+-------------+-----------------+
| Anhui          |          16 |         5141136 |
| Chongqing      |           1 |         6351600 |
| Fujian         |          12 |         3575650 |
| Gansu          |           7 |         2462631 |
| Guangdong      |          20 |         9510263 |
| Guangxi        |           9 |         2925142 |
| Guizhou        |           6 |         2512087 |
| Hainan         |           2 |          557120 |
…………

##統(tǒng)計(jì)各個(gè)國家的城市名列表秧荆？

wenjuan[world]>SELECT CountryCode,GROUP_CONCAT(NAME) FROM city GROUP BY CountryCode;
| CountryCode | GROUP_CONCAT(NAME) |
| ABW         | Oranjestad                        |                           | AFG         | Kabul,Qandahar,Herat,Mazar-e-Sharif                         |
| ARE         | Dubai,Abu Dhabi,Sharja,al-Ayn,Ajman |
…………

5> having語句

##統(tǒng)計(jì)中國每個(gè)省的城市個(gè)數(shù)及省總?cè)丝跀?shù)倔毙，只顯示人口總數(shù)大于800萬的省乙濒？

wenjuan[world]>SELECT District,COUNT(NAME),SUM(population) FROM city WHERE countryCode='CHN'  GROUP BY District HAVING SUM(population)>8000000;
+--------------+-------------+-----------------+
| District     | COUNT(NAME) | SUM(population) |
+--------------+-------------+-----------------+
| Guangdong    |          20 |         9510263 |
| Heilongjiang |          21 |        11628057 |
| Hubei        |          22 |         8547585 |
| Jiangsu      |          25 |         9719860 |
| Liaoning     |          21 |        15079174 |
| Shandong     |          32 |        12114416 |
| Shanghai     |           1 |         9696300 |
+--------------+-------------+-----------------+
7 rows in set (0.00 sec)

wenjuan[world]>

6> order b子句

##統(tǒng)計(jì)中國每個(gè)省的城市個(gè)數(shù)及省總?cè)丝跀?shù)陕赃，只顯示人口總數(shù)大于800萬的省，并進(jìn)行從大到小排序？

wenjuan[world]>SELECT District,COUNT(NAME),SUM(population) FROM city WHERE countryCode='CHN'  GROUP BY District HAVING SUM(population)>8000000 ORDER BY SUM(population) DESC;
+--------------+-------------+-----------------+
| District     | COUNT(NAME) | SUM(population) |
+--------------+-------------+-----------------+
| Liaoning     |          21 |        15079174 |
| Shandong     |          32 |        12114416 |
| Heilongjiang |          21 |        11628057 |
| Jiangsu      |          25 |         9719860 |
| Shanghai     |           1 |         9696300 |
| Guangdong    |          20 |         9510263 |
| Hubei        |          22 |         8547585 |
+--------------+-------------+-----------------+
7 rows in set (0.00 sec)

wenjuan[world]>

##查詢中國所有城市信息凯正，并以人口數(shù)降序輸出？

wenjuan[world]>SELECT * FROM city WHERE District='shandong' UNION ALL SELECT * FROM city WHERE District='hebei';
+------+--------------+-------------+----------+------------+
| ID   | Name         | CountryCode | District | Population |
+------+--------------+-------------+----------+------------+
| 1903 | Qingdao      | CHN         | Shandong |    2596000 |
| 1904 | Jinan        | CHN         | Shandong |    2278100 |
| 1921 | Zibo         | CHN         | Shandong |    1140000 |
| 1960 | Yantai       | CHN         | Shandong |     452127 |
| 1963 | Weifang      | CHN         | Shandong |     428522 |
| 1977 | Zaozhuang    | CHN         | Shandong |     380846 |
| 1991 | Tai′an       | CHN         | Shandong |     350696 |
…………

7> limit應(yīng)用

1> 語法：

LIMIT M  offet N 
LIMIT N,M
-- 跳過前N行,顯示M行(N和M代表的是數(shù)字)

2> 實(shí)例：
##查詢中國所有城市信息豌蟋，并以人口數(shù)降序輸出廊散，并只取前五名？

wenjuan[world]>SELECT * FROM city WHERE countryCode='CHN'   ORDER BY population DESC LIMIT 5;
+------+-----------+-------------+-----------+------------+
| ID   | Name      | CountryCode | District  | Population |
+------+-----------+-------------+-----------+------------+
| 1890 | Shanghai  | CHN         | Shanghai  |    9696300 |
| 1891 | Peking    | CHN         | Peking    |    7472000 |
| 1892 | Chongqing | CHN         | Chongqing |    6351600 |
| 1893 | Tianjin   | CHN         | Tianjin   |    5286800 |
| 1894 | Wuhan     | CHN         | Hubei     |    4344600 |
+------+-----------+-------------+-----------+------------+
5 rows in set (0.00 sec)

wenjuan[world]>

##查詢中國所有城市信息梧疲，并以人口數(shù)降序輸出允睹，并只第6到10名？

SELECT * FROM city WHERE countryCode='CHN'   ORDER BY population DESC LIMIT 5,5;
SELECT * FROM city WHERE countryCode='CHN'   ORDER BY population DESC LIMIT 5 OFFSET 5;

8> distinct應(yīng)用

##查詢所有的國家代碼信息

wenjuan[world]>SELECT DISTINCT countryCode FROM city;
+-------------+
| countryCode |
+-------------+
| ABW         |
| AFG         |
| AGO         |
| AIA         |
| ALB         |
…………

9> union和union all的應(yīng)用

查看山東省或河北省的城市信息幌氮？

wenjuan[world]>SELECT * FROM city WHERE District='shandong' UNION ALL SELECT * FROM city WHERE District='hebei';
+------+--------------+-------------+----------+------------+
| ID   | Name         | CountryCode | District | Population |
+------+--------------+-------------+----------+------------+
| 1903 | Qingdao      | CHN         | Shandong |    2596000 |
| 1904 | Jinan        | CHN         | Shandong |    2278100 |
| 1921 | Zibo         | CHN         | Shandong |    1140000 |
| 1960 | Yantai       | CHN         | Shandong |     452127 |
| 1963 | Weifang      | CHN         | Shandong |     428522 |
…………
| 1907 | Shijiazhuang | CHN         | Hebei    |    2041500 |
| 1924 | Tangshan     | CHN         | Hebei    |    1040000 |
| 1928 | Handan       | CHN         | Hebei    |     840000 |
| 1948 | Zhangjiakou  | CHN         | Hebei    |     530000 |
…………

注意：他們的性能高于or 或 in 的性能
union和union all的區(qū)別缭受？（面試題）
union帶有去重復(fù)的功能，union all沒有去重復(fù)的功能

1.3 select多表查詢

1> 作用

業(yè)務(wù)需要的數(shù)據(jù)來自多張表時(shí)该互，會(huì)使用到多表查詢

2> 多表連接類型

內(nèi)連接 *****
外鏈接 ***
全連接 *
笛卡爾

3>多表連接的基本語法（內(nèi)連接）

傳統(tǒng)連接 where  
自連接           
join uing      **
join on        *****

4> join on 的語法

查詢張三的家庭住址

SELECT A.name,B.address FROM
A JOIN  B
ON A.id=B.id
WHERE A.name='zhangsan'

多表連接的套路：

根據(jù)需求找到關(guān)聯(lián)表

找到表與標(biāo)的關(guān)聯(lián)列

列名調(diào)用時(shí),需要添加表前綴

5> 別名的使用

（1）表別名

一般是在 FROM的表的別名,或者join后的表的別名

在 where, group by ,select后的列,having,order by

（2）列別名

一般是在select后的列米者，定義的別名

作用：
??- 結(jié)果集顯示會(huì)以別名形式展示
??- 在hanving和order by 中可以調(diào)用列別名

6> 多表連接案例

（1）查詢?nèi)丝跀?shù)量少于100人的城市所在:國家名,國土面積,城市名,人口數(shù)

USE world;
DESC city;
DESC country;
SELECT    
country.name ,country.SurfaceArea,city.name,city.Population
FROM city  
JOIN country
ON city.CountryCode=country.code
WHERE city.Population<100;

（2）統(tǒng)計(jì)zhang3學(xué)習(xí)了幾門課程

SELECT student.sname ,COUNT(sc.sno)  課程數(shù)
FROM student
JOIN sc
ON student.sno=sc.sno
WHERE student.sname='li4';

（3）統(tǒng)計(jì)zhang3學(xué)習(xí)課程名稱

SELECT student.sname ,GROUP_CONCAT(course.cname)   課程名稱
FROM student
JOIN sc
ON student.sno=sc.sno
JOIN course
ON sc.cno=course.cno
WHERE student.sname='zhang3';

（4）oldguo老師教了學(xué)生的個(gè)數(shù)

SELECT th.tname,COUNT(st.sno) 個(gè)數(shù) FROM teacher AS th
JOIN course AS cr ON th.tno=cr.tno
JOIN sc ON cr.cno=sc.cno
JOIN student AS st ON sc.sno=st.sno
WHERE  tname='oldguo';

（5）每位老師所教課程的平均分,并按平均分排序

SELECT th.`tname` tname,cr.`cname` cname,cr.`cno` cno,AVG(sc.`score`) avg_score FROM teacher AS th
JOIN course AS cr ON th.tno=cr.tno
JOIN sc ON cr.cno=sc.cno
GROUP BY th.`tname`,cr.`cname`
ORDER BY avg_score DESC

（6）查詢oldguo所教的不及格的學(xué)生姓名

SELECT th.`tname`,st.`sname`,sc.`score` FROM teacher AS th
JOIN course AS cr ON th.tno=cr.tno
JOIN sc ON cr.cno=sc.cno
JOIN student AS st ON sc.sno=st.sno
WHERE score<60 AND tname='oldguo';

（7）查詢所有老師所教學(xué)生不及格的信息

SELECT th.tname 教師名稱,GROUP_CONCAT(st.sname) 不及格的學(xué)生 FROM teacher AS th
INNER JOIN course AS cr ON th.tno=cr.tno
INNER JOIN sc ON cr.cno=sc.cno
INNER JOIN student AS st ON sc.sno=st.sno
WHERE score<60
GROUP BY th.tname

最后編輯于：2019.08.13 19:15:44

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人面猴
序言：七十年代末，一起剝皮案震驚了整個(gè)濱河市宇智，隨后出現(xiàn)的幾起案子蔓搞，更是在濱河造成了極大的恐慌，老刑警劉巖随橘，帶你破解...
沈念sama閱讀 219,110評(píng)論 6贊 508
死咒
序言：濱河連續(xù)發(fā)生了三起死亡事件喂分，死亡現(xiàn)場離奇詭異，居然都是意外死亡机蔗，警方通過查閱死者的電腦和手機(jī)蒲祈，發(fā)現(xiàn)死者居然都...
沈念sama閱讀 93,443評(píng)論 3贊 395
救了他兩次的神仙讓他今天三更去死
文/潘曉璐我一進(jìn)店門，熙熙樓的掌柜王于貴愁眉苦臉地迎上來萝嘁，“玉大人梆掸，你說我怎么就攤上這事⊙姥裕” “怎么了沥潭？”我有些...
開封第一講書人閱讀 165,474評(píng)論 0贊 356
道士緝兇錄：失蹤的賣姜人
文/不壞的土叔我叫張陵，是天一觀的道長嬉挡。經(jīng)常有香客問我钝鸽，道長，這世上最難降的妖魔是什么庞钢？我笑而不...
開封第一講書人閱讀 58,881評(píng)論 1贊 295
?港島之戀（遺憾婚禮）
正文為了忘掉前任拔恰，我火速辦了婚禮，結(jié)果婚禮上基括，老公的妹妹穿的比我還像新娘颜懊。我一直安慰自己，他們只是感情好，可當(dāng)我...
茶點(diǎn)故事閱讀 67,902評(píng)論 6贊 392
惡毒庶女頂嫁案：這布局不是一般人想出來的
文/花漫我一把揭開白布河爹。她就那樣靜靜地躺著匠璧，像睡著了一般。火紅的嫁衣襯著肌膚如雪咸这。梳的紋絲不亂的頭發(fā)上夷恍，一...
開封第一講書人閱讀 51,698評(píng)論 1贊 305
城市分裂傳說
那天，我揣著相機(jī)與錄音媳维，去河邊找鬼酿雪。笑死，一個(gè)胖子當(dāng)著我的面吹牛侄刽，可吹牛的內(nèi)容都是我干的指黎。我是一名探鬼主播，決...
沈念sama閱讀 40,418評(píng)論 3贊 419
雙鴛鴦連環(huán)套：你想象不到人心有多黑
文/蒼蘭香墨我猛地睜開眼州丹，長吁一口氣：“原來是場噩夢(mèng)啊……” “哼醋安！你這毒婦竟也來了？” 一聲冷哼從身側(cè)響起墓毒，我...
開封第一講書人閱讀 39,332評(píng)論 0贊 276
萬榮殺人案實(shí)錄
序言：老撾萬榮一對(duì)情侶失蹤茬故，失蹤者是張志新（化名）和其女友劉穎，沒想到半個(gè)月后蚁鳖，有當(dāng)?shù)厝嗽跇淞掷锇l(fā)現(xiàn)了一具尸體磺芭，經(jīng)...
沈念sama閱讀 45,796評(píng)論 1贊 316
?護(hù)林員之死
正文獨(dú)居荒郊野嶺守林人離奇死亡，尸身上長有42處帶血的膿包…… 初始之章·張勛以下內(nèi)容為張勛視角年9月15日...
茶點(diǎn)故事閱讀 37,968評(píng)論 3贊 337
?白月光啟示錄
正文我和宋清朗相戀三年醉箕，在試婚紗的時(shí)候發(fā)現(xiàn)自己被綠了钾腺。大學(xué)時(shí)的朋友給我發(fā)了我未婚夫和他白月光在一起吃飯的照片。...
茶點(diǎn)故事閱讀 40,110評(píng)論 1贊 351
活死人
序言：一個(gè)原本活蹦亂跳的男人離奇死亡讥裤，死狀恐怖放棒，靈堂內(nèi)的尸體忽然破棺而出，到底是詐尸還是另有隱情己英，我是刑警寧澤间螟，帶...
沈念sama閱讀 35,792評(píng)論 5贊 346
?日本核電站爆炸內(nèi)幕
正文年R本政府宣布，位于F島的核電站损肛，受9級(jí)特大地震影響厢破，放射性物質(zhì)發(fā)生泄漏。R本人自食惡果不足惜治拿，卻給世界環(huán)境...
茶點(diǎn)故事閱讀 41,455評(píng)論 3贊 331
男人毒藥：我在死后第九天來索命
文/蒙蒙一摩泪、第九天我趴在偏房一處隱蔽的房頂上張望。院中可真熱鬧劫谅，春花似錦见坑、人聲如沸嚷掠。這莊子的主人今日做“春日...
開封第一講書人閱讀 32,003評(píng)論 0贊 22
一樁弒父案荞驴，背后竟有這般陰謀
文/蒼蘭香墨我抬頭看了看天上的太陽不皆。三九已至，卻和暖如春熊楼，著一層夾襖步出監(jiān)牢的瞬間霹娄，已是汗流浹背。一陣腳步聲響...
開封第一講書人閱讀 33,130評(píng)論 1贊 272
情欲美人皮
我被黑心中介騙來泰國打工孙蒙，沒想到剛下飛機(jī)就差點(diǎn)兒被人妖公主榨干…… 1. 我叫王不留项棠，地道東北人悲雳。一個(gè)月前我還...
沈念sama閱讀 48,348評(píng)論 3贊 373
代替公主和親
正文我出身青樓挎峦，卻偏偏與公主長得像，于是被迫代替她去往敵國和親合瓢。傳聞我的和親對(duì)象是個(gè)殘疾皇子坦胶，可洞房花燭夜當(dāng)晚...
茶點(diǎn)故事閱讀 45,047評(píng)論 2贊 355