例如,str=select sum(InventoryQty) from test_oolislis where ProductCode='999',如何用SqlSugar用str查出一个值
时间: 2023-04-03 16:03:14 浏览: 55
可以使用以下代码来查询一个值:
var db = new SqlSugarClient(new ConnectionConfig()
{
ConnectionString = "your connection string",
DbType = DbType.SqlServer,
IsAutoCloseConnection = true,
InitKeyType = InitKeyType.Attribute
});
var result = db.Ado.GetScalar(str);
其中,"your connection string"需要替换为你的数据库连接字符串,result即为查询结果。
相关问题
cursor.execute("SELECT data FROM your_table WHERE label=?", (prediction_label,))
这是一个使用 Flask 和 MySQL 进行带有参数的查询的示例。假设你想根据 `prediction_label` 的值从 `your_table` 表中查询 `data` 列的数据。
```python
from flask import Flask
import mysql.connector
app = Flask(__name__)
# 连接到 MySQL 数据库
db = mysql.connector.connect(
host="localhost",
user="yourusername",
password="yourpassword",
database="yourdatabase"
)
@app.route("/")
def index():
# 创建一个游标对象
cursor = db.cursor()
# 执行带有参数的查询语句
prediction_label = "label_value" # 替换为你自己的预测标签值
query = "SELECT data FROM your_table WHERE label=%s"
cursor.execute(query, (prediction_label,))
result = cursor.fetchall()
# 处理查询结果
data = ""
for row in result:
data += str(row[0]) + "<br>"
return data
if __name__ == "__main__":
app.run()
```
请确保将 `yourusername`、`yourpassword`、`yourdatabase` 和 `your_table` 替换为你自己的数据库信息,并将 `"label_value"` 替换为你想要查询的具体标签值。
在上述示例中,我们通过在 SQL 查询语句中使用 `WHERE` 子句和参数化查询来实现带有参数的查询。然后,我们将查询结果处理并返回给用户。
请注意,这只是一个简单的示例,你可能需要根据实际情况进行更复杂的查询和错误处理。此外,确保对用户输入进行适当的验证和防止 SQL 注入攻击。
优化这段sql:SELECT `msisdn`, `relationship_account` AS relationshipAccount, '' AS relationshipName, IFNULL(SUM( `dual_time` ), 0) AS totalTime, IFNULL(COUNT(1), 0) AS totalCall, IFNULL(SUM(`local_action` = (SELECT status_description FROM dwd_t_code_value WHERE storage_status = '07')), 0) AS active, IFNULL(SUM(`local_action` = (SELECT status_description FROM dwd_t_code_value WHERE storage_status = '08')), 0) AS passive, IFNULL(SUM(`call_status` = (SELECT status_description FROM dwd_t_code_value WHERE storage_status = '09')), 0) AS success, IFNULL(SUM(`call_status` = (SELECT status_description FROM dwd_t_code_value WHERE storage_status = '10')), 0) AS fail, FROM_UNIXTIME(MIN(UNIX_TIMESTAMP(`start_time`))) AS onceCallTime, FROM_UNIXTIME(MAX(UNIX_TIMESTAMP(`start_time`))) AS endCallTime FROM `dwd_t_call_record` WHERE `person_no` = '653129200105072624' GROUP BY `relationship_account` ORDER BY `start_time` ASC
可以优化的地方有:
1. 子查询可以改为使用 JOIN,例如:
```
SELECT status_description
FROM dwd_t_code_value
WHERE storage_status = '07'
```
改为:
```
SELECT t2.status_description
FROM (
SELECT status_description, storage_status
FROM dwd_t_code_value
) t2
WHERE t2.storage_status = '07'
```
2. 使用 EXISTS 或者 IN 替换掉子查询,例如:
```
IFNULL(SUM(`local_action` = (SELECT status_description FROM dwd_t_code_value WHERE storage_status = '07')), 0) AS active
```
改为:
```
IFNULL(SUM(`local_action` IN (SELECT status_description FROM dwd_t_code_value WHERE storage_status = '07')), 0) AS active
```
或者:
```
IFNULL(SUM(EXISTS (SELECT 1 FROM dwd_t_code_value WHERE storage_status = '07' AND status_description = `local_action`)), 0) AS active
```
3. 可以考虑将 FROM_UNIXTIME 和 UNIX_TIMESTAMP 改为 DATE_FORMAT 和 STR_TO_DATE,以避免频繁的数据类型转换。
综上所述,优化后的 SQL 可能类似于以下内容:
```
SELECT
`msisdn`,
`relationship_account` AS relationshipAccount,
'' AS relationshipName,
IFNULL(SUM(`dual_time`), 0) AS totalTime,
IFNULL(COUNT(1), 0) AS totalCall,
IFNULL(SUM(`local_action` IN (SELECT status_description FROM dwd_t_code_value WHERE storage_status = '07')), 0) AS active,
IFNULL(SUM(`local_action` IN (SELECT status_description FROM dwd_t_code_value WHERE storage_status = '08')), 0) AS passive,
IFNULL(SUM(`call_status` IN (SELECT status_description FROM dwd_t_code_value WHERE storage_status = '09')), 0) AS success,
IFNULL(SUM(`call_status` IN (SELECT status_description FROM dwd_t_code_value WHERE storage_status = '10')), 0) AS fail,
DATE_FORMAT(MIN(STR_TO_DATE(`start_time`, '%Y-%m-%d %H:%i:%s')), '%Y-%m-%d %H:%i:%s') AS onceCallTime,
DATE_FORMAT(MAX(STR_TO_DATE(`start_time`, '%Y-%m-%d %H:%i:%s')), '%Y-%m-%d %H:%i:%s') AS endCallTime
FROM
`dwd_t_call_record`
WHERE
`person_no` = '653129200105072624'
GROUP BY
`relationship_account`
ORDER BY
`start_time` ASC
```