Pomelo.EntityFrameworkCore.MySql 升级到 7.0 后出现：
System.InvalidOperationException:“The 'sbyte' property could not be mapped to the database type 'tinyint(1)' because the database provider does not support mapping 'sbyte' properties to 'tinyint(1)' columns. Consider mapping to a different database type or converting the property value to a type supported by the database using a value converter. See https://aka.ms/efcore-docs-value-converters for more information. Alternately, exclude the property from the model using the '[NotMapped]' attribute or by using 'EntityTypeBuilder.Ignore' in 'OnModelCreating'.”
对比 6.0 生成的 DbContext.cs 发现缺少了 UseLoggerFactory，按旧版修改即可。
找到 OnConfiguring 方法，上方插入：
public static readonly LoggerFactory MyLoggerFactory = new LoggerFactory(new[] {
new DebugLoggerProvider()
});在 OnConfiguring 方法中将：
optionsBuilder.UseMySql("连接字符串");改为：
optionsBuilder.UseLoggerFactory(MyLoggerFactory).UseMySql("连接字符串");
下载 sqlmap：https://github.com/sqlmapproject/sqlmap
下载 python：https://www.python.org/downloads/
以 windows 版为例：
安装 python；
解压缩 sqlmap；
“在终端中打开 / 在命令行中打开” sqlmap.py 文件所在目录；
执行命令
python sqlmap.py -u "网址" --data="POST数据" --tables需要注意的是，sqlmap 会记录探测过的网址的结果信息，修复网站漏洞后要再次检测是否安全时，应删除缓存文件，位置在：
C:\Users\用户\AppData\Local\sqlmap\output\
论坛出现动态页面打开或刷新非常慢（超过半分钟），甚至打不开，该页无法显示，502 Bad Gateway 等情况，TTFB 计时需要好几秒。
切换 nginx 版本、php 版本 等均无效果，甚至购买新的 ECS 重新搭建环境也是效果甚微。
最终在阿里云 RDS 管理中，手动主备库切换，问题得以解决。
因此大概率是原主库有问题（有损坏的表需要修复或锁等情况）。
查询故障时间段的慢 SQL，发现某表的锁等待时间特别长，不知道是不是这个表的原因导致的。
次日，提交工单得到回复是原主库（现备库）会自动修复，经再次主备库切换测试得到了肯定的结果。
再次日，又遇到同样的打开慢的情况，这次直接找到慢 SQL 中锁等待时间较长的表，优化（OPTIMIZE TABLE）（虽然是 InnoDB），立刻解决了问题。
判断是否为数字
if isNumeric(id) then
else
response.End
end if强制转换为数字
ii = clng(ii)转义单引号
replace(xxx, "'", "\'")判断一个字符串是否包含另一个字符串
if instr(str, "s")>0 then
response.Write(1)
else
response.Write(0)
end if开发环境正常，发布到 IIS 报错
Could not load file or assembly 'Microsoft.EntityFrameworkCore.Relational, Version=6.0.x.0, Culture=neutral, PublicKeyToken=adb9793829ddae60'. 系统找不到指定的文件。
尝试在 UI 层安装 Pomelo.EntityFrameworkCore.MySql 无果。
最终，在发布时文件发布选项中，去掉“启用 ReadyToRun 编译”就正常了。
当然这种情况不是在所有启用了 ReadyToRun 编译的项目中遇到，但该项目改为不启用 ReadyToRun 后恢复正常了，原因暂时未知。
public static class EntityFrameworkCoreExtension
{
private static DbCommand CreateCommand(DatabaseFacade facade, string sql, out DbConnection connection, params object[] parameters)
{
var conn = facade.GetDbConnection();
connection = conn;
conn.Open();
var cmd = conn.CreateCommand();
cmd.CommandText = sql;
cmd.Parameters.AddRange(parameters);
return cmd;
}
public static DataTable SqlQuery(this DatabaseFacade facade, string sql, params object[] parameters)
{
var command = CreateCommand(facade, sql, out DbConnection conn, parameters);
var reader = command.ExecuteReader();
var dt = new DataTable();
dt.Load(reader);
reader.Close();
conn.Close();
return dt;
}
public static List<T> SqlQuery<T>(this DatabaseFacade facade, string sql, params object[] parameters) where T : class, new()
{
var dt = SqlQuery(facade, sql, parameters);
return dt.ToList<T>();
}
public static List<T> ToList<T>(this DataTable dt) where T : class, new()
{
var propertyInfos = typeof(T).GetProperties();
var list = new List<T>();
foreach (DataRow row in dt.Rows)
{
var t = new T();
foreach (PropertyInfo p in propertyInfos)
{
if (dt.Columns.IndexOf(p.Name) != -1 && row[p.Name] != DBNull.Value)
{
p.SetValue(t, row[p.Name], null);
}
}
list.Add(t);
}
return list;
}
}调用示例：
var data = db.Database.SqlQuery<List<string>>("SELECT 'title' FROM `table` WHERE `id` = {0};", id);using Microsoft.AspNetCore.Mvc;
using Microsoft.EntityFrameworkCore;
namespace xxx.xxx.xxx.Controllers
{
public class DiscuzTinyintViewerController : Controller
{
public IActionResult Index()
{
using var context = new Data.xxx.xxxContext();
var conn = context.Database.GetDbConnection();
conn.Open();
using var cmd = conn.CreateCommand();
cmd.CommandText = "SELECT `TABLE_NAME` FROM information_schema.TABLES WHERE TABLE_SCHEMA = DATABASE();";
Dictionary<string, List<FieldType>?> tables = new();
using var r = cmd.ExecuteReader();
while (r.Read())
{
tables.Add((string)r["TABLE_NAME"], null);
}
conn.Close();
foreach (var table in tables)
{
var conn2 = context.Database.GetDbConnection();
conn2.Open();
using var cmd2 = conn2.CreateCommand();
cmd2.CommandText = "DESCRIBE " + table.Key;
using var r2 = cmd2.ExecuteReader();
List<FieldType> fields = new();
while (r2.Read())
{
if (((string)r2[1]).Contains("tinyint(1)"))
{
fields.Add(new()
{
Field = (string)r2[0],
Type = (string)r2[1],
Null = (string)r2[2],
});
}
}
conn2.Close();
tables[table.Key] = fields;
}
foreach (var table in tables)
{
foreach (var f in table.Value)
{
var conn3 = context.Database.GetDbConnection();
conn3.Open();
using var cmd3 = conn3.CreateCommand();
cmd3.CommandText = $"SELECT {f.Field} as F, COUNT({f.Field}) as C FROM {table.Key} GROUP BY {f.Field}";
using var r3 = cmd3.ExecuteReader();
List<FieldType.ValueCount> vs = new();
while (r3.Read())
{
vs.Add(new() { Value = Convert.ToString(r3["F"]), Count = Convert.ToInt32(r3["C"]) });
}
conn3.Close();
f.groupedValuesCount = vs;
}
}
return Json(tables.Where(c => c.Value != null && c.Value.Count > 0));
}
private class FieldType
{
public string Field { get; set; }
public string Type { get; set; }
public string Null { get; set; }
public List<ValueCount> groupedValuesCount { get; set; }
public class ValueCount
{
public string Value { get; set; }
public int Count { get; set; }
}
public string RecommendedType
{
get
{
if (groupedValuesCount == null || groupedValuesCount.Count < 2)
{
return "无建议";
}
else if (groupedValuesCount.Count == 2 && groupedValuesCount.Any(c => c.Value == "0") && groupedValuesCount.Any(c => c.Value == "1"))
{
return "bool" + (Null == "YES" ? "?" : "");
}
else
{
return "sbyte" + (Null == "YES" ? "?" : "");
}
}
}
}
}
}[{
"key": "pre_forum_post",
"value": [{
"field": "first",
"type": "tinyint(1)",
"null": "NO",
"groupedValuesCount": [{
"value": "0",
"count": 1395501
}, {
"value": "1",
"count": 179216
}],
"recommendedType": "bool"
}, {
"field": "invisible",
"type": "tinyint(1)",
"null": "NO",
"groupedValuesCount": [{
"value": "-5",
"count": 9457
}, {
"value": "-3",
"count": 1412
}, {
"value": "-2",
"count": 1122
}, {
"value": "-1",
"count": 402415
}, {
"value": "0",
"count": 1160308
}, {
"value": "1",
"count": 3
}],
"recommendedType": "sbyte"
}, {
"field": "anonymous",
"type": "tinyint(1)",
"null": "NO",
"groupedValuesCount": [{
"value": "0",
"count": 1574690
}, {
"value": "1",
"count": 27
}],
"recommendedType": "bool"
}, {
"field": "usesig",
"type": "tinyint(1)",
"null": "NO",
"groupedValuesCount": [{
"value": "0",
"count": 162487
}, {
"value": "1",
"count": 1412230
}],
"recommendedType": "bool"
}, {
"field": "htmlon",
"type": "tinyint(1)",
"null": "NO",
"groupedValuesCount": [{
"value": "0",
"count": 1574622
}, {
"value": "1",
"count": 95
}],
"recommendedType": "bool"
}, {
"field": "bbcodeoff",
"type": "tinyint(1)",
"null": "NO",
"groupedValuesCount": [{
"value": "-1",
"count": 935448
}, {
"value": "0",
"count": 639229
}, {
"value": "1",
"count": 40
}],
"recommendedType": "sbyte"
}, {
"field": "smileyoff",
"type": "tinyint(1)",
"null": "NO",
"groupedValuesCount": [{
"value": "-1",
"count": 1359482
}, {
"value": "0",
"count": 215186
}, {
"value": "1",
"count": 49
}],
"recommendedType": "sbyte"
}, {
"field": "parseurloff",
"type": "tinyint(1)",
"null": "NO",
"groupedValuesCount": [{
"value": "0",
"count": 1572844
}, {
"value": "1",
"count": 1873
}],
"recommendedType": "bool"
}, {
"field": "attachment",
"type": "tinyint(1)",
"null": "NO",
"groupedValuesCount": [{
"value": "0",
"count": 1535635
}, {
"value": "1",
"count": 2485
}, {
"value": "2",
"count": 36597
}],
"recommendedType": "sbyte"
}, {
"field": "comment",
"type": "tinyint(1)",
"null": "NO",
"groupedValuesCount": [{
"value": "0",
"count": 1569146
}, {
"value": "1",
"count": 5571
}],
"recommendedType": "bool"
}]
}]测试表数据量 152 万条，测试跳过 100 万取 10 条。
测试一：直接使用 limit 跳过 1000000 取 10，耗时 2.4s；
SELECT *
FROM `pre_forum_post`
ORDER BY `pid`
LIMIT 1000000, 10
> OK
> 时间: 2.394s测试二：先使用 limit 跳过 1000000 取 1，再使用配合 where 条件，使用 limit 取 10，耗时 0.2s。
SELECT *
FROM `pre_forum_post`
WHERE `pid` >= (
SELECT `pid`
FROM `pre_forum_post`
ORDER BY `pid`
LIMIT 1000000, 1
)
ORDER BY `pid`
LIMIT 10
> OK
> 时间: 0.207s两次测试耗时相差约 10 倍。测试取 100 条或取 1 条，耗时都相差约 10 倍。
但若测试跳过条数较小时，测试一效率更高，因此应按照项目的实际需要选择适当的查询方法。
如果您想在 MySQL / SQL Server 等数据库的所有表的所有字段中搜索文本字符串，您可以使用 Navicat 非常轻松地完成此操作。以下是搜索每个数据库表的步骤。
1) 打开 Navicat，在菜单中选择：工具 - 在数据库或模式中查找...
2) 转到搜索表单
如图所示，你会看到一个看起来像这样的表单：
现在您所要做的就是填写您的搜索条件。
3) 按“查找”并浏览结果
完成这些操作后，只需按“查找”按钮，稍等片刻，然后浏览结果即可。此图显示了结果的样子：
当您双击“查找结果”中的一个表时，Navicat 将向您显示相关结果。
概括
总而言之，如果您需要在整个 MySQL 数据库及其所有表中搜索字符串，这种方法对我来说效果很好。
private static List<string> GetTableNames(DbContext context)
{
context.Database.OpenConnection();
var connection = context.Database.GetDbConnection();
using var command = connection.CreateCommand();
command.CommandText = @"SELECT `TABLE_NAME`
FROM information_schema.TABLES
WHERE TABLE_SCHEMA = DATABASE();";
var tableNames = new List<string>();
using var reader = command.ExecuteReader();
while (reader.Read())
{
tableNames.Add((string)reader["TABLE_NAME"]);
}
return tableNames;
}