Dapper sql in

应用场景:

使用 sql的 Case When Then 批量更新某张表,底层数据库用到了Dapper

代码示例:

public int UpdateClientReceivedResult(Dictionary<string, string> dict)
{
var dynamicSqlParam = new DynamicParameters();
var sbSet = new StringBuilder();
sbSet.Append(" (CASE SmsFlowID ");
int idx = ;
foreach (var kv in dict)
{
sbSet.Append(string.Format(" WHEN @SmsFlowID{0} THEN @ClientReceivedResult{0} ", idx));
dynamicSqlParam.Add(string.Format("SmsFlowID{0}", idx), kv.Key, null, null, null);
dynamicSqlParam.Add(string.Format("ClientReceivedResult{0}", idx), kv.Value, null, null, null);
idx += ;
}
sbSet.Append(" ELSE ClientReceivedResult END) "); var sbWhere = new StringBuilder();
sbWhere.Append(" AND SmsFlowID in @ids ");
dynamicSqlParam.Add("ids", dict.Keys.ToArray(), null, null, null); string sql = string.Format("UPDATE [SmsSendResult] SET [ClientReceivedResult]={0} WHERE 1=1 {1}", sbSet,
sbWhere);
int affectNum = -;
using (var conn = new SqlConnection(SmsDBConnString))
{
affectNum = conn.Execute(sql, dynamicSqlParam);
}
return affectNum;
}

最终生成的sql:

UPDATE [SmsSendResult] SET  [ClientReceivedResult]= (CASE SmsFlowID  WHEN @SmsFlowID0 THEN @ClientReceivedResult0  WHEN @SmsFlowID1 THEN @ClientReceivedResult1  WHEN @SmsFlowID2 THEN @ClientReceivedResult2  WHEN @SmsFlowID3 THEN @ClientReceivedResult3  WHEN @SmsFlowID4 THEN @ClientReceivedResult4  WHEN @SmsFlowID5 THEN @ClientReceivedResult5  WHEN @SmsFlowID6 THEN @ClientReceivedResult6  WHEN @SmsFlowID7 THEN @ClientReceivedResult7  ELSE ClientReceivedResult END)  WHERE 1=1  AND SmsFlowID in @SmsFlowID

代码说明:
这个方法的作用是,根据传进来的Dict<SmsFlowID,ClientReceivedResult>批量更新SmsSendResult对应的值,为了限定更新的条数,需要用到where in操作,in后面的参数名必须要注意一下,尽量不和别的参数名字有重复,我之前sbWhere是这么写的:

var sbWhere = new StringBuilder();
sbWhere.Append(" AND SmsFlowID in @SmsFlowID ");
dynamicSqlParam.Add("SmsFlowID", dict.Keys.ToArray(), null, null, null);

结果运行报异常:说什么已存在相同参数名SmsFlowID1。。。找了半天,原来是in的参数名字的问题!Dapper对于 where col in @arg 会将动态参数的数组类型的参数自动转化为 where col in (@arg1,@arg2....),这样就重名了,所以找了半天原因,原来是这么个回事,修改后程序运行正常

Dapper sql inDapper sql in
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