DataTable to JSON string

var lst = dt.AsEnumerable()
    .Select(r => r.Table.Columns.Cast<DataColumn>()
            .Select(c => new KeyValuePair<string, object>(c.ColumnName, r[c.Ordinal])
           ).ToDictionary(z=>z.Key,z=>z.Value)
    ).ToList();

var serializer = new System.Web.Script.Serialization.JavaScriptSerializer();
return serializer.Serialize(lst);

Json傳輸 參數字串轉為 javascript function

{
   "param1" : "str1",
   "num1" : 1,
   "someFunction" : "function(){alert(1);}"
}

var obj = JSON.parse(str,turnStrToFunction);



    /*************
       JSON.parse(str,reviver)

       reviver function = > 轉換字串成為javascript function
    **************/
    function turnStrToFunction (key, value) {
        if (value && (typeof value === 'string') && value.indexOf("function(") === 0) {
            var jsFunc = new Function('return ' + value)();
            return jsFunc;
        }
         
        return value;
    };

SQL Group By Like , 欄位橫轉直(pivot)

select Year
        ,Month
        ,SUM(contactUs)contactUs
        ,SUM(contactUs)contactUs
        ,SUM(mamaClubCancel)mamaClubCancel
        ,SUM(mamaClubSignUp)mamaClubSignUp
        ,SUM(memberAdd)memberAdd
        ,SUM(memberLogin)memberLogin
        ,SUM(mamaClubLogin)mamaClubLogin from (
            --pivot start
            select YEAR,Month ,contactUs, mamaClubCancel, mamaClubSignUp, memberAdd, memberLogin , mamaClubLogin
            from
            (
                --groupby start
                SELECT Year(cdate) AS 'Year'
                    , Month(cdate) AS 'Month'
                    , case when i_name like 'mamaClubLogin%' then 'mamaClubLogin' else i_name end i_name
                    , COUNT(DISTINCT fno) total
                    , COUNT(DISTINCT ino) distint 
                from SUB_FlowTracking D
                GROUP BY Year(cdate), Month(cdate),
                        --Group By Like
                        case when i_name like 'mamaClubLogin%' then 'mamaClubLogin' else i_name end
                --groupby end
            ) d
            pivot
            ( --sum field
              SUM(d.total)
              --field source field
              for i_name in (contactUs, mamaClubCancel, mamaClubSignUp, memberAdd, memberLogin , mamaClubLogin)
            ) piv
            --pivot end
) T Group by Year,Month