我有一个 MySQL 数据库，其中包含一些价格数据我想使用 HighCharts/HighStock 显示，但我不确定如何实际从 MySQL 获取这些数据（通过 DBslayer 作为 JSON 层）并显示在高图表中（我在他们的网站上找到的示例没有帮助，并且到处搜索也没有很好的 tuts）。
所以基本上系统看起来像这样：
MySQL <---> DBSlayer Service <---> JSON Requests to DBSlayer <---> Web page with charts - send query to DBSLayer
DBSlayer 查询的 MySQL 视图如下所示：
DATE TIME | Symbol1 | Price 1 | Symbol2 | Price 2 | Price3
2011-09-01| ABC | 12.3 | XYZ | 67.8 | 0.0852
或者更好的例子是从查询到 DBSlayer 返回的 JSON：
{"RESULT" : {"HEADER" : ["id" , , "authorID" , "msgDate" , "obj_obj" , "obj_subj" , "obj_diff" , "subj_pos" , "subj_neg" , "subj_diff" , "pos_lex" , "neg_lex" ] ,
"ROWS" : [["4e0f1c393bfbb6aa4b7278c2" , "27" , "2011-06-30 13:59:47" , 0.0275171 , 0.972483 , -0.944966 , 0.993814 , 0.00618577 , 0.987628 , 1 , 0 ] ,
["4e0f1c393bfbb6aa4b7278c3" , "36324" , "2011-06-30 13:59:31" , 0.364953 , 0.635047 , -0.270095 , 0.0319281 , 0.968072 , -0.936144 , 3 , 1 ] ,
["4e0f1c393bfbb6aa4b7278c4" , "12134" , "2011-06-30 13:59:28" , 0.0112589 , 0.988741 , -0.977482 , 0.857735 , 0.142265 , 0.715469 , 1 , 1 ] ] ,
"TYPES" : ["MYSQL_TYPE_VAR_STRING" , "MYSQL_TYPE_VAR_STRING" , "MYSQL_TYPE_DATETIME" , "MYSQL_TYPE_DOUBLE" , "MYSQL_TYPE_DOUBLE" , "MYSQL_TYPE_DOUBLE" , "MYSQL_TYPE_DOUBLE" , "MYSQL_TYPE_DOUBLE" , "MYSQL_TYPE_DOUBLE" , "MYSQL_TYPE_DOUBLE" , "MYSQL_TYPE_LONG" } , "SERVER" : "db-webPrices"}
我应该如何将它部署到高图表？我是否应该首先使用 Node.js 来包装查询（DBSlayer 库中有 Node.js，但是它们不适用于最新版本的 Node.js。
我将如何使用 JQuery 来获取这样的 HighStock 图表的数据和格式：http ://www.highcharts.com/stock/demo/multiple-series/gray
使用 CSV 文件作为数据源的基本 HighCharts 演示如下所示：
$(function() {
var seriesOptions = [],
yAxisOptions = [],
seriesCounter = 0,
names = ['DJI', 'SENTIMENT', 'GOOG', 'GS', 'SENTIMENT-Z', 'DJI-Z'],
colors = Highcharts.getOptions().colors;
$.each(names, function(i, name) {
$.get(name +'.csv', function(csv, state, xhr) {
// inconsistency
if (typeof csv != 'string') {
csv = xhr.responseText;
}
// parse the CSV data
var data = [], header, comment = /^#/, x;
$.each(csv.split('\n'), function(i, line){
if (!comment.test(line)) {
if (!header) {
header = line;
}
else {
var point = line.split(';'), date = point[0].split('-');
x = Date.UTC(date[2], date[1] - 1, date[0]);
if (point.length > 1) {
// use point[4], the close value
data.push([
x,
parseFloat(point[4])
]);
}
}
}
});
seriesOptions[i] = {
name: name,
data: data,
yAxis: i
};
// create one y axis for each series in order to be able to compare them
yAxisOptions[i] = {
alternateGridColor: null,
gridLineWidth: i ? 0 : 1, // only grid lines for the first series
opposite: i ? true : false,
minorGridLineWidth: 0,
title: {
text: name,
style: {
color: colors[i]
}
},
lineWidth: 2,
lineColor: colors[i]
};
// As we're loading the data asynchronously, we don't know what order it will arrive. So
// we keep a counter and create the chart when all the data is loaded.
seriesCounter++;
if (seriesCounter == names.length) {
createChart();
}
});
});
// create the chart when all data is loaded
function createChart() {
chart = new Highcharts.StockChart({
chart: {
renderTo: 'container',
alignTicks: false
},
rangeSelector: {
selected: 1
},
title: {
text: null
},
xAxis: {
type: 'datetime',
maxZoom: 14 * 24 * 3600000, // fourteen days
title: {
text: null
}
},
yAxis: yAxisOptions,
series: seriesOptions
});
}
});
</script>
<script type="text/javascript" src="js/themes/gray.js"></script>
任何示例/代码将不胜感激！
干杯!