10

我在本地有一个包含JSON格式化数据的文件。我创建了一个小脚本来在PHP通过调用时回显这个文件的输出AJAX。数据文件的大小为59k. 我按照 highcharts 的建议禁用动画和阴影。当我加载图表时，渲染需要非常非常长的时间。我已经粘贴了下面的脚本。有什么想法可以更快地呈现此图表吗？就目前而言，这绝对是不可接受的。

echo_file.php输出如下所示：

[{"name":"loess","data":[[1373241600000,3.49571041760408],[1373241660000,3.4844505982485],[1373241720000,3.47324293684199],[1373241780000,3.46208745646435],[1373241840000,3.45098418019539],[1373241900000,3.43993313111491],[1373241960000,3.42893433230273],[1373242020000,3.41798780683864],[1373242080000,3.4070935778
43611722495],[1373243400000,3.18069824879358],[1373243460000,3.17101320762565],[1373243520000,3.16138101680096],[1373243580000,3.15180169939934],[1373243640000,3.14227527850057],[1373243700000,3.13280177718446],[1373243760000,3.12338121853083],[1373243820000,3.11401362561948],[1373243880000,3.10469902153021]]}]

这是脚本：

$(document).ready(function() {


 var seriesOptions = [],
    yAxisOptions = [],
    colors = Highcharts.getOptions().colors;

function myAjax() {
    $.ajax({
                url: 'echo_file.php', 
                datatype: 'json',
                success: function(data) {

                    seriesOptions=data;
                    createChart();
                },

                cache: false    
                });
}

setInterval(myAjax, 300000); 


   function createChart() {

        $('#container').highcharts('StockChart', {
            chart: {
                animation: false,
                shadow: false

            },
            title : {
            text : 'CPU Utilization'
        },

            plotOptions: {

            series: {
                lineWidth: 2
            }
        },

            rangeSelector: {
                enabled: true,
                buttons: [{
                        type: 'minute',
                        count: 60,
                        text: 'hourly'
                    }, {
                        type: 'all',
                        text: 'All'
                    }]
            },
            credits: {
                enabled: false
            },
             xAxis: {
                type: 'datetime',
                minPadding:0.02,
                maxPadding:0.02,
                ordinal: false



            },


            yAxis: {
                labels: {
                    formatter: function() {
                        //return (this.value > 0 ? '+' : '') + this.value + '%';
                        return (this.value);
                    }
                }

            },


            yAxis : {
                title : {
                    text : '% CPU Utilization'
                },
                min:0,
                max:100,

                plotLines : {
                    value : 70,
                    color : '#FFA500',
                    dashStyle : 'shortdash',
                    width : 2,
                    label : {
                        text : 'Threshold',
                        align:'right'
                    }
                }                           

            },
            scrollbar: {
                    enabled: true
                    },
            navigator : {
                adaptToUpdatedData: false

            },


            tooltip: {
                pointFormat: '<span style="color:{series.color}">{series.name}</span>: <b>{point.y} </b>',
                valueDecimals: 2
            },

            series: seriesOptions

        });
    }

});
4

2 回答 2

7

Highcharts 刚刚发布了一个 boost 模块，可以帮助加速包含大量数据点的图表。您需要一个现代浏览器才能使用它。

https://github.com/highslide-software/highcharts.com/blob/master/js/modules/boost.src.js

当我想加快渲染速度时，这是我的 highcharts 选项。它会删除所有动画、点击事件和工具提示。

Highcharts.setOptions({
    plotOptions: {
        area: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        arearange: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        areaspline: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        areasplinerange: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        bar: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        boxplot: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        bubble: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        column: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        columnrange: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        errorbar: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        funnel: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        gauge: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        heatmap: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        line: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        pie: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        polygon: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        pyramid: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        scatter: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        series: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        solidgauge: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        spline: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        treemap: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
        waterfall: { animation: false, enableMouseTracking: false, stickyTracking: true, shadow: false, dataLabels: { style: { textShadow: false } } },
    },
    chart: {
        reflow: false,
        events: {
            redraw: function() {
                console.log("highcharts redraw, rendering-done");
                $('body').addClass('rendering-done');
            }
        },
        animation: false
    },
    tooltip: {
        enabled: false,
        animation: false
    },
    exporting: {
        enabled:false
    },
    credits: {
        enabled: false
    }
});
于 2015-08-27T13:55:24.027 回答
2

即使文件是本地数据也必须传输到浏览器，因为图表是在那里绘制的，这里有一个 52k 点的示例，并且图表加载速度非常快。

请参阅http://highcharts.com/stock/demo/data-grouping

如果在你的情况下你有太多的点，也许你应该采取一些机制来划分有代表性的样本，因为显示一个眼睛无法区分不同值的图表是没有意义的。​​​​

请参阅http://highcharts.com/stock/demo/lazy-loading

于 2013-07-09T14:29:32.487 回答