Question

我正在尝试使用JavaScript和tsiclient库从Azure时序见解预览中查询数据。我的代码遵循github文档中的格式，但是当我推送查询时，出现500个“内部服务错误” POST错误。

我的代码：

import datetime

import pytz

def diff_hours_tz(from_tz_name, to_tz_name, negative=False):
    """
    Returns difference hours  between timezones
    res = diff_hours_tz("UTC", "Europe/Paris") : 2
    """
    from_tz = pytz.timezone(from_tz_name)
    to_tz = pytz.timezone(to_tz_name)

    utc_dt = datetime.datetime.now(datetime.timezone.utc)
    dt_from = dt_to = datetime.datetime.utcnow()

    dt_from = from_tz.localize(dt_from)
    dt_to = to_tz.localize(dt_to)

    from_d = dt_from - utc_dt
    if from_d.days < 0:
        return diff_hours_tz(to_tz_name, from_tz_name, True)

    dt_delta = dt_from - dt_to

    negative_int = -1 if negative else 1

    return int(dt_delta.seconds/3600)*negative_int

def dt_tz_to_tz(dt, from_tz_name, to_tz_name):
    """
    Apply difference hours between timezones to a datetime object
    dt_new = dt_tz_to_tz(datetime.datetime.now(), "UTC", "Europe/Paris")
    """
    hours = diff_hours_tz(from_tz_name, to_tz_name)
    return dt+datetime.timedelta(hours=hours)

# Usage example

res = diff_hours_tz("Europe/Paris", "America/New_York")
# Result : -6
res = diff_hours_tz("UTC", "Europe/Paris")
# Result : 2

now = datetime.datetime.now()
# Result : 2019-06-18 15:10:31.720105
dt_new = dt_tz_to_tz(now, "UTC", "Europe/Paris")
# Result : 2019-06-18 17:10:31.720105
dt_new = dt_tz_to_tz(now, "Europe/Paris", "America/New_York")
# Result : 2019-06-18 09:10:31.720105
dt_new = dt_tz_to_tz(now, "America/New_York", "Europe/Paris")
# Result : 2019-06-18 21:10:31.720105

有人对此有任何经验吗？

编辑-完整回复：

var data = [];
    data.push(new tsiClient.ux.TsqExpression(
        // instanceObject
        {   
            timeSeriesId: ['CSIRO_Density-SC503_DPV'] 
        },
        // variableObject
        { 
            rawdata: {
                kind: 'numeric',
                value: {
                    tsx: 'rawdata.value'
                },
                filter: null,
                aggregation: null
            }
        },
        // searchSpan
        { 
            from: startDate,
            to: endDate,
            bucketSize: '5m'
        },
        // color
        '#60B9AE',
        // alias
        'Tag_Values',
        // contextMenu
        null
    ));
    authContext.getTsiToken().then(function(token) {
        tsiClient.server.getTsqResults(
           token, 
           environmentFqdn,
           data.map(ae => ae.toTsq())).then(function(result) {
               console.log(result);
           });
    });

最后编辑！我发现了问题-变量对象的语法错误：

code: "InternalServerError"
message: "Internal server error. Please retry your request later."

应该是

'rawdata.value'

Answer 1

您正确使用了Value变量，应该像下面这样。

value: {tsx: '$event.value'}

这是我尝试使用PAYG SKU进行基本图表的示例，并且对我有用。

var linechartTsqExpressions = [];
                var startDate = new Date('2017-04-20T20:00:00Z');
                var endDate = new Date(startDate.valueOf() + 1000*60*60*24*30);

                linechartTsqExpressions.push(new tsiClient.ux.TsqExpression(
                    {timeSeriesId: ['df4412c4-dba2-4a52-87af-780e78ff156b']}, // instance json
                    {Max: {
                        kind: 'numeric',
                        value: {tsx: '$event.value.Double'},
                        filter: null,
                        aggregation: {tsx: 'max($value)'}
                    }}, // variable json
                    { from: startDate, to: endDate, bucketSize: '6h' }, // search span
                    '#60B9AE', // color
                    'MaxValue')); // alias
                linechartTsqExpressions.push(new tsiClient.ux.TsqExpression(
                    {timeSeriesId: ['df4412c4-dba2-4a52-87af-780e78ff156b']}, // instance json
                    {Avg: {
                        kind: 'numeric',
                        value: {tsx: '$event.value.Double'},
                        filter: null,
                        aggregation: {tsx: 'avg($value)'}
                    }}, // variable json
                    { from: startDate, to: endDate, bucketSize: '6h' }, // search span
                    '#D869CB', // color
                    'AvgValue')); // 

                var eventsTsqExpressions = [new tsiClient.ux.TsqExpression(
                    {timeSeriesId: ['df4412c4-dba2-4a52-87af-780e78ff156b']}, // instance json
                    {Avg: {
                        kind: 'numeric',
                        value: {tsx: '$event.value.Double'},
                        filter: null,
                        aggregation: {tsx: 'avg($value)'}
                    }}, // variable json
                    { from: startDate, to: new Date(startDate.valueOf() + 1000*60*60*2), bucketSize: '1m'}, // search span
                    '#D869CB', // color
                    'AvgValue')]; // 
                authContext.getTsiToken().then(function(token){
                    tsiClient.server.getTsqResults(token, '10000000-0000-0000-0000-100000000109.env.timeseries.azure.com', linechartTsqExpressions.map(function(ae){return ae.toTsq()})).then(function(result){
                        var transformedResult = tsiClient.ux.transformTsqResultsForVisualization(result, linechartTsqExpressions);
                        var lineChart = new tsiClient.ux.LineChart(document.getElementById('chart1'));
                        lineChart.render(transformedResult, {theme: 'dark', grid: true, tooltip: true, legend: 'compact'}, linechartTsqExpressions);
                    });
                    tsiClient.server.getTsqResults(token, '10000000-0000-0000-0000-100000000109.env.timeseries.azure.com', eventsTsqExpressions.map(function(ae){return ae.toTsq(true, true)})).then(function(result){
                        var transformedEvents = tsiClient.ux.transformTsqResultsToEventsArray(result);
                        var eventsTable = tsiClient.ux.EventsTable(document.getElementById('chart2'));
                        eventsTable.render(transformedEvents, {theme: 'dark', offset: 'Local'}, true);
                    });
                });

您可以将此repo用于将来的参考。希望对您有所帮助。

从Azure Time Series Insights JavaScript API查询数据时，如何解决500个内部服务错误？

1 个答案: