grafana/public/app/plugins/panel/table/transformers.ts

240 lines
5.7 KiB
TypeScript

import _ from 'lodash';
import flatten from '../../../core/utils/flatten';
import TimeSeries from '../../../core/time_series2';
import TableModel from '../../../core/table_model';
var transformers = {};
transformers['timeseries_to_rows'] = {
description: 'Time series to rows',
getColumns: function() {
return [];
},
transform: function(data, panel, model) {
model.columns = [
{text: 'Time', type: 'date'},
{text: 'Metric'},
{text: 'Value'},
];
for (var i = 0; i < data.length; i++) {
var series = data[i];
for (var y = 0; y < series.datapoints.length; y++) {
var dp = series.datapoints[y];
model.rows.push([dp[1], series.target, dp[0]]);
}
}
},
};
transformers['timeseries_to_columns'] = {
description: 'Time series to columns',
getColumns: function() {
return [];
},
transform: function(data, panel, model) {
model.columns.push({text: 'Time', type: 'date'});
// group by time
var points = {};
for (let i = 0; i < data.length; i++) {
var series = data[i];
model.columns.push({text: series.target});
for (var y = 0; y < series.datapoints.length; y++) {
var dp = series.datapoints[y];
var timeKey = dp[1].toString();
if (!points[timeKey]) {
points[timeKey] = {time: dp[1]};
points[timeKey][i] = dp[0];
} else {
points[timeKey][i] = dp[0];
}
}
}
for (var time in points) {
var point = points[time];
var values = [point.time];
for (let i = 0; i < data.length; i++) {
var value = point[i];
values.push(value);
}
model.rows.push(values);
}
}
};
transformers['timeseries_aggregations'] = {
description: 'Time series aggregations',
getColumns: function() {
return [
{text: 'Avg', value: 'avg'},
{text: 'Min', value: 'min'},
{text: 'Max', value: 'max'},
{text: 'Total', value: 'total'},
{text: 'Current', value: 'current'},
{text: 'Count', value: 'count'},
];
},
transform: function(data, panel, model) {
var i, y;
model.columns.push({text: 'Metric'});
for (i = 0; i < panel.columns.length; i++) {
model.columns.push({text: panel.columns[i].text});
}
for (i = 0; i < data.length; i++) {
var series = new TimeSeries({
datapoints: data[i].datapoints,
alias: data[i].target,
});
series.getFlotPairs('connected');
var cells = [series.alias];
for (y = 0; y < panel.columns.length; y++) {
cells.push(series.stats[panel.columns[y].value]);
}
model.rows.push(cells);
}
}
};
transformers['annotations'] = {
description: 'Annotations',
getColumns: function() {
return [];
},
transform: function(data, panel, model) {
model.columns.push({text: 'Time', type: 'date'});
model.columns.push({text: 'Title'});
model.columns.push({text: 'Text'});
model.columns.push({text: 'Tags'});
if (!data || !data.annotations || data.annotations.length === 0) {
return;
}
for (var i = 0; i < data.annotations.length; i++) {
var evt = data.annotations[i];
model.rows.push([evt.time, evt.title, evt.text, evt.tags]);
}
}
};
transformers['table'] = {
description: 'Table',
getColumns: function(data) {
if (!data || data.length === 0) {
return [];
}
return data[0].columns;
},
transform: function(data, panel, model) {
if (!data || data.length === 0) {
return;
}
if (data[0].type !== 'table') {
throw {message: 'Query result is not in table format, try using another transform.'};
}
model.columns = data[0].columns;
model.rows = data[0].rows;
}
};
transformers['json'] = {
description: 'JSON Data',
getColumns: function(data) {
if (!data || data.length === 0) {
return [];
}
var names: any = {};
for (var i = 0; i < data.length; i++) {
var series = data[i];
if (series.type !== 'docs') {
continue;
}
// only look at 100 docs
var maxDocs = Math.min(series.datapoints.length, 100);
for (var y = 0; y < maxDocs; y++) {
var doc = series.datapoints[y];
var flattened = flatten(doc, null);
for (var propName in flattened) {
names[propName] = true;
}
}
}
return _.map(names, function(value, key) {
return {text: key, value: key};
});
},
transform: function(data, panel, model) {
var i, y, z;
for (let column of panel.columns) {
var tableCol: any = {text: column.text};
// if filterable data then set columns to filterable
if (data.length > 0 && data[0].filterable) {
tableCol.filterable = true;
}
model.columns.push(tableCol);
}
if (model.columns.length === 0) {
model.columns.push({text: 'JSON'});
}
for (i = 0; i < data.length; i++) {
var series = data[i];
for (y = 0; y < series.datapoints.length; y++) {
var dp = series.datapoints[y];
var values = [];
if (_.isObject(dp) && panel.columns.length > 0) {
var flattened = flatten(dp, null);
for (z = 0; z < panel.columns.length; z++) {
values.push(flattened[panel.columns[z].value]);
}
} else {
values.push(JSON.stringify(dp));
}
model.rows.push(values);
}
}
}
};
function transformDataToTable(data, panel) {
var model = new TableModel();
if (!data || data.length === 0) {
return model;
}
var transformer = transformers[panel.transform];
if (!transformer) {
throw {message: 'Transformer ' + panel.transform + ' not found'};
}
transformer.transform(data, panel, model);
return model;
}
export {transformers, transformDataToTable};