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profiler charts
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@@ -193,46 +193,83 @@ module.exports = {
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},
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extractTimelineChart_meta: true,
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async extractTimelineChart({ jslid, formatterFunction, measures }) {
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const formater = requirePluginFunction(formatterFunction);
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const datastore = new JsonLinesDatastore(getJslFileName(jslid), formater);
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async extractTimelineChart({ jslid, timestampFunction, aggregateFunction, measures }) {
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const timestamp = requirePluginFunction(timestampFunction);
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const aggregate = requirePluginFunction(aggregateFunction);
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const datastore = new JsonLinesDatastore(getJslFileName(jslid));
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let mints = null;
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let maxts = null;
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// pass 1 - counts stats, time range
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await datastore.enumRows(row => {
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if (!mints || row.ts < mints) mints = row.ts;
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if (!maxts || row.ts > maxts) maxts = row.ts;
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const ts = timestamp(row);
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if (!mints || ts < mints) mints = ts;
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if (!maxts || ts > maxts) maxts = ts;
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return true;
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});
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const minTime = new Date(mints).getTime();
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const maxTime = new Date(maxts).getTime();
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const duration = maxTime - minTime;
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const STEPS = 100;
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const step = duration / STEPS;
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const labels = _.range(STEPS).map(i => new Date(minTime + step / 2 + step * i));
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let stepCount = duration > 100 * 1000 ? STEPS : Math.round((maxTime - minTime) / 1000);
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if (stepCount < 2) {
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stepCount = 2;
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}
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const stepDuration = duration / stepCount;
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const labels = _.range(stepCount).map(i => new Date(minTime + stepDuration / 2 + stepDuration * i));
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const datasets = measures.map(m => ({
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label: m.label,
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data: Array(STEPS).fill(0),
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// const datasets = measures.map(m => ({
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// label: m.label,
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// data: Array(stepCount).fill(0),
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// }));
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const mproc = measures.map(m => ({
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...m,
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}));
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const data = Array(stepCount)
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.fill(0)
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.map(() => ({}));
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// pass 2 - count measures
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await datastore.enumRows(row => {
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if (!mints || row.ts < mints) mints = row.ts;
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if (!maxts || row.ts > maxts) maxts = row.ts;
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for (let i = 0; i < measures.length; i++) {
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const part = Math.round((new Date(row.ts).getTime() - minTime) / step);
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datasets[i].data[part] += row[measures[i].field];
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const ts = timestamp(row);
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let part = Math.round((new Date(ts).getTime() - minTime) / stepDuration);
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if (part < 0) part = 0;
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if (part >= stepCount) part - stepCount - 1;
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if (data[part]) {
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data[part] = aggregate(data[part], row, stepDuration);
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}
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return true;
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});
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datastore._closeReader();
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// const measureByField = _.fromPairs(measures.map((m, i) => [m.field, i]));
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// for (let mindex = 0; mindex < measures.length; mindex++) {
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// for (let stepIndex = 0; stepIndex < stepCount; stepIndex++) {
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// const measure = measures[mindex];
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// if (measure.perSecond) {
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// datasets[mindex].data[stepIndex] /= stepDuration / 1000;
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// }
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// if (measure.perField) {
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// datasets[mindex].data[stepIndex] /= datasets[measureByField[measure.perField]].data[stepIndex];
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// }
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// }
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// }
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// for (let i = 0; i < measures.length; i++) {
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// if (measures[i].hidden) {
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// datasets[i] = null;
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// }
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// }
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return {
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labels,
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datasets,
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datasets: mproc.map(m => ({
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label: m.label,
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data: data.map(d => d[m.field] || 0),
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})),
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};
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},
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};
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