[ML] Enables display of contextual data for population charts using other metrics than count.

x-pack/plugins/ml/public/explorer/explorer_charts/explorer_chart_distribution.js

@@ -182,6 +182,7 @@ export class ExplorerChartDistribution extends React.Component {
             return d;
           }
         })
+        // Don't use an arrow function since we need access to `this`.
         .each(function () {
           maxYAxisLabelWidth = Math.max(this.getBBox().width + yAxis.tickPadding(), maxYAxisLabelWidth);
         })
@@ -342,16 +343,17 @@ export class ExplorerChartDistribution extends React.Component {
       // Create any new dots that are needed i.e. if number of chart points has increased.
       dots.enter().append('circle')
         .attr('r', LINE_CHART_ANOMALY_RADIUS)
+        // Don't use an arrow function since we need access to `this`.
         .on('mouseover', function (d) {
           showLineChartTooltip(d, this);
         })
         .on('mouseout', () => mlChartTooltipService.hide());
 
       // Update all dots to new positions.
       const threshold = mlSelectSeverityService.state.get('threshold');
-      dots.attr('cx', function (d) { return lineChartXScale(d.date); })
-        .attr('cy', function (d) { return lineChartYScale(d[CHART_Y_ATTRIBUTE]); })
-        .attr('class', function (d) {
+      dots.attr('cx', d => lineChartXScale(d.date))
+        .attr('cy', d => lineChartYScale(d[CHART_Y_ATTRIBUTE]))
+        .attr('class', (d) => {
           let markerClass = 'metric-value';
           if (_.has(d, 'anomalyScore') && Number(d.anomalyScore) >= threshold.val) {
             markerClass += ' anomaly-marker ';

x-pack/plugins/ml/public/explorer/explorer_charts/explorer_chart_single_metric.js

@@ -138,6 +138,7 @@ export class ExplorerChartSingleMetric extends React.Component {
             return lineChartYScale.tickFormat()(d);
           }
         })
+        // Don't use an arrow function since we need access to `this`.
         .each(function () {
           maxYAxisLabelWidth = Math.max(this.getBBox().width + yAxis.tickPadding(), maxYAxisLabelWidth);
         })
@@ -277,16 +278,17 @@ export class ExplorerChartSingleMetric extends React.Component {
       // Create any new dots that are needed i.e. if number of chart points has increased.
       dots.enter().append('circle')
         .attr('r', LINE_CHART_ANOMALY_RADIUS)
+        // Don't use an arrow function since we need access to `this`.
         .on('mouseover', function (d) {
           showLineChartTooltip(d, this);
         })
         .on('mouseout', () => mlChartTooltipService.hide());
 
       // Update all dots to new positions.
       const threshold = mlSelectSeverityService.state.get('threshold');
-      dots.attr('cx', function (d) { return lineChartXScale(d.date); })
-        .attr('cy', function (d) { return lineChartYScale(d.value); })
-        .attr('class', function (d) {
+      dots.attr('cx', d => lineChartXScale(d.date))
+        .attr('cy', d => lineChartYScale(d.value))
+        .attr('class', (d) => {
           let markerClass = 'metric-value';
           if (_.has(d, 'anomalyScore') && Number(d.anomalyScore) >= threshold.val) {
             markerClass += ` anomaly-marker ${getSeverityWithLow(d.anomalyScore)}`;
@@ -306,6 +308,7 @@ export class ExplorerChartSingleMetric extends React.Component {
         .attr('d', d3.svg.symbol().size(MULTI_BUCKET_SYMBOL_SIZE).type('cross'))
         .attr('transform', d => `translate(${lineChartXScale(d.date)}, ${lineChartYScale(d.value)})`)
         .attr('class', d => `anomaly-marker multi-bucket ${getSeverityWithLow(d.anomalyScore)}`)
+        // Don't use an arrow function since we need access to `this`.
         .on('mouseover', function (d) {
           showLineChartTooltip(d, this);
         })

x-pack/plugins/ml/public/explorer/explorer_charts/explorer_charts_container_service.js

@@ -76,7 +76,7 @@ export function explorerChartsContainerServiceFactory(
     // For now just take first 6 (or 8 if 4 charts per row).
     const maxSeriesToPlot = Math.max(chartsPerRow * 2, 6);
     const recordsToPlot = allSeriesRecords.slice(0, maxSeriesToPlot);
-    const seriesConfigs = buildDataConfigs(recordsToPlot);
+    const seriesConfigs = recordsToPlot.map(buildConfig);
 
     // Calculate the time range of the charts, which is a function of the chart width and max job bucket span.
     data.tooManyBuckets = false;
@@ -504,11 +504,6 @@ export function explorerChartsContainerServiceFactory(
     return recordsForSeries;
   }
 
-  function buildDataConfigs(anomalyRecords) {
-    // Build the chart configuration for each anomaly record.
-    return anomalyRecords.map(buildConfig);
-  }
-
   function calculateChartRange(seriesConfigs, earliestMs, latestMs, chartWidth, recordsToPlot, timeFieldName) {
     let tooManyBuckets = false;
     // Calculate the time range for the charts.

x-pack/plugins/ml/public/services/results_service.js

@@ -1399,6 +1399,8 @@ function getEventRateData(
 // Returned response contains a results property, which is an object
 // of document counts against time (epoch millis).
 const SAMPLER_TOP_TERMS_SHARD_SIZE = 200;
+const ENTITY_AGGREGATION_SIZE = 10;
+const AGGREGATION_MIN_DOC_COUNT = 1;
 function getEventDistributionData(
   index,
   types,
@@ -1412,8 +1414,7 @@ function getEventDistributionData(
   latestMs,
   interval) {
   return new Promise((resolve, reject) => {
-    // only get this data for count (used by rare chart)
-    if (metricFunction !== 'count' || splitField === undefined) {
+    if (splitField === undefined) {
       return resolve([]);
     }
 
@@ -1464,7 +1465,7 @@ function getEventDistributionData(
           date_histogram: {
             field: timeFieldName,
             interval: interval,
-            min_doc_count: 0
+            min_doc_count: AGGREGATION_MIN_DOC_COUNT
           },
           aggs: {
             sample: {
@@ -1475,7 +1476,8 @@ function getEventDistributionData(
                 entities: {
                   terms: {
                     field: splitField.fieldName,
-                    size: 10
+                    size: ENTITY_AGGREGATION_SIZE,
+                    min_doc_count: AGGREGATION_MIN_DOC_COUNT
                   }
                 }
               }
@@ -1491,7 +1493,7 @@ function getEventDistributionData(
     }
 
     if (metricFieldName !== undefined && metricFieldName !== '') {
-      body.aggs.byTime.aggs = {};
+      body.aggs.byTime.aggs.sample.aggs.entities.aggs = {};
 
       const metricAgg = {
         [metricFunction]: {
@@ -1502,7 +1504,7 @@ function getEventDistributionData(
       if (metricFunction === 'percentiles') {
         metricAgg[metricFunction].percents = [ML_MEDIAN_PERCENTS];
       }
-      body.aggs.byTime.aggs.metric = metricAgg;
+      body.aggs.byTime.aggs.sample.aggs.entities.aggs.metric = metricAgg;
     }
 
     ml.esSearch({
@@ -1516,10 +1518,11 @@ function getEventDistributionData(
           const date = +dataForTime.key;
           const entities = _.get(dataForTime, ['sample', 'entities', 'buckets'], []);
           entities.forEach((entity) => {
+            const value = (metricFunction === 'count') ? entity.doc_count : entity.metric.value;
             d.push({
               date,
               entity: entity.key,
-              value: entity.doc_count
+              value
             });
           });
           return d;

x-pack/plugins/ml/public/util/chart_utils.js

@@ -142,7 +142,7 @@ export function getChartType(config) {
     return CHART_TYPE.EVENT_DISTRIBUTION;
   } else if (
     POPULATION_DISTRIBUTION_ENABLED &&
-    config.functionDescription === 'count' &&
+    config.functionDescription !== 'rare' &&
     config.entityFields.some(f => f.fieldType === 'over')
   ) {
     return CHART_TYPE.POPULATION_DISTRIBUTION;