mirror of
https://github.com/grafana/grafana.git
synced 2025-02-25 18:55:37 -06:00
361 lines
10 KiB
TypeScript
361 lines
10 KiB
TypeScript
///<reference path="../../../headers/common.d.ts" />
|
||
|
||
import _ from 'lodash';
|
||
import queryDef from "./query_def";
|
||
import TableModel from 'app/core/table_model';
|
||
|
||
export function ElasticResponse(targets, response) {
|
||
this.targets = targets;
|
||
this.response = response;
|
||
}
|
||
|
||
ElasticResponse.prototype.processMetrics = function(esAgg, target, seriesList, props) {
|
||
var metric, y, i, newSeries, bucket, value;
|
||
|
||
for (y = 0; y < target.metrics.length; y++) {
|
||
metric = target.metrics[y];
|
||
if (metric.hide) {
|
||
continue;
|
||
}
|
||
|
||
switch (metric.type) {
|
||
case 'count': {
|
||
newSeries = { datapoints: [], metric: 'count', props: props};
|
||
for (i = 0; i < esAgg.buckets.length; i++) {
|
||
bucket = esAgg.buckets[i];
|
||
value = bucket.doc_count;
|
||
newSeries.datapoints.push([value, bucket.key]);
|
||
}
|
||
seriesList.push(newSeries);
|
||
break;
|
||
}
|
||
case 'percentiles': {
|
||
if (esAgg.buckets.length === 0) {
|
||
break;
|
||
}
|
||
|
||
var firstBucket = esAgg.buckets[0];
|
||
var percentiles = firstBucket[metric.id].values;
|
||
|
||
for (var percentileName in percentiles) {
|
||
newSeries = {datapoints: [], metric: 'p' + percentileName, props: props, field: metric.field};
|
||
|
||
for (i = 0; i < esAgg.buckets.length; i++) {
|
||
bucket = esAgg.buckets[i];
|
||
var values = bucket[metric.id].values;
|
||
newSeries.datapoints.push([values[percentileName], bucket.key]);
|
||
}
|
||
seriesList.push(newSeries);
|
||
}
|
||
|
||
break;
|
||
}
|
||
case 'extended_stats': {
|
||
for (var statName in metric.meta) {
|
||
if (!metric.meta[statName]) {
|
||
continue;
|
||
}
|
||
|
||
newSeries = {datapoints: [], metric: statName, props: props, field: metric.field};
|
||
|
||
for (i = 0; i < esAgg.buckets.length; i++) {
|
||
bucket = esAgg.buckets[i];
|
||
var stats = bucket[metric.id];
|
||
|
||
// add stats that are in nested obj to top level obj
|
||
stats.std_deviation_bounds_upper = stats.std_deviation_bounds.upper;
|
||
stats.std_deviation_bounds_lower = stats.std_deviation_bounds.lower;
|
||
|
||
newSeries.datapoints.push([stats[statName], bucket.key]);
|
||
}
|
||
|
||
seriesList.push(newSeries);
|
||
}
|
||
|
||
break;
|
||
}
|
||
default: {
|
||
newSeries = { datapoints: [], metric: metric.type, field: metric.field, props: props};
|
||
for (i = 0; i < esAgg.buckets.length; i++) {
|
||
bucket = esAgg.buckets[i];
|
||
|
||
value = bucket[metric.id];
|
||
if (value !== undefined) {
|
||
if (value.normalized_value) {
|
||
newSeries.datapoints.push([value.normalized_value, bucket.key]);
|
||
} else {
|
||
newSeries.datapoints.push([value.value, bucket.key]);
|
||
}
|
||
}
|
||
|
||
}
|
||
seriesList.push(newSeries);
|
||
break;
|
||
}
|
||
}
|
||
}
|
||
};
|
||
|
||
ElasticResponse.prototype.processAggregationDocs = function(esAgg, aggDef, target, table, props) {
|
||
// add columns
|
||
if (table.columns.length === 0) {
|
||
for (let propKey of _.keys(props)) {
|
||
table.addColumn({text: propKey, filterable: true});
|
||
}
|
||
table.addColumn({text: aggDef.field, filterable: true});
|
||
}
|
||
|
||
// helper func to add values to value array
|
||
let addMetricValue = (values, metricName, value) => {
|
||
table.addColumn({text: metricName});
|
||
values.push(value);
|
||
};
|
||
|
||
for (let bucket of esAgg.buckets) {
|
||
let values = [];
|
||
|
||
for (let propValues of _.values(props)) {
|
||
values.push(propValues);
|
||
}
|
||
|
||
// add bucket key (value)
|
||
values.push(bucket.key);
|
||
|
||
for (let metric of target.metrics) {
|
||
switch (metric.type) {
|
||
case "count": {
|
||
addMetricValue(values, this._getMetricName(metric.type), bucket.doc_count);
|
||
break;
|
||
}
|
||
case 'extended_stats': {
|
||
for (var statName in metric.meta) {
|
||
if (!metric.meta[statName]) {
|
||
continue;
|
||
}
|
||
|
||
var stats = bucket[metric.id];
|
||
// add stats that are in nested obj to top level obj
|
||
stats.std_deviation_bounds_upper = stats.std_deviation_bounds.upper;
|
||
stats.std_deviation_bounds_lower = stats.std_deviation_bounds.lower;
|
||
|
||
addMetricValue(values, this._getMetricName(statName), stats[statName]);
|
||
}
|
||
break;
|
||
}
|
||
default: {
|
||
let metricName = this._getMetricName(metric.type);
|
||
let otherMetrics = _.filter(target.metrics, {type: metric.type});
|
||
|
||
// if more of the same metric type include field field name in property
|
||
if (otherMetrics.length > 1) {
|
||
metricName += ' ' + metric.field;
|
||
}
|
||
|
||
addMetricValue(values, metricName, bucket[metric.id].value);
|
||
break;
|
||
}
|
||
}
|
||
}
|
||
|
||
table.rows.push(values);
|
||
}
|
||
};
|
||
|
||
// This is quite complex
|
||
// neeed to recurise down the nested buckets to build series
|
||
ElasticResponse.prototype.processBuckets = function(aggs, target, seriesList, table, props, depth) {
|
||
var bucket, aggDef, esAgg, aggId;
|
||
var maxDepth = target.bucketAggs.length-1;
|
||
|
||
for (aggId in aggs) {
|
||
aggDef = _.find(target.bucketAggs, {id: aggId});
|
||
esAgg = aggs[aggId];
|
||
|
||
if (!aggDef) {
|
||
continue;
|
||
}
|
||
|
||
if (depth === maxDepth) {
|
||
if (aggDef.type === 'date_histogram') {
|
||
this.processMetrics(esAgg, target, seriesList, props);
|
||
} else {
|
||
this.processAggregationDocs(esAgg, aggDef, target, table, props);
|
||
}
|
||
} else {
|
||
for (var nameIndex in esAgg.buckets) {
|
||
bucket = esAgg.buckets[nameIndex];
|
||
props = _.clone(props);
|
||
if (bucket.key !== void 0) {
|
||
props[aggDef.field] = bucket.key;
|
||
} else {
|
||
props["filter"] = nameIndex;
|
||
}
|
||
if (bucket.key_as_string) {
|
||
props[aggDef.field] = bucket.key_as_string;
|
||
}
|
||
this.processBuckets(bucket, target, seriesList, table, props, depth+1);
|
||
}
|
||
}
|
||
}
|
||
};
|
||
|
||
ElasticResponse.prototype._getMetricName = function(metric) {
|
||
var metricDef = _.find(queryDef.metricAggTypes, {value: metric});
|
||
if (!metricDef) {
|
||
metricDef = _.find(queryDef.extendedStats, {value: metric});
|
||
}
|
||
|
||
return metricDef ? metricDef.text : metric;
|
||
};
|
||
|
||
ElasticResponse.prototype._getSeriesName = function(series, target, metricTypeCount) {
|
||
var metricName = this._getMetricName(series.metric);
|
||
|
||
if (target.alias) {
|
||
var regex = /\{\{([\s\S]+?)\}\}/g;
|
||
|
||
return target.alias.replace(regex, function(match, g1, g2) {
|
||
var group = g1 || g2;
|
||
|
||
if (group.indexOf('term ') === 0) { return series.props[group.substring(5)]; }
|
||
if (series.props[group] !== void 0) { return series.props[group]; }
|
||
if (group === 'metric') { return metricName; }
|
||
if (group === 'field') { return series.field; }
|
||
|
||
return match;
|
||
});
|
||
}
|
||
|
||
if (series.field && queryDef.isPipelineAgg(series.metric)) {
|
||
var appliedAgg = _.find(target.metrics, { id: series.field });
|
||
if (appliedAgg) {
|
||
metricName += ' ' + queryDef.describeMetric(appliedAgg);
|
||
} else {
|
||
metricName = 'Unset';
|
||
}
|
||
} else if (series.field) {
|
||
metricName += ' ' + series.field;
|
||
}
|
||
|
||
var propKeys = _.keys(series.props);
|
||
if (propKeys.length === 0) {
|
||
return metricName;
|
||
}
|
||
|
||
var name = '';
|
||
for (var propName in series.props) {
|
||
name += series.props[propName] + ' ';
|
||
}
|
||
|
||
if (metricTypeCount === 1) {
|
||
return name.trim();
|
||
}
|
||
|
||
return name.trim() + ' ' + metricName;
|
||
};
|
||
|
||
ElasticResponse.prototype.nameSeries = function(seriesList, target) {
|
||
var metricTypeCount = _.uniq(_.map(seriesList, 'metric')).length;
|
||
var fieldNameCount = _.uniq(_.map(seriesList, 'field')).length;
|
||
|
||
for (var i = 0; i < seriesList.length; i++) {
|
||
var series = seriesList[i];
|
||
series.target = this._getSeriesName(series, target, metricTypeCount, fieldNameCount);
|
||
}
|
||
};
|
||
|
||
ElasticResponse.prototype.processHits = function(hits, seriesList) {
|
||
var series = {target: 'docs', type: 'docs', datapoints: [], total: hits.total, filterable: true};
|
||
var propName, hit, doc, i;
|
||
|
||
for (i = 0; i < hits.hits.length; i++) {
|
||
hit = hits.hits[i];
|
||
doc = {
|
||
_id: hit._id,
|
||
_type: hit._type,
|
||
_index: hit._index
|
||
};
|
||
|
||
if (hit._source) {
|
||
for (propName in hit._source) {
|
||
doc[propName] = hit._source[propName];
|
||
}
|
||
}
|
||
|
||
for (propName in hit.fields) {
|
||
doc[propName] = hit.fields[propName];
|
||
}
|
||
series.datapoints.push(doc);
|
||
}
|
||
|
||
seriesList.push(series);
|
||
};
|
||
|
||
ElasticResponse.prototype.trimDatapoints = function(aggregations, target) {
|
||
var histogram = _.find(target.bucketAggs, { type: 'date_histogram'});
|
||
|
||
var shouldDropFirstAndLast = histogram && histogram.settings && histogram.settings.trimEdges;
|
||
if (shouldDropFirstAndLast) {
|
||
var trim = histogram.settings.trimEdges;
|
||
for (var prop in aggregations) {
|
||
var points = aggregations[prop];
|
||
if (points.datapoints.length > trim * 2) {
|
||
points.datapoints = points.datapoints.slice(trim, points.datapoints.length - trim);
|
||
}
|
||
}
|
||
}
|
||
};
|
||
|
||
ElasticResponse.prototype.getErrorFromElasticResponse = function(response, err) {
|
||
var result: any = {};
|
||
result.data = JSON.stringify(err, null, 4);
|
||
if (err.root_cause && err.root_cause.length > 0 && err.root_cause[0].reason) {
|
||
result.message = err.root_cause[0].reason;
|
||
} else {
|
||
result.message = err.reason || 'Unkown elatic error response';
|
||
}
|
||
|
||
if (response.$$config) {
|
||
result.config = response.$$config;
|
||
}
|
||
|
||
return result;
|
||
};
|
||
|
||
ElasticResponse.prototype.getTimeSeries = function() {
|
||
var seriesList = [];
|
||
|
||
for (var i = 0; i < this.response.responses.length; i++) {
|
||
var response = this.response.responses[i];
|
||
if (response.error) {
|
||
throw this.getErrorFromElasticResponse(this.response, response.error);
|
||
}
|
||
|
||
if (response.hits && response.hits.hits.length > 0) {
|
||
this.processHits(response.hits, seriesList);
|
||
}
|
||
|
||
if (response.aggregations) {
|
||
var aggregations = response.aggregations;
|
||
var target = this.targets[i];
|
||
var tmpSeriesList = [];
|
||
var table = new TableModel();
|
||
|
||
this.processBuckets(aggregations, target, tmpSeriesList, table, {}, 0);
|
||
this.trimDatapoints(tmpSeriesList, target);
|
||
this.nameSeries(tmpSeriesList, target);
|
||
|
||
for (var y = 0; y < tmpSeriesList.length; y++) {
|
||
seriesList.push(tmpSeriesList[y]);
|
||
}
|
||
|
||
if (table.rows.length > 0) {
|
||
seriesList.push(table);
|
||
}
|
||
}
|
||
}
|
||
|
||
return { data: seriesList };
|
||
};
|
||
|