Change top_hits aggregation to top_metrics for snapshot api (#95644)
* Change top_hits aggregations to top_metrics for snapshot api * Fix typing * Remove top_hits types * Add test for top metrics * Fix functional test * Add size 1 to top metrics aggregation * change type for metadata rows Co-authored-by: Kibana Machine <42973632+kibanamachine@users.noreply.github.com>
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@ -282,8 +282,10 @@ export const ESSumBucketAggRT = rt.type({
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}),
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});
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export const ESTopHitsAggRT = rt.type({
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top_hits: rt.object,
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export const ESTopMetricsAggRT = rt.type({
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top_metrics: rt.type({
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metrics: rt.union([rt.array(rt.type({ field: rt.string })), rt.type({ field: rt.string })]),
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}),
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});
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export interface SnapshotTermsWithAggregation {
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@ -309,7 +311,7 @@ export const ESAggregationRT = rt.union([
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ESSumBucketAggRT,
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ESTermsWithAggregationRT,
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ESCaridnalityAggRT,
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ESTopHitsAggRT,
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ESTopMetricsAggRT,
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]);
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export const MetricsUIAggregationRT = rt.record(rt.string, ESAggregationRT);
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@ -81,6 +81,46 @@ Object {
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}
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`;
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exports[`convertHistogramBucketsToTimeseies(keys, options, buckets) should tranform top_metric aggregations 1`] = `
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Object {
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"columns": Array [
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Object {
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"name": "timestamp",
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"type": "date",
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},
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Object {
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"name": "metric_0",
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"type": "number",
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},
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Object {
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"name": "__metadata__",
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"type": "number",
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},
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],
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"id": "example-0",
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"keys": Array [
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"example-0",
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],
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"rows": Array [
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Object {
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"__metadata__": Array [
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Object {
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"host.ip": "testHostIp",
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"host.name": "testHostName",
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},
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],
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"metric_0": 1,
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"timestamp": 1577836800000,
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},
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Object {
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"__metadata__": Array [],
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"metric_0": null,
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"timestamp": 1577836860000,
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},
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],
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}
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`;
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exports[`convertHistogramBucketsToTimeseies(keys, options, buckets) should work with keyed percentiles 1`] = `
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Object {
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"columns": Array [
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@ -118,4 +118,56 @@ describe('convertHistogramBucketsToTimeseies(keys, options, buckets)', () => {
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convertHistogramBucketsToTimeseries(keys, { ...options }, bucketsWithMultipleKeyedPercentiles)
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).toThrow();
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});
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it('should tranform top_metric aggregations', () => {
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const topMetricOptions: MetricsAPIRequest = {
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...options,
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metrics: [
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{ id: 'metric_0', aggregations: { metric_0: { avg: { field: 'system.cpu.user.pct' } } } },
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{
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id: '__metadata__',
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aggregations: {
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__metadata__: {
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top_metrics: {
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metrics: [{ field: 'host.name' }, { field: 'host.ip' }],
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},
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},
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},
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},
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],
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};
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const bucketsWithTopAggregation = [
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{
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key: 1577836800000,
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key_as_string: '2020-01-01T00:00:00.000Z',
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doc_count: 1,
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metric_0: { value: 1 },
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__metadata__: {
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top: [
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{
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sort: ['2021-03-30T13:46:27.684Z'],
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metrics: {
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'host.name': 'testHostName',
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'host.ip': 'testHostIp',
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},
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},
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],
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},
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},
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{
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key: 1577836860000,
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key_as_string: '2020-01-01T00:01:00.000Z',
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doc_count: 1,
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metric_0: { value: null },
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__metadata__: {
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top: [],
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},
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},
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];
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expect(
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convertHistogramBucketsToTimeseries(keys, topMetricOptions, bucketsWithTopAggregation)
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).toMatchSnapshot();
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});
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});
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@ -19,7 +19,7 @@ import {
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NormalizedMetricValueRT,
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PercentilesTypeRT,
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PercentilesKeyedTypeRT,
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TopHitsTypeRT,
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TopMetricsTypeRT,
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MetricValueTypeRT,
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} from '../types';
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@ -57,8 +57,8 @@ const getValue = (valueObject: ValueObjectType) => {
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return valueObject.value;
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}
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if (TopHitsTypeRT.is(valueObject)) {
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return valueObject.hits.hits.map((hit) => hit._source);
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if (TopMetricsTypeRT.is(valueObject)) {
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return valueObject.top.map((res) => res.metrics);
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}
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return null;
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@ -26,27 +26,13 @@ export const PercentilesKeyedTypeRT = rt.type({
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values: rt.array(rt.type({ key: rt.string, value: NumberOrNullRT })),
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});
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export const TopHitsTypeRT = rt.type({
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hits: rt.type({
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total: rt.type({
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value: rt.number,
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relation: rt.string,
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}),
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hits: rt.array(
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rt.intersection([
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rt.type({
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_index: rt.string,
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_id: rt.string,
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_score: NumberOrNullRT,
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_source: rt.object,
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}),
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rt.partial({
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sort: rt.array(rt.union([rt.string, rt.number])),
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max_score: NumberOrNullRT,
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}),
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])
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),
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}),
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export const TopMetricsTypeRT = rt.type({
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top: rt.array(
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rt.type({
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sort: rt.union([rt.array(rt.number), rt.array(rt.string)]),
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metrics: rt.record(rt.string, rt.union([rt.number, rt.string, rt.null])),
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})
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),
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});
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export const MetricValueTypeRT = rt.union([
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@ -54,7 +40,7 @@ export const MetricValueTypeRT = rt.union([
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NormalizedMetricValueRT,
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PercentilesTypeRT,
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PercentilesKeyedTypeRT,
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TopHitsTypeRT,
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TopMetricsTypeRT,
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]);
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export type MetricValueType = rt.TypeOf<typeof MetricValueTypeRT>;
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@ -20,7 +20,7 @@ import { InfraSource } from '../../../lib/sources';
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export const isIPv4 = (subject: string) => /^(?:[0-9]{1,3}\.){3}[0-9]{1,3}$/.test(subject);
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type RowWithMetadata = MetricsAPIRow & {
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[META_KEY]: object[];
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[META_KEY]: Array<Record<string, string | number | string[]>>;
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};
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export const applyMetadataToLastPath = (
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@ -47,7 +47,7 @@ export const applyMetadataToLastPath = (
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source.configuration.fields
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);
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// Set the label as the name and fallback to the id OR path.value
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lastPath.label = get(firstMetaDoc, inventoryFields.name, lastPath.value);
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lastPath.label = (firstMetaDoc[inventoryFields.name] ?? lastPath.value) as string;
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// If the inventory fields contain an ip address, we need to try and set that
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// on the path object. IP addersses are typically stored as multiple fields. We will
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// use the first IPV4 address we find.
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@ -72,16 +72,19 @@ export const transformRequestToMetricsAPIRequest = async (
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id: META_KEY,
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aggregations: {
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[META_KEY]: {
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top_hits: {
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top_metrics: {
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size: 1,
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_source: [inventoryFields.name],
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sort: [{ [sourceOverrides?.timestamp ?? source.configuration.fields.timestamp]: 'desc' }],
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metrics: [{ field: inventoryFields.name }],
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sort: {
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[source.configuration.fields.timestamp]: 'desc',
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},
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},
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},
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},
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};
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if (inventoryFields.ip) {
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metaAggregation.aggregations[META_KEY].top_hits._source.push(inventoryFields.ip);
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metaAggregation.aggregations[META_KEY].top_metrics.metrics.push({ field: inventoryFields.ip });
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}
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metricsApiRequest.metrics.push(metaAggregation);
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