grafana/pkg/tsdb/elasticsearch/time_series_query.go
Piotr Jamróz 9fb8339f87
Elastic: Allow using long/int as date field for alerts (#44027)
* Use integers for time range filter

Previously it was passed as a string which is automatically converted by Elastic to a number only if the field type is "date". For other types (e.g. "long") such conversion doesn't work. In theory "date" could be passed as a formatted string but we don't use it this way and always pass it as a number so it is safe to always pass numbers, not strings.

* Fix time_series_query_test

* Retrigger build
2022-01-17 15:45:09 +01:00

477 lines
14 KiB
Go

package elasticsearch
import (
"fmt"
"regexp"
"strconv"
"time"
"github.com/Masterminds/semver"
"github.com/grafana/grafana-plugin-sdk-go/backend"
"github.com/grafana/grafana/pkg/components/simplejson"
es "github.com/grafana/grafana/pkg/tsdb/elasticsearch/client"
"github.com/grafana/grafana/pkg/tsdb/intervalv2"
)
type timeSeriesQuery struct {
client es.Client
dataQueries []backend.DataQuery
intervalCalculator intervalv2.Calculator
}
var newTimeSeriesQuery = func(client es.Client, dataQuery []backend.DataQuery,
intervalCalculator intervalv2.Calculator) *timeSeriesQuery {
return &timeSeriesQuery{
client: client,
dataQueries: dataQuery,
intervalCalculator: intervalCalculator,
}
}
func (e *timeSeriesQuery) execute() (*backend.QueryDataResponse, error) {
tsQueryParser := newTimeSeriesQueryParser()
queries, err := tsQueryParser.parse(e.dataQueries)
if err != nil {
return &backend.QueryDataResponse{}, err
}
ms := e.client.MultiSearch()
from := e.dataQueries[0].TimeRange.From.UnixNano() / int64(time.Millisecond)
to := e.dataQueries[0].TimeRange.To.UnixNano() / int64(time.Millisecond)
result := backend.QueryDataResponse{
Responses: backend.Responses{},
}
for _, q := range queries {
if err := e.processQuery(q, ms, from, to, result); err != nil {
return &backend.QueryDataResponse{}, err
}
}
req, err := ms.Build()
if err != nil {
return &backend.QueryDataResponse{}, err
}
res, err := e.client.ExecuteMultisearch(req)
if err != nil {
return &backend.QueryDataResponse{}, err
}
rp := newResponseParser(res.Responses, queries, res.DebugInfo)
return rp.getTimeSeries()
}
func (e *timeSeriesQuery) processQuery(q *Query, ms *es.MultiSearchRequestBuilder, from, to int64,
result backend.QueryDataResponse) error {
minInterval, err := e.client.GetMinInterval(q.Interval)
if err != nil {
return err
}
interval := e.intervalCalculator.Calculate(e.dataQueries[0].TimeRange, minInterval, q.MaxDataPoints)
b := ms.Search(interval)
b.Size(0)
filters := b.Query().Bool().Filter()
filters.AddDateRangeFilter(e.client.GetTimeField(), to, from, es.DateFormatEpochMS)
if q.RawQuery != "" {
filters.AddQueryStringFilter(q.RawQuery, true)
}
if len(q.BucketAggs) == 0 {
if len(q.Metrics) == 0 || q.Metrics[0].Type != "raw_document" {
result.Responses[q.RefID] = backend.DataResponse{
Error: fmt.Errorf("invalid query, missing metrics and aggregations"),
}
return nil
}
metric := q.Metrics[0]
b.Size(metric.Settings.Get("size").MustInt(500))
b.SortDesc("@timestamp", "boolean")
b.AddDocValueField("@timestamp")
return nil
}
aggBuilder := b.Agg()
// iterate backwards to create aggregations bottom-down
for _, bucketAgg := range q.BucketAggs {
bucketAgg.Settings = simplejson.NewFromAny(
bucketAgg.generateSettingsForDSL(),
)
switch bucketAgg.Type {
case dateHistType:
aggBuilder = addDateHistogramAgg(aggBuilder, bucketAgg, from, to)
case histogramType:
aggBuilder = addHistogramAgg(aggBuilder, bucketAgg)
case filtersType:
aggBuilder = addFiltersAgg(aggBuilder, bucketAgg)
case termsType:
aggBuilder = addTermsAgg(aggBuilder, bucketAgg, q.Metrics)
case geohashGridType:
aggBuilder = addGeoHashGridAgg(aggBuilder, bucketAgg)
}
}
for _, m := range q.Metrics {
m := m
if m.Type == countType {
continue
}
if isPipelineAgg(m.Type) {
if isPipelineAggWithMultipleBucketPaths(m.Type) {
if len(m.PipelineVariables) > 0 {
bucketPaths := map[string]interface{}{}
for name, pipelineAgg := range m.PipelineVariables {
if _, err := strconv.Atoi(pipelineAgg); err == nil {
var appliedAgg *MetricAgg
for _, pipelineMetric := range q.Metrics {
if pipelineMetric.ID == pipelineAgg {
appliedAgg = pipelineMetric
break
}
}
if appliedAgg != nil {
if appliedAgg.Type == countType {
bucketPaths[name] = "_count"
} else {
bucketPaths[name] = pipelineAgg
}
}
}
}
aggBuilder.Pipeline(m.ID, m.Type, bucketPaths, func(a *es.PipelineAggregation) {
a.Settings = m.generateSettingsForDSL(e.client.GetVersion())
})
} else {
continue
}
} else {
if _, err := strconv.Atoi(m.PipelineAggregate); err == nil {
var appliedAgg *MetricAgg
for _, pipelineMetric := range q.Metrics {
if pipelineMetric.ID == m.PipelineAggregate {
appliedAgg = pipelineMetric
break
}
}
if appliedAgg != nil {
bucketPath := m.PipelineAggregate
if appliedAgg.Type == countType {
bucketPath = "_count"
}
aggBuilder.Pipeline(m.ID, m.Type, bucketPath, func(a *es.PipelineAggregation) {
a.Settings = m.generateSettingsForDSL(e.client.GetVersion())
})
}
} else {
continue
}
}
} else {
aggBuilder.Metric(m.ID, m.Type, m.Field, func(a *es.MetricAggregation) {
a.Settings = m.generateSettingsForDSL(e.client.GetVersion())
})
}
}
return nil
}
func setFloatPath(settings *simplejson.Json, path ...string) {
if stringValue, err := settings.GetPath(path...).String(); err == nil {
if value, err := strconv.ParseFloat(stringValue, 64); err == nil {
settings.SetPath(path, value)
}
}
}
func setIntPath(settings *simplejson.Json, path ...string) {
if stringValue, err := settings.GetPath(path...).String(); err == nil {
if value, err := strconv.ParseInt(stringValue, 10, 64); err == nil {
settings.SetPath(path, value)
}
}
}
// Casts values to float when required by Elastic's query DSL
func (metricAggregation MetricAgg) generateSettingsForDSL(version *semver.Version) map[string]interface{} {
switch metricAggregation.Type {
case "moving_avg":
setFloatPath(metricAggregation.Settings, "window")
setFloatPath(metricAggregation.Settings, "predict")
setFloatPath(metricAggregation.Settings, "settings", "alpha")
setFloatPath(metricAggregation.Settings, "settings", "beta")
setFloatPath(metricAggregation.Settings, "settings", "gamma")
setFloatPath(metricAggregation.Settings, "settings", "period")
case "serial_diff":
setFloatPath(metricAggregation.Settings, "lag")
}
if isMetricAggregationWithInlineScriptSupport(metricAggregation.Type) {
scriptValue, err := metricAggregation.Settings.GetPath("script").String()
if err != nil {
// the script is stored using the old format : `script:{inline: "value"}` or is not set
scriptValue, err = metricAggregation.Settings.GetPath("script", "inline").String()
}
constraint, _ := semver.NewConstraint(">=5.6.0")
if err == nil {
if constraint.Check(version) {
metricAggregation.Settings.SetPath([]string{"script"}, scriptValue)
} else {
metricAggregation.Settings.SetPath([]string{"script"}, map[string]interface{}{"inline": scriptValue})
}
}
}
return metricAggregation.Settings.MustMap()
}
func (bucketAgg BucketAgg) generateSettingsForDSL() map[string]interface{} {
// TODO: This might also need to be applied to other bucket aggregations and other fields.
switch bucketAgg.Type {
case "date_histogram":
setIntPath(bucketAgg.Settings, "min_doc_count")
}
return bucketAgg.Settings.MustMap()
}
func addDateHistogramAgg(aggBuilder es.AggBuilder, bucketAgg *BucketAgg, timeFrom, timeTo int64) es.AggBuilder {
aggBuilder.DateHistogram(bucketAgg.ID, bucketAgg.Field, func(a *es.DateHistogramAgg, b es.AggBuilder) {
a.Interval = bucketAgg.Settings.Get("interval").MustString("auto")
a.MinDocCount = bucketAgg.Settings.Get("min_doc_count").MustInt(0)
a.ExtendedBounds = &es.ExtendedBounds{Min: timeFrom, Max: timeTo}
a.Format = bucketAgg.Settings.Get("format").MustString(es.DateFormatEpochMS)
if a.Interval == "auto" {
a.Interval = "$__interval"
}
if offset, err := bucketAgg.Settings.Get("offset").String(); err == nil {
a.Offset = offset
}
if missing, err := bucketAgg.Settings.Get("missing").String(); err == nil {
a.Missing = &missing
}
if timezone, err := bucketAgg.Settings.Get("timeZone").String(); err == nil {
if timezone != "utc" {
a.TimeZone = timezone
}
}
aggBuilder = b
})
return aggBuilder
}
func addHistogramAgg(aggBuilder es.AggBuilder, bucketAgg *BucketAgg) es.AggBuilder {
aggBuilder.Histogram(bucketAgg.ID, bucketAgg.Field, func(a *es.HistogramAgg, b es.AggBuilder) {
a.Interval = bucketAgg.Settings.Get("interval").MustInt(1000)
a.MinDocCount = bucketAgg.Settings.Get("min_doc_count").MustInt(0)
if missing, err := bucketAgg.Settings.Get("missing").Int(); err == nil {
a.Missing = &missing
}
aggBuilder = b
})
return aggBuilder
}
func addTermsAgg(aggBuilder es.AggBuilder, bucketAgg *BucketAgg, metrics []*MetricAgg) es.AggBuilder {
aggBuilder.Terms(bucketAgg.ID, bucketAgg.Field, func(a *es.TermsAggregation, b es.AggBuilder) {
if size, err := bucketAgg.Settings.Get("size").Int(); err == nil {
a.Size = size
} else if size, err := bucketAgg.Settings.Get("size").String(); err == nil {
a.Size, err = strconv.Atoi(size)
if err != nil {
a.Size = 500
}
} else {
a.Size = 500
}
if a.Size == 0 {
a.Size = 500
}
if minDocCount, err := bucketAgg.Settings.Get("min_doc_count").Int(); err == nil {
a.MinDocCount = &minDocCount
}
if missing, err := bucketAgg.Settings.Get("missing").String(); err == nil {
a.Missing = &missing
}
if orderBy, err := bucketAgg.Settings.Get("orderBy").String(); err == nil {
/*
The format for extended stats and percentiles is {metricId}[bucket_path]
for everything else it's just {metricId}, _count, _term, or _key
*/
metricIdRegex := regexp.MustCompile(`^(\d+)`)
metricId := metricIdRegex.FindString(orderBy)
if len(metricId) > 0 {
for _, m := range metrics {
if m.ID == metricId {
if m.Type == "count" {
a.Order["_count"] = bucketAgg.Settings.Get("order").MustString("desc")
} else {
a.Order[orderBy] = bucketAgg.Settings.Get("order").MustString("desc")
b.Metric(m.ID, m.Type, m.Field, nil)
}
break
}
}
} else {
a.Order[orderBy] = bucketAgg.Settings.Get("order").MustString("desc")
}
}
aggBuilder = b
})
return aggBuilder
}
func addFiltersAgg(aggBuilder es.AggBuilder, bucketAgg *BucketAgg) es.AggBuilder {
filters := make(map[string]interface{})
for _, filter := range bucketAgg.Settings.Get("filters").MustArray() {
json := simplejson.NewFromAny(filter)
query := json.Get("query").MustString()
label := json.Get("label").MustString()
if label == "" {
label = query
}
filters[label] = &es.QueryStringFilter{Query: query, AnalyzeWildcard: true}
}
if len(filters) > 0 {
aggBuilder.Filters(bucketAgg.ID, func(a *es.FiltersAggregation, b es.AggBuilder) {
a.Filters = filters
aggBuilder = b
})
}
return aggBuilder
}
func addGeoHashGridAgg(aggBuilder es.AggBuilder, bucketAgg *BucketAgg) es.AggBuilder {
aggBuilder.GeoHashGrid(bucketAgg.ID, bucketAgg.Field, func(a *es.GeoHashGridAggregation, b es.AggBuilder) {
a.Precision = bucketAgg.Settings.Get("precision").MustInt(3)
aggBuilder = b
})
return aggBuilder
}
type timeSeriesQueryParser struct{}
func newTimeSeriesQueryParser() *timeSeriesQueryParser {
return &timeSeriesQueryParser{}
}
func (p *timeSeriesQueryParser) parse(tsdbQuery []backend.DataQuery) ([]*Query, error) {
queries := make([]*Query, 0)
for _, q := range tsdbQuery {
model, err := simplejson.NewJson(q.JSON)
if err != nil {
return nil, err
}
timeField, err := model.Get("timeField").String()
if err != nil {
return nil, err
}
rawQuery := model.Get("query").MustString()
bucketAggs, err := p.parseBucketAggs(model)
if err != nil {
return nil, err
}
metrics, err := p.parseMetrics(model)
if err != nil {
return nil, err
}
alias := model.Get("alias").MustString("")
interval := model.Get("interval").MustString("")
queries = append(queries, &Query{
TimeField: timeField,
RawQuery: rawQuery,
BucketAggs: bucketAggs,
Metrics: metrics,
Alias: alias,
Interval: interval,
RefID: q.RefID,
MaxDataPoints: q.MaxDataPoints,
})
}
return queries, nil
}
func (p *timeSeriesQueryParser) parseBucketAggs(model *simplejson.Json) ([]*BucketAgg, error) {
var err error
var result []*BucketAgg
for _, t := range model.Get("bucketAggs").MustArray() {
aggJSON := simplejson.NewFromAny(t)
agg := &BucketAgg{}
agg.Type, err = aggJSON.Get("type").String()
if err != nil {
return nil, err
}
agg.ID, err = aggJSON.Get("id").String()
if err != nil {
return nil, err
}
agg.Field = aggJSON.Get("field").MustString()
agg.Settings = simplejson.NewFromAny(aggJSON.Get("settings").MustMap())
result = append(result, agg)
}
return result, nil
}
func (p *timeSeriesQueryParser) parseMetrics(model *simplejson.Json) ([]*MetricAgg, error) {
var err error
var result []*MetricAgg
for _, t := range model.Get("metrics").MustArray() {
metricJSON := simplejson.NewFromAny(t)
metric := &MetricAgg{}
metric.Field = metricJSON.Get("field").MustString()
metric.Hide = metricJSON.Get("hide").MustBool(false)
metric.ID = metricJSON.Get("id").MustString()
metric.PipelineAggregate = metricJSON.Get("pipelineAgg").MustString()
metric.Settings = simplejson.NewFromAny(metricJSON.Get("settings").MustMap())
metric.Meta = simplejson.NewFromAny(metricJSON.Get("meta").MustMap())
metric.Type, err = metricJSON.Get("type").String()
if err != nil {
return nil, err
}
if isPipelineAggWithMultipleBucketPaths(metric.Type) {
metric.PipelineVariables = map[string]string{}
pvArr := metricJSON.Get("pipelineVariables").MustArray()
for _, v := range pvArr {
kv := v.(map[string]interface{})
metric.PipelineVariables[kv["name"].(string)] = kv["pipelineAgg"].(string)
}
}
result = append(result, metric)
}
return result, nil
}