grafana/pkg/tsdb/elasticsearch/data_query.go
Ivana Huckova 494d169980
Elasticsearch: Fix legend for alerting, expressions and previously frontend queries (#84485)
* Elasticsearch: Fix legend for alerting, expressions and previously frontend queries

* Add comment

* Update comment
2024-03-18 18:01:33 +01:00

511 lines
17 KiB
Go

package elasticsearch
import (
"context"
"encoding/json"
"fmt"
"regexp"
"slices"
"strconv"
"time"
"github.com/grafana/grafana-plugin-sdk-go/backend"
"github.com/grafana/grafana-plugin-sdk-go/experimental/errorsource"
"github.com/grafana/grafana/pkg/components/simplejson"
"github.com/grafana/grafana/pkg/infra/log"
"github.com/grafana/grafana/pkg/infra/tracing"
es "github.com/grafana/grafana/pkg/tsdb/elasticsearch/client"
)
const (
defaultSize = 500
)
type elasticsearchDataQuery struct {
client es.Client
dataQueries []backend.DataQuery
logger log.Logger
ctx context.Context
tracer tracing.Tracer
keepLabelsInResponse bool
}
var newElasticsearchDataQuery = func(ctx context.Context, client es.Client, req *backend.QueryDataRequest, logger log.Logger, tracer tracing.Tracer) *elasticsearchDataQuery {
_, fromAlert := req.Headers[headerFromAlert]
fromExpression := req.GetHTTPHeader(headerFromExpression) != ""
return &elasticsearchDataQuery{
client: client,
dataQueries: req.Queries,
logger: logger,
ctx: ctx,
tracer: tracer,
// To maintain backward compatibility, it is necessary to keep labels in responses for alerting and expressions queries.
// Historically, these labels have been used in alerting rules and transformations.
keepLabelsInResponse: fromAlert || fromExpression,
}
}
func (e *elasticsearchDataQuery) execute() (*backend.QueryDataResponse, error) {
start := time.Now()
response := backend.NewQueryDataResponse()
e.logger.Debug("Parsing queries", "queriesLength", len(e.dataQueries))
queries, err := parseQuery(e.dataQueries, e.logger)
if err != nil {
mq, _ := json.Marshal(e.dataQueries)
e.logger.Error("Failed to parse queries", "error", err, "queries", string(mq), "queriesLength", len(queries), "duration", time.Since(start), "stage", es.StagePrepareRequest)
return errorsource.AddPluginErrorToResponse(e.dataQueries[0].RefID, response, err), nil
}
ms := e.client.MultiSearch()
for _, q := range queries {
from := q.TimeRange.From.UnixNano() / int64(time.Millisecond)
to := q.TimeRange.To.UnixNano() / int64(time.Millisecond)
if err := e.processQuery(q, ms, from, to); err != nil {
mq, _ := json.Marshal(q)
e.logger.Error("Failed to process query to multisearch request builder", "error", err, "query", string(mq), "queriesLength", len(queries), "duration", time.Since(start), "stage", es.StagePrepareRequest)
return errorsource.AddPluginErrorToResponse(q.RefID, response, err), nil
}
}
req, err := ms.Build()
if err != nil {
mqs, _ := json.Marshal(e.dataQueries)
e.logger.Error("Failed to build multisearch request", "error", err, "queriesLength", len(queries), "queries", string(mqs), "duration", time.Since(start), "stage", es.StagePrepareRequest)
return errorsource.AddPluginErrorToResponse(e.dataQueries[0].RefID, response, err), nil
}
e.logger.Info("Prepared request", "queriesLength", len(queries), "duration", time.Since(start), "stage", es.StagePrepareRequest)
res, err := e.client.ExecuteMultisearch(req)
if err != nil {
// We are returning error containing the source that was added trough errorsource.Middleware
return errorsource.AddErrorToResponse(e.dataQueries[0].RefID, response, err), nil
}
return parseResponse(e.ctx, res.Responses, queries, e.client.GetConfiguredFields(), e.keepLabelsInResponse, e.logger, e.tracer)
}
func (e *elasticsearchDataQuery) processQuery(q *Query, ms *es.MultiSearchRequestBuilder, from, to int64) error {
err := isQueryWithError(q)
if err != nil {
err = fmt.Errorf("received invalid query. %w", err)
return err
}
defaultTimeField := e.client.GetConfiguredFields().TimeField
b := ms.Search(q.Interval, q.TimeRange)
b.Size(0)
filters := b.Query().Bool().Filter()
filters.AddDateRangeFilter(defaultTimeField, to, from, es.DateFormatEpochMS)
filters.AddQueryStringFilter(q.RawQuery, true)
if isLogsQuery(q) {
processLogsQuery(q, b, from, to, defaultTimeField)
} else if isDocumentQuery(q) {
processDocumentQuery(q, b, from, to, defaultTimeField)
} else {
// Otherwise, it is a time series query and we process it
processTimeSeriesQuery(q, b, from, to, defaultTimeField)
}
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() map[string]any {
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()
}
if err == nil {
metricAggregation.Settings.SetPath([]string{"script"}, scriptValue)
}
}
return metricAggregation.Settings.MustMap()
}
func (bucketAgg BucketAgg) generateSettingsForDSL() map[string]any {
setIntPath(bucketAgg.Settings, "min_doc_count")
return bucketAgg.Settings.MustMap()
}
func addDateHistogramAgg(aggBuilder es.AggBuilder, bucketAgg *BucketAgg, timeFrom, timeTo int64, timeField string) es.AggBuilder {
// If no field is specified, use the time field
field := bucketAgg.Field
if field == "" {
field = timeField
}
aggBuilder.DateHistogram(bucketAgg.ID, field, func(a *es.DateHistogramAgg, b es.AggBuilder) {
var interval = bucketAgg.Settings.Get("interval").MustString("auto")
if slices.Contains(es.GetCalendarIntervals(), interval) {
a.CalendarInterval = interval
} else {
if interval == "auto" {
// note this is not really a valid grafana-variable-handling,
// because normally this would not match `$__interval_ms`,
// but because how we apply these in the go-code, this will work
// correctly, and becomes something like `500ms`.
// a nicer way would be to use `${__interval_ms}ms`, but
// that format is not recognized where we apply these variables
// in the elasticsearch datasource
a.FixedInterval = "$__interval_msms"
} else {
a.FixedInterval = interval
}
}
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 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 = stringToIntWithDefaultValue(bucketAgg.Settings.Get("interval").MustString(), 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 {
a.Size = stringToIntWithDefaultValue(bucketAgg.Settings.Get("size").MustString(), defaultSize)
}
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 addNestedAgg(aggBuilder es.AggBuilder, bucketAgg *BucketAgg) es.AggBuilder {
aggBuilder.Nested(bucketAgg.ID, bucketAgg.Field, func(a *es.NestedAggregation, b es.AggBuilder) {
aggBuilder = b
})
return aggBuilder
}
func addFiltersAgg(aggBuilder es.AggBuilder, bucketAgg *BucketAgg) es.AggBuilder {
filters := make(map[string]any)
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 = stringToIntWithDefaultValue(bucketAgg.Settings.Get("precision").MustString(), es.DefaultGeoHashPrecision)
aggBuilder = b
})
return aggBuilder
}
func getPipelineAggField(m *MetricAgg) string {
// In frontend we are using Field as pipelineAggField
// There might be historical reason why in backend we were using PipelineAggregate as pipelineAggField
// So for now let's check Field first and then PipelineAggregate to ensure that we are not breaking anything
// TODO: Investigate, if we can remove check for PipelineAggregate
pipelineAggField := m.Field
if pipelineAggField == "" {
pipelineAggField = m.PipelineAggregate
}
return pipelineAggField
}
func isQueryWithError(query *Query) error {
if len(query.BucketAggs) == 0 {
// If no aggregations, only document and logs queries are valid
if len(query.Metrics) == 0 || !(isLogsQuery(query) || isDocumentQuery(query)) {
return fmt.Errorf("invalid query, missing metrics and aggregations")
}
}
return nil
}
func isLogsQuery(query *Query) bool {
return query.Metrics[0].Type == logsType
}
func isDocumentQuery(query *Query) bool {
return isRawDataQuery(query) || isRawDocumentQuery(query)
}
func isRawDataQuery(query *Query) bool {
return query.Metrics[0].Type == rawDataType
}
func isRawDocumentQuery(query *Query) bool {
return query.Metrics[0].Type == rawDocumentType
}
func processLogsQuery(q *Query, b *es.SearchRequestBuilder, from, to int64, defaultTimeField string) {
metric := q.Metrics[0]
sort := es.SortOrderDesc
if metric.Settings.Get("sortDirection").MustString() == "asc" {
// This is currently used only for log context query
sort = es.SortOrderAsc
}
b.Sort(sort, defaultTimeField, "boolean")
b.Sort(sort, "_doc", "")
b.AddDocValueField(defaultTimeField)
// We need to add timeField as field with standardized time format to not receive
// invalid formats that elasticsearch can parse, but our frontend can't (e.g. yyyy_MM_dd_HH_mm_ss)
b.AddTimeFieldWithStandardizedFormat(defaultTimeField)
b.Size(stringToIntWithDefaultValue(metric.Settings.Get("limit").MustString(), defaultSize))
b.AddHighlight()
// This is currently used only for log context query to get
// log lines before and after the selected log line
searchAfter := metric.Settings.Get("searchAfter").MustArray()
for _, value := range searchAfter {
b.AddSearchAfter(value)
}
// For log query, we add a date histogram aggregation
aggBuilder := b.Agg()
q.BucketAggs = append(q.BucketAggs, &BucketAgg{
Type: dateHistType,
Field: defaultTimeField,
ID: "1",
Settings: simplejson.NewFromAny(map[string]any{
"interval": "auto",
}),
})
bucketAgg := q.BucketAggs[0]
bucketAgg.Settings = simplejson.NewFromAny(
bucketAgg.generateSettingsForDSL(),
)
_ = addDateHistogramAgg(aggBuilder, bucketAgg, from, to, defaultTimeField)
}
func processDocumentQuery(q *Query, b *es.SearchRequestBuilder, from, to int64, defaultTimeField string) {
metric := q.Metrics[0]
b.Sort(es.SortOrderDesc, defaultTimeField, "boolean")
b.Sort(es.SortOrderDesc, "_doc", "")
b.AddDocValueField(defaultTimeField)
if isRawDataQuery(q) {
// For raw_data queries we need to add timeField as field with standardized time format to not receive
// invalid formats that elasticsearch can parse, but our frontend can't (e.g. yyyy_MM_dd_HH_mm_ss)
b.AddTimeFieldWithStandardizedFormat(defaultTimeField)
}
b.Size(stringToIntWithDefaultValue(metric.Settings.Get("size").MustString(), defaultSize))
}
func processTimeSeriesQuery(q *Query, b *es.SearchRequestBuilder, from, to int64, defaultTimeField string) {
aggBuilder := b.Agg()
// Process buckets
// 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, defaultTimeField)
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)
case nestedType:
aggBuilder = addNestedAgg(aggBuilder, bucketAgg)
}
}
// Process metrics
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]any{}
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()
})
} else {
continue
}
} else {
pipelineAggField := getPipelineAggField(m)
if _, err := strconv.Atoi(pipelineAggField); err == nil {
var appliedAgg *MetricAgg
for _, pipelineMetric := range q.Metrics {
if pipelineMetric.ID == pipelineAggField {
appliedAgg = pipelineMetric
break
}
}
if appliedAgg != nil {
bucketPath := pipelineAggField
if appliedAgg.Type == countType {
bucketPath = "_count"
}
aggBuilder.Pipeline(m.ID, m.Type, bucketPath, func(a *es.PipelineAggregation) {
a.Settings = m.generateSettingsForDSL()
})
}
} else {
continue
}
}
} else {
aggBuilder.Metric(m.ID, m.Type, m.Field, func(a *es.MetricAggregation) {
a.Settings = m.generateSettingsForDSL()
})
}
}
}
func stringToIntWithDefaultValue(valueStr string, defaultValue int) int {
value, err := strconv.Atoi(valueStr)
if err != nil {
value = defaultValue
}
// In our case, 0 is not a valid value and in this case we default to defaultValue
if value == 0 {
value = defaultValue
}
return value
}