package logql import ( "context" "errors" "flag" "fmt" "sort" "strconv" "strings" "time" "github.com/opentracing/opentracing-go" "github.com/grafana/loki/v3/pkg/logqlmodel/metadata" "github.com/go-kit/log" "github.com/go-kit/log/level" "github.com/prometheus/client_golang/prometheus" "github.com/prometheus/client_golang/prometheus/promauto" "github.com/prometheus/common/model" "github.com/prometheus/prometheus/model/labels" "github.com/prometheus/prometheus/promql" promql_parser "github.com/prometheus/prometheus/promql/parser" "github.com/grafana/dskit/tenant" "github.com/grafana/loki/v3/pkg/iter" "github.com/grafana/loki/v3/pkg/logproto" "github.com/grafana/loki/v3/pkg/logql/syntax" "github.com/grafana/loki/v3/pkg/logqlmodel" "github.com/grafana/loki/v3/pkg/logqlmodel/stats" "github.com/grafana/loki/v3/pkg/util" "github.com/grafana/loki/v3/pkg/util/constants" "github.com/grafana/loki/v3/pkg/util/httpreq" logutil "github.com/grafana/loki/v3/pkg/util/log" "github.com/grafana/loki/v3/pkg/util/server" "github.com/grafana/loki/v3/pkg/util/validation" ) const ( DefaultBlockedQueryMessage = "blocked by policy" ) var ( QueryTime = promauto.NewHistogramVec(prometheus.HistogramOpts{ Namespace: "logql", Name: "query_duration_seconds", Help: "LogQL query timings", Buckets: prometheus.DefBuckets, }, []string{"query_type"}) QueriesBlocked = promauto.NewCounterVec(prometheus.CounterOpts{ Namespace: constants.Loki, Name: "blocked_queries", Help: "Count of queries blocked by per-tenant policy", }, []string{"user"}) lastEntryMinTime = time.Unix(-100, 0) ) type QueryParams interface { LogSelector() (syntax.LogSelectorExpr, error) GetStart() time.Time GetEnd() time.Time GetShards() []string } // SelectParams specifies parameters passed to data selections. type SelectLogParams struct { *logproto.QueryRequest } func (s SelectLogParams) WithStoreChunks(chunkRefGroup *logproto.ChunkRefGroup) SelectLogParams { cpy := *s.QueryRequest cpy.StoreChunks = chunkRefGroup return SelectLogParams{&cpy} } func (s SelectLogParams) String() string { if s.QueryRequest != nil { return fmt.Sprintf("selector=%s, direction=%s, start=%s, end=%s, limit=%d, shards=%s", s.Selector, logproto.Direction_name[int32(s.Direction)], s.Start, s.End, s.Limit, strings.Join(s.Shards, ",")) } return "" } // LogSelector returns the LogSelectorExpr from the SelectParams. // The `LogSelectorExpr` can then returns all matchers and filters to use for that request. func (s SelectLogParams) LogSelector() (syntax.LogSelectorExpr, error) { if s.QueryRequest.Plan == nil { return nil, errors.New("query plan is empty") } expr, ok := s.QueryRequest.Plan.AST.(syntax.LogSelectorExpr) if !ok { return nil, errors.New("only log selector is supported") } return expr, nil } type SelectSampleParams struct { *logproto.SampleQueryRequest } func (s SelectSampleParams) WithStoreChunks(chunkRefGroup *logproto.ChunkRefGroup) SelectSampleParams { cpy := *s.SampleQueryRequest cpy.StoreChunks = chunkRefGroup return SelectSampleParams{&cpy} } // Expr returns the SampleExpr from the SelectSampleParams. // The `LogSelectorExpr` can then returns all matchers and filters to use for that request. func (s SelectSampleParams) Expr() (syntax.SampleExpr, error) { if s.SampleQueryRequest.Plan == nil { return nil, errors.New("query plan is empty") } expr, ok := s.SampleQueryRequest.Plan.AST.(syntax.SampleExpr) if !ok { return nil, errors.New("only sample expression supported") } return expr, nil } // LogSelector returns the LogSelectorExpr from the SelectParams. // The `LogSelectorExpr` can then returns all matchers and filters to use for that request. func (s SelectSampleParams) LogSelector() (syntax.LogSelectorExpr, error) { expr, err := s.Expr() if err != nil { return nil, err } return expr.Selector() } // Querier allows a LogQL expression to fetch an EntryIterator for a // set of matchers and filters type Querier interface { SelectLogs(context.Context, SelectLogParams) (iter.EntryIterator, error) SelectSamples(context.Context, SelectSampleParams) (iter.SampleIterator, error) } // EngineOpts is the list of options to use with the LogQL query engine. type EngineOpts struct { // MaxLookBackPeriod is the maximum amount of time to look back for log lines. // only used for instant log queries. MaxLookBackPeriod time.Duration `yaml:"max_look_back_period"` // LogExecutingQuery will control if we log the query when Exec is called. LogExecutingQuery bool `yaml:"-"` } func (opts *EngineOpts) RegisterFlagsWithPrefix(prefix string, f *flag.FlagSet) { f.DurationVar(&opts.MaxLookBackPeriod, prefix+".engine.max-lookback-period", 30*time.Second, "The maximum amount of time to look back for log lines. Used only for instant log queries.") // Log executing query by default opts.LogExecutingQuery = true } func (opts *EngineOpts) applyDefault() { if opts.MaxLookBackPeriod == 0 { opts.MaxLookBackPeriod = 30 * time.Second } } // Engine is the LogQL engine. type Engine struct { logger log.Logger evaluatorFactory EvaluatorFactory limits Limits opts EngineOpts } // NewEngine creates a new LogQL Engine. func NewEngine(opts EngineOpts, q Querier, l Limits, logger log.Logger) *Engine { opts.applyDefault() if logger == nil { logger = log.NewNopLogger() } return &Engine{ logger: logger, evaluatorFactory: NewDefaultEvaluator(q, opts.MaxLookBackPeriod), limits: l, opts: opts, } } // Query creates a new LogQL query. Instant/Range type is derived from the parameters. func (ng *Engine) Query(params Params) Query { return &query{ logger: ng.logger, params: params, evaluator: ng.evaluatorFactory, record: true, logExecQuery: ng.opts.LogExecutingQuery, limits: ng.limits, } } // Query is a LogQL query to be executed. type Query interface { // Exec processes the query. Exec(ctx context.Context) (logqlmodel.Result, error) } type query struct { logger log.Logger params Params limits Limits evaluator EvaluatorFactory record bool logExecQuery bool } func (q *query) resultLength(res promql_parser.Value) int { switch r := res.(type) { case promql.Vector: return len(r) case promql.Matrix: return r.TotalSamples() case logqlmodel.Streams: return int(r.Lines()) case ProbabilisticQuantileMatrix: return len(r) default: // for `scalar` or `string` or any other return type, we just return `0` as result length. return 0 } } // Exec Implements `Query`. It handles instrumentation & defers to Eval. func (q *query) Exec(ctx context.Context) (logqlmodel.Result, error) { sp, ctx := opentracing.StartSpanFromContext(ctx, "query.Exec") defer sp.Finish() sp.LogKV( "type", GetRangeType(q.params), "query", q.params.QueryString(), "start", q.params.Start(), "end", q.params.End(), "step", q.params.Step(), "length", q.params.End().Sub(q.params.Start()), ) if q.logExecQuery { queryHash := util.HashedQuery(q.params.QueryString()) if GetRangeType(q.params) == InstantType { level.Info(logutil.WithContext(ctx, q.logger)).Log("msg", "executing query", "type", "instant", "query", q.params.QueryString(), "query_hash", queryHash) } else { level.Info(logutil.WithContext(ctx, q.logger)).Log("msg", "executing query", "type", "range", "query", q.params.QueryString(), "length", q.params.End().Sub(q.params.Start()), "step", q.params.Step(), "query_hash", queryHash) } } rangeType := GetRangeType(q.params) timer := prometheus.NewTimer(QueryTime.WithLabelValues(string(rangeType))) defer timer.ObserveDuration() // records query statistics start := time.Now() statsCtx, ctx := stats.NewContext(ctx) metadataCtx, ctx := metadata.NewContext(ctx) data, err := q.Eval(ctx) queueTime, _ := ctx.Value(httpreq.QueryQueueTimeHTTPHeader).(time.Duration) statResult := statsCtx.Result(time.Since(start), queueTime, q.resultLength(data)) sp.LogKV(statResult.KVList()...) status, _ := server.ClientHTTPStatusAndError(err) if q.record { RecordRangeAndInstantQueryMetrics(ctx, q.logger, q.params, strconv.Itoa(status), statResult, data) } return logqlmodel.Result{ Data: data, Statistics: statResult, Headers: metadataCtx.Headers(), Warnings: metadataCtx.Warnings(), }, err } func (q *query) Eval(ctx context.Context) (promql_parser.Value, error) { tenants, _ := tenant.TenantIDs(ctx) timeoutCapture := func(id string) time.Duration { return q.limits.QueryTimeout(ctx, id) } queryTimeout := validation.SmallestPositiveNonZeroDurationPerTenant(tenants, timeoutCapture) ctx, cancel := context.WithTimeout(ctx, queryTimeout) defer cancel() if q.checkBlocked(ctx, tenants) { return nil, logqlmodel.ErrBlocked } switch e := q.params.GetExpression().(type) { case syntax.SampleExpr: value, err := q.evalSample(ctx, e) return value, err case syntax.LogSelectorExpr: itr, err := q.evaluator.NewIterator(ctx, e, q.params) if err != nil { return nil, err } encodingFlags := httpreq.ExtractEncodingFlagsFromCtx(ctx) if encodingFlags.Has(httpreq.FlagCategorizeLabels) { itr = iter.NewCategorizeLabelsIterator(itr) } defer util.LogErrorWithContext(ctx, "closing iterator", itr.Close) streams, err := readStreams(itr, q.params.Limit(), q.params.Direction(), q.params.Interval()) return streams, err default: return nil, fmt.Errorf("unexpected type (%T): cannot evaluate", e) } } func (q *query) checkBlocked(ctx context.Context, tenants []string) bool { blocker := newQueryBlocker(ctx, q) for _, tenant := range tenants { if blocker.isBlocked(ctx, tenant) { QueriesBlocked.WithLabelValues(tenant).Inc() return true } } return false } // evalSample evaluate a sampleExpr func (q *query) evalSample(ctx context.Context, expr syntax.SampleExpr) (promql_parser.Value, error) { if lit, ok := expr.(*syntax.LiteralExpr); ok { return q.evalLiteral(ctx, lit) } if vec, ok := expr.(*syntax.VectorExpr); ok { return q.evalVector(ctx, vec) } tenantIDs, err := tenant.TenantIDs(ctx) if err != nil { return nil, err } maxIntervalCapture := func(id string) time.Duration { return q.limits.MaxQueryRange(ctx, id) } maxQueryInterval := validation.SmallestPositiveNonZeroDurationPerTenant(tenantIDs, maxIntervalCapture) if maxQueryInterval != 0 { err = q.checkIntervalLimit(expr, maxQueryInterval) if err != nil { return nil, err } } expr, err = optimizeSampleExpr(expr) if err != nil { return nil, err } stepEvaluator, err := q.evaluator.NewStepEvaluator(ctx, q.evaluator, expr, q.params) if err != nil { return nil, err } defer util.LogErrorWithContext(ctx, "closing SampleExpr", stepEvaluator.Close) next, _, r := stepEvaluator.Next() if stepEvaluator.Error() != nil { return nil, stepEvaluator.Error() } if next && r != nil { switch vec := r.(type) { case SampleVector: maxSeriesCapture := func(id string) int { return q.limits.MaxQuerySeries(ctx, id) } maxSeries := validation.SmallestPositiveIntPerTenant(tenantIDs, maxSeriesCapture) mfl := false if rae, ok := expr.(*syntax.RangeAggregationExpr); ok && (rae.Operation == syntax.OpRangeTypeFirstWithTimestamp || rae.Operation == syntax.OpRangeTypeLastWithTimestamp) { mfl = true } return q.JoinSampleVector(next, vec, stepEvaluator, maxSeries, mfl) case ProbabilisticQuantileVector: return MergeQuantileSketchVector(next, vec, stepEvaluator, q.params) default: return nil, fmt.Errorf("unsupported result type: %T", r) } } return nil, errors.New("unexpected empty result") } func vectorsToSeries(vec promql.Vector, sm map[uint64]promql.Series) { for _, p := range vec { var ( series promql.Series hash = p.Metric.Hash() ok bool ) series, ok = sm[hash] if !ok { series = promql.Series{ Metric: p.Metric, Floats: make([]promql.FPoint, 0, 1), } sm[hash] = series } series.Floats = append(series.Floats, promql.FPoint{ T: p.T, F: p.F, }) sm[hash] = series } } func (q *query) JoinSampleVector(next bool, r StepResult, stepEvaluator StepEvaluator, maxSeries int, mergeFirstLast bool) (promql_parser.Value, error) { vec := promql.Vector{} if next { vec = r.SampleVector() } // fail fast for the first step or instant query if len(vec) > maxSeries { return nil, logqlmodel.NewSeriesLimitError(maxSeries) } seriesIndex := map[uint64]promql.Series{} if GetRangeType(q.params) == InstantType { // an instant query sharded first/last_over_time can return a single vector if mergeFirstLast { vectorsToSeries(vec, seriesIndex) series := make([]promql.Series, 0, len(seriesIndex)) for _, s := range seriesIndex { series = append(series, s) } result := promql.Matrix(series) sort.Sort(result) return result, stepEvaluator.Error() } sortByValue, err := Sortable(q.params) if err != nil { return nil, fmt.Errorf("fail to check Sortable, logql: %s ,err: %s", q.params.QueryString(), err) } if !sortByValue { sort.Slice(vec, func(i, j int) bool { return labels.Compare(vec[i].Metric, vec[j].Metric) < 0 }) } return vec, nil } for next { vec = r.SampleVector() vectorsToSeries(vec, seriesIndex) // as we slowly build the full query for each steps, make sure we don't go over the limit of unique series. if len(seriesIndex) > maxSeries { return nil, logqlmodel.NewSeriesLimitError(maxSeries) } next, _, r = stepEvaluator.Next() if stepEvaluator.Error() != nil { return nil, stepEvaluator.Error() } } series := make([]promql.Series, 0, len(seriesIndex)) for _, s := range seriesIndex { series = append(series, s) } result := promql.Matrix(series) sort.Sort(result) return result, stepEvaluator.Error() } func (q *query) checkIntervalLimit(expr syntax.SampleExpr, limit time.Duration) error { var err error expr.Walk(func(e syntax.Expr) { switch e := e.(type) { case *syntax.RangeAggregationExpr: if e.Left == nil || e.Left.Interval <= limit { return } err = fmt.Errorf("%w: [%s] > [%s]", logqlmodel.ErrIntervalLimit, model.Duration(e.Left.Interval), model.Duration(limit)) } }) return err } func (q *query) evalLiteral(_ context.Context, expr *syntax.LiteralExpr) (promql_parser.Value, error) { value, err := expr.Value() if err != nil { return nil, err } s := promql.Scalar{ T: q.params.Start().UnixNano() / int64(time.Millisecond), V: value, } if GetRangeType(q.params) == InstantType { return s, nil } return PopulateMatrixFromScalar(s, q.params), nil } func (q *query) evalVector(_ context.Context, expr *syntax.VectorExpr) (promql_parser.Value, error) { value, err := expr.Value() if err != nil { return nil, err } s := promql.Scalar{ T: q.params.Start().UnixNano() / int64(time.Millisecond), V: value, } if GetRangeType(q.params) == InstantType { return promql.Vector{promql.Sample{ T: q.params.Start().UnixMilli(), F: value, Metric: labels.Labels{}, }}, nil } return PopulateMatrixFromScalar(s, q.params), nil } func PopulateMatrixFromScalar(data promql.Scalar, params Params) promql.Matrix { var ( start = params.Start() end = params.End() step = params.Step() series = promql.Series{ Floats: make( []promql.FPoint, 0, // allocate enough space for all needed entries int(end.Sub(start)/step)+1, ), } ) for ts := start; !ts.After(end); ts = ts.Add(step) { series.Floats = append(series.Floats, promql.FPoint{ T: ts.UnixNano() / int64(time.Millisecond), F: data.V, }) } return promql.Matrix{series} } // readStreams reads the streams from the iterator and returns them sorted. // If categorizeLabels is true, the stream labels contains just the stream labels and entries inside each stream have their // structuredMetadata and parsed fields populated with structured metadata labels plus the parsed labels respectively. // Otherwise, the stream labels are the whole series labels including the stream labels, structured metadata labels and parsed labels. func readStreams(i iter.EntryIterator, size uint32, dir logproto.Direction, interval time.Duration) (logqlmodel.Streams, error) { streams := map[string]*logproto.Stream{} respSize := uint32(0) // lastEntry should be a really old time so that the first comparison is always true, we use a negative // value here because many unit tests start at time.Unix(0,0) lastEntry := lastEntryMinTime for respSize < size && i.Next() { streamLabels, entry := i.Labels(), i.At() forwardShouldOutput := dir == logproto.FORWARD && (entry.Timestamp.Equal(lastEntry.Add(interval)) || entry.Timestamp.After(lastEntry.Add(interval))) backwardShouldOutput := dir == logproto.BACKWARD && (entry.Timestamp.Equal(lastEntry.Add(-interval)) || entry.Timestamp.Before(lastEntry.Add(-interval))) // If step == 0 output every line. // If lastEntry.Unix < 0 this is the first pass through the loop and we should output the line. // Then check to see if the entry is equal to, or past a forward or reverse step if interval == 0 || lastEntry.Unix() < 0 || forwardShouldOutput || backwardShouldOutput { stream, ok := streams[streamLabels] if !ok { stream = &logproto.Stream{ Labels: streamLabels, } streams[streamLabels] = stream } stream.Entries = append(stream.Entries, entry) lastEntry = i.At().Timestamp respSize++ } } result := make(logqlmodel.Streams, 0, len(streams)) for _, stream := range streams { result = append(result, *stream) } sort.Sort(result) return result, i.Err() } type groupedAggregation struct { labels labels.Labels value float64 mean float64 groupCount int heap vectorByValueHeap reverseHeap vectorByReverseValueHeap }