package engine import ( "context" "encoding/base64" "strings" "time" "github.com/apache/arrow-go/v18/arrow" "github.com/apache/arrow-go/v18/arrow/array" "github.com/go-kit/log" "github.com/go-kit/log/level" "github.com/pkg/errors" "github.com/prometheus/client_golang/prometheus" "github.com/prometheus/prometheus/model/labels" "github.com/thanos-io/objstore" "github.com/grafana/loki/v3/pkg/dataobj/metastore" "github.com/grafana/loki/v3/pkg/engine/executor" "github.com/grafana/loki/v3/pkg/engine/internal/types" "github.com/grafana/loki/v3/pkg/engine/planner/logical" "github.com/grafana/loki/v3/pkg/engine/planner/physical" "github.com/grafana/loki/v3/pkg/logproto" "github.com/grafana/loki/v3/pkg/logql" "github.com/grafana/loki/v3/pkg/logqlmodel" "github.com/grafana/loki/v3/pkg/logqlmodel/stats" utillog "github.com/grafana/loki/v3/pkg/util/log" ) var ( ErrNotSupported = errors.New("feature not supported in new query engine") ) // New creates a new instance of the query engine that implements the [logql.Engine] interface. func New(opts logql.EngineOpts, bucket objstore.Bucket, limits logql.Limits, reg prometheus.Registerer, logger log.Logger) *QueryEngine { var ms metastore.Metastore if bucket != nil { ms = metastore.NewObjectMetastore(bucket, logger) } return &QueryEngine{ logger: logger, metrics: newMetrics(reg), limits: limits, metastore: ms, bucket: bucket, opts: opts, } } // QueryEngine combines logical planning, physical planning, and execution to evaluate LogQL queries. type QueryEngine struct { logger log.Logger metrics *metrics limits logql.Limits metastore metastore.Metastore bucket objstore.Bucket opts logql.EngineOpts } // Query implements [logql.Engine]. func (e *QueryEngine) Query(params logql.Params) logql.Query { return &queryAdapter{ engine: e, params: params, } } // Execute executes a LogQL query and returns its results or alternatively an error. // The execution is done in three steps: // 1. Create a logical plan from the provided query parameters. // 2. Create a physical plan from the logical plan using information from the catalog. // 3. Evaluate the physical plan with the executor. func (e *QueryEngine) Execute(ctx context.Context, params logql.Params) (logqlmodel.Result, error) { start := time.Now() builder := newResultBuilder() logger := utillog.WithContext(ctx, e.logger) logger = log.With(logger, "query", params.QueryString(), "shard", strings.Join(params.Shards(), ","), "engine", "v2") t := time.Now() // start stopwatch for logical planning logicalPlan, err := logical.BuildPlan(params) if err != nil { level.Warn(logger).Log("msg", "failed to create logical plan", "err", err) e.metrics.subqueries.WithLabelValues(statusNotImplemented).Inc() return builder.empty(), ErrNotSupported } e.metrics.logicalPlanning.Observe(time.Since(t).Seconds()) durLogicalPlanning := time.Since(t) level.Info(logger).Log( "msg", "finished logical planning", "plan", base64.StdEncoding.EncodeToString([]byte(logicalPlan.String())), "duration", durLogicalPlanning.Seconds(), ) t = time.Now() // start stopwatch for physical planning executionContext := physical.NewContext(ctx, e.metastore, params.Start(), params.End()) planner := physical.NewPlanner(executionContext) plan, err := planner.Build(logicalPlan) if err != nil { level.Warn(logger).Log("msg", "failed to create physical plan", "err", err) e.metrics.subqueries.WithLabelValues(statusFailure).Inc() return builder.empty(), ErrNotSupported } plan, err = planner.Optimize(plan) if err != nil { level.Warn(logger).Log("msg", "failed to optimize physical plan", "err", err) e.metrics.subqueries.WithLabelValues(statusFailure).Inc() return builder.empty(), ErrNotSupported } e.metrics.physicalPlanning.Observe(time.Since(t).Seconds()) durPhysicalPlanning := time.Since(t) level.Info(logger).Log( "msg", "finished physical planning", "plan", base64.StdEncoding.EncodeToString([]byte(physical.PrintAsTree(plan))), "duration", durLogicalPlanning.Seconds(), ) level.Info(logger).Log( "msg", "start executing query with new engine", ) t = time.Now() // start stopwatch for execution cfg := executor.Config{ BatchSize: int64(e.opts.BatchSize), Bucket: e.bucket, } pipeline := executor.Run(ctx, cfg, plan) defer pipeline.Close() if err := collectResult(ctx, pipeline, builder); err != nil { e.metrics.subqueries.WithLabelValues(statusFailure).Inc() return builder.empty(), err } statsCtx := stats.FromContext(ctx) builder.setStats(statsCtx.Result(time.Since(start), 0, builder.len())) e.metrics.subqueries.WithLabelValues(statusSuccess).Inc() e.metrics.execution.Observe(time.Since(t).Seconds()) durExecution := time.Since(t) level.Debug(logger).Log( "msg", "finished executing with new engine", "duration_logical_planning", durLogicalPlanning, "duration_physical_planning", durPhysicalPlanning, "duration_execution", durExecution, ) return builder.build(), nil } func collectResult(_ context.Context, pipeline executor.Pipeline, result *resultBuilder) error { for { if err := pipeline.Read(); err != nil { if errors.Is(err, executor.EOF) { break } return err } if err := collectRecord(pipeline, result); err != nil { return err } } return nil } func collectRecord(pipeline executor.Pipeline, result *resultBuilder) error { rec, err := pipeline.Value() if err != nil { return err } defer rec.Release() for rowIdx := range int(rec.NumRows()) { collectRow(rec, rowIdx, result) } return nil } func collectRow(rec arrow.Record, i int, result *resultBuilder) { var entry logproto.Entry lbs := labels.NewBuilder(labels.EmptyLabels()) metadata := labels.NewBuilder(labels.EmptyLabels()) for colIdx := range int(rec.NumCols()) { col := rec.Column(colIdx) colName := rec.ColumnName(colIdx) // TODO(chaudum): We need to add metadata to columns to identify builtins, labels, metadata, and parsed. field := rec.Schema().Field(colIdx) colType, ok := field.Metadata.GetValue(types.MetadataKeyColumnType) // Ignore column values that are NULL or invalid or don't have a column typ if col.IsNull(i) || !col.IsValid(i) || !ok { continue } // Extract line if colName == types.ColumnNameBuiltinMessage && colType == types.ColumnTypeBuiltin.String() { entry.Line = col.(*array.String).Value(i) continue } // Extract timestamp if colName == types.ColumnNameBuiltinTimestamp && colType == types.ColumnTypeBuiltin.String() { entry.Timestamp = time.Unix(0, int64(col.(*array.Timestamp).Value(i))) continue } // Extract label if colType == types.ColumnTypeLabel.String() { switch arr := col.(type) { case *array.String: lbs.Set(colName, arr.Value(i)) } continue } // Extract metadata if colType == types.ColumnTypeMetadata.String() { switch arr := col.(type) { case *array.String: metadata.Set(colName, arr.Value(i)) } continue } } entry.StructuredMetadata = logproto.FromLabelsToLabelAdapters(metadata.Labels()) stream := lbs.Labels() // Ignore rows that don't have stream labels, log line, or timestamp if stream.Len() == 0 || entry.Line == "" || entry.Timestamp.Equal(time.Time{}) { return } // Finally, add newly created entry to builder result.add(stream, entry) } var _ logql.Engine = (*QueryEngine)(nil) // queryAdapter dispatches query execution to the wrapped engine. type queryAdapter struct { params logql.Params engine *QueryEngine } // Exec implements [logql.Query]. func (q *queryAdapter) Exec(ctx context.Context) (logqlmodel.Result, error) { return q.engine.Execute(ctx, q.params) } var _ logql.Query = (*queryAdapter)(nil)