26 Commits (3e415aca3d904fa6fa3cbedfdc7a2bdfd7fb6d41)

Author	SHA1	Message	Date
Robert Fratto	2e418b13fd	chore(engine): unexport subpackages (#19384) ... This moves packages around to reduce the surface area of the public engine API: * `pkg/engine/planner` moves to `pkg/engine/internal/planner` * `pkg/engine/executor` moves to `pkg/engine/internal/executor` These packages were only used from `pkg/engine` and did not need to be public. We may make them public again in the future if we want to expose subcomponents of the engine. This move means that `pkg/engine/planner/internal/tree` became `pkg/engine/internal/planner/internal/tree`. To reduce the import path, I also moved that package to `pkg/engine/internal/util/tree`. Other than moving files and updating import paths, no code changes are made. Signed-off-by: Robert Fratto <robertfratto@gmail.com>	3 months ago
Stas Spiridonov	1474ede675	feat(engine): More aggregations for the new query engine (#19350)	3 months ago
Trevor Whitney	aec34ed30a	feat: add json parsing stage to v2 engine (#19240)	3 months ago
Trevor Whitney	fc58d21eb3	chore: exclude types package from linting rules. (#19220)	4 months ago
Trevor Whitney	ccb4549ddd	feat: add logfmt parse support to the v2 query engine (#18931)	4 months ago
Sophie Waldman	98b411a649	chore(linter): Fix issues flagged by updated golangci-lint version (#19206)	4 months ago
Robert Fratto	ed1b61d253	chore(engine): improve performance of topk pipeline (#18593)	5 months ago
Christian Haudum	4305a6aa61	chore(engine): Make literals simple types (#17733) ... Representing data types as simple types (string, int64, float64) makes them more efficient to cast without conversion. Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	6 months ago
Robert Fratto	5266865fef	chore(engine): add implementation for performing topk across streams of Arrow records (#18330) ... This commit adds a `engine.topkBatch` type, which can be used by the implementation of execution nodes to perform compute the set of topk rows from a stream of records. This is needed as part of #17976, and more generally for efficiently sorting rows when a limit is also used. Implementing this required quite a few helper utilities in the new `arrowagg` package. The `arrowagg` package provides utilities for aggregating various Arrow types: * `arrowagg.Arrays` to concatenate a stream of `arrow.Array`s. * `arrayagg.Records` to concatenate a stream of `arrow.Record`s, creating a merged schema. * `arrowagg.Mapper` for quickly finding fields in incoming schemas, since arrow-go can return false when comparing two identical schemas/fields. Co-authored-by: Ashwanth <iamashwanth@gmail.com>	6 months ago
Ashwanth	50374f0bb1	chore(engine): column expression evaluation for ambiguous column type look-ups (#18228)	6 months ago
Ashwanth	646ebe81d8	chore(engine): adds AST conversion and result builders for metric queries (#18166)	6 months ago
Ashwanth	635896dab9	chore(engine): adds vector aggregation planning and execution nodes (#18100)	7 months ago
Christian Haudum	3956ea1be7	chore(engine): Map line filter expressions to data object predicates (#18102) ... This PR converts line filter expressions into message predicates for the data object scan, instead of returning an error. Signed-off-by: Christian Haudum <christian.haudum@gmail.com> Co-authored-by: Ashwanth <iamashwanth@gmail.com>	7 months ago
Ashwanth	1effa30851	chore(engine): implement range aggregation operator (#17997)	7 months ago
Ashwanth	e1206fb84d	feat(planning): adds physical and logical nodes for range aggregation (#17974) ... Signed-off-by: Ashwanth <iamashwanth@gmail.com> Co-authored-by: Owen Diehl <ow.diehl@gmail.com>	7 months ago
Christian Haudum	cbb5be6d57	feat(engine): Implements predicate mapping for DataObjScan (#17621) ... This is an initial implementation of `buildLogsPredicate(expr physical.Expression) (dataobj.LogsPredicate, error)`. While there have been discussions about bypassing this approach in favor of directly using `dataset.Reader` and `dataset.Predicate`, this PR provides essential supported functionality to unblock progress in the interim. Specifically, it handles mapping common timestamp and metadata equality predicates. Signed-off-by: Christian Haudum <christian.haudum@gmail.com> Co-authored-by: Owen Diehl <ow.diehl@gmail.com>	8 months ago
Christian Haudum	1629181f9c	chore(engine): Unify name and type of builtin columns (#17608) ... Names and types used when creating and collecting records need to match. * `Entry.Line` maps to `builtin.message` of type `arrow.BinaryTypes.String` * `Entry.Timestamp` maps to `builin.timestamp` of type `arrow.FixedWidthTypes.Timestamp_ns` Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	8 months ago
Christian Haudum	94b1d2d5ce	chore(engine): Improve type system of the new query engine (#17456) ... **What this PR does / why we need it**: The original type system for the new engine was introduced before adding Apache Arrow and with that an additional type system. One aspect of the new type system of this PR is that the logical types of the engine are aligned/interchangeable with the arrow logical types. ```go type Type uint8 const ( NULL = Type(arrow.NULL) BOOL = Type(arrow.BOOL) STRING = Type(arrow.STRING) INT64 = Type(arrow.INT64) FLOAT64 = Type(arrow.FLOAT64) ) ``` The actual data types of Loki (`Boolean`, `String`, `Integer`, `Float`, `Timestamp`, `Duration`, and `Bytes`) are implemented as wrapper around a logical type. Different data types can use the same logical type as representation, such as `Integer`, `Timestamp` and `Duration` both use `INT64`. Since Arrow array types are bound to logical types, and one logical type can have multiple Loki data types, it is required to "annotate" Fields of an arrow.Record using its Metadata, similar to how it is done for distinguishing builtin columns from label/metadata/parsed columns. Additionally, the PR contains a mapping between Loki types and Arrow types. The `Literal` has been updated to use the new types. The old system also used UINT64 as representation of the `Timestamp` type, which is incorrect, since both LogQL and the DataObjects allow timestamps before unix epoch. --- Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	8 months ago
Christian Haudum	6b4430afd0	chore(engine): Collect pipeline records into Loki result (#17447) ... This PR adds the missing piece between existing HTTP handler and the new execution engine, which converts the Apache Arrow records from the vectorized, columnar, pull-based iterator pipeline into the existing (row-based) Loki response format. Since the engine only supports logs queries at the moment, the transformation logic does not take possible metric query results into account. Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	8 months ago
Christian Haudum	208e519564	chore(engine): Add framework for function evaluation (#17374) ... Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	8 months ago
Christian Haudum	525b41155d	chore(engine): Add expression evaluator to evaluate physical expressions against a given record batch (#17257) ... The evaluator takes a physcial expressions and an arrow.Record as input and return a ColumnVector. This PR only implements the evaluation of the LiteralExpr and ColumnExpr. Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	9 months ago
Christian Haudum	1705f98a9f	chore(engine): Wire up new execution engine (#17032) ... This PR connects the already existing components of the new query engine and wires them up in the querier API. The feature flag `-querier.engine.enable-v2-engine` controls whether supported queries should be executed using the new engine. Note that this implementation currently does not execute any queries. Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	9 months ago
Christian Haudum	ba61aa88de	chore(engine): Integrate metastore into physical query planning (#17016) ... This PR integrates the data object lookup using the metastore into the query planning. To achieve that, I extended the `Metastore` interface with an additional function that not only returns the data object paths, but also the stream IDs of streams that match the given label matchers. ```go type Metastore interface { ... // StreamsIDs returns object store paths and stream IDs for all matching objects for the given matchers between [start,end] StreamIDs(ctx context.Context, start, end time.Time, matchers ...*labels.Matcher) ([]string, [][]int64, error) ... } ``` Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	9 months ago
Christian Haudum	40223d7320	chore(engine): Unify `Literal` and `ColumnRef` across logical and physical plan (#16927) ... Literals and column refs are used by both the logical and physical plan. However, the interfaces they need to implement are partly private (`isValue()` and `isExpression()`). Therefore they are wrapped in their own struct that implement these interfaces. Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	9 months ago
Christian Haudum	138093b900	chore(planner): Convert AST into logical plan (#16916) ... Minimal implementation of the logical planner that converts a parsed LogQL statement in AST form into a logical plan in SSA form. Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	9 months ago
Christian Haudum	efe15486fe	chore(engine): Add first stage of physical query planning (#16891) ... Planning consists of two stages: 1. Conversion stage: Instructions from the logical plan are converted into Nodes in the physical plan. Most instructions can be translated into a single Node. However, `MakeTable` translates into multiple `DataObjScan` nodes. 2. Pushdown stage: a) Push down the limit of the `Limit` node to the `DataObjScan` nodes. b) Push down filter predicates from the `Filter` nodes to the `DataObjScan` nodes. **This PR implements only the first stage.** Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	9 months ago