9 Commits (9d0d1084e39fdfd4a58d701b13ff755f4e5f36eb)

Author	SHA1	Message	Date
Ashwanth	b3803113ad	chore(engine): registers functions for logical op (#19704)	2 months ago
Christian Haudum	73bc30d9a8	perf(engine): Improve regexp expression evaluation (#19644) ... This PR changes the evaluation of regex-match binary expression evaluations so that the regexp on right hand side of the expression is only compiled once for each batch evaluation, rather than for each row. This saves a ton of allocations and improves general performance of queries with a regexp line or label filter.	2 months ago
Stas Spiridonov	7eda6749a4	feat(engine): basic math expressions (#19407)	3 months ago
Christian Haudum	9e76f1d251	chore(engine): Refactor `ColumnVector` (#19549) ... This PR removes the need of the ColumnVector as a result of expression evaluation and instead returns an arrow.Array. Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	3 months ago
Stas Spiridonov	160dc2c493	chore: removed arrow-go allocators/retain/release (#19569)	3 months ago
Christian Haudum	849a9214fa	chore: Release column vectors and their arrays correctly (#19496) ... Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	3 months ago
Stas Spiridonov	16dab82593	chore: consistent expressionEvaluator.eval result memory ownership (#19438)	3 months ago
Christian Haudum	119275aab7	chore(engine): Column naming conventions (#19396) ... In the new engine, we need fully qualified column names, since columns from different sources can have the same name. Right now, the distinction between columns with the same name is implemented using the `Metadata` field on the `arrow.Field`. However, it is quite cumbersome to parse the column type and data type from this generic map. This PR introduces package with naming conventions for columns, defined by name, data type, and column type. So, this information can be encoded into the `Name` field of the `arrow.Field`. The convention is defined as ``` [DATA_TYPE].[COLUMN_TYPE].[COLUMN_NAME] ``` #### Examples: * `utf8.label.service_name` * `timestamp_ns.builtin.timestamp` The column type can easily be converted into a `Scope`, which is defined by an origin and type. The mapping is as follows: ``` ColumnTypeBuiltin -> Scope{Record, Attribute} ColumnTypeMetadata -> Scope{Record, Builtin} ColumnTypeLabel -> Scope{Resource, Attribute} ColumnTypeParsed -> Scope{Generated, Attribute} ColumnTypeGenerated -> Scope{Generated, Builtin} ColumnTypeAmbiguous -> Scope{Unscoped, Attribute} ``` --- Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	3 months ago
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
Christian Haudum	6f7dc12eb4	chore(engine): Add support for regex and substr filters (#18501) ... Filters predicates on ambiguous columns (basically any label filter expression) cannot be pushed down to the DataObjScan and need to be evaluated in the Filter node. This PR adds the evaluation functions for MATCH_RE(string,string) and MATCH_SUBSTR(string, string) and their negating equivalent. Under the hood, the PR also replaces the type specific comparison function implementations with a generic one, which now also handle arrow.Timestamp arrays correctly. Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	6 months ago