5 Commits (34f5ae3cd875ab599e93e657ccfbfb5f7cdcb22e)

Author	SHA1	Message	Date
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>	2 months ago
Christian Haudum	c06eb636e5	chore(engine): Add "compatibility node" to physical plan to adhere with naming of "colliding labels" in v1 engine (#19470) ... ### Summary The v1 engine has a mechanism to rename labels in case they have the same name but different origin, such as labels, structured metadata, or parsed fields. 1. In case a log line has a structured metadata key with the same name as the label name of the stream, than the metadata key is suffixed with `_extracted`, such as `service_extracted`, if `service` exists in both `labels` and `metadata`. 2. In case a parser creates a parsed field with the same as the label name of the stream, then the parsed key is suffixed with `_extracted` in the same way as case 1. However, if the field name also collides with a structured metadata key, then the extracted structured metadata is replaced with the extracted parsed field. This PR only implements the first case. As a follow up PR, the second case needs to be implemented as well. Additionally, the newly introduced "compatibility node" should also be made optional with a feature flag and/or per-request. Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	3 months ago
Christian Haudum	2214a700b3	chore(engine): Implement new semantic column naming (#19415) ... This PR implements the column naming convention introduced in https://github.com/grafana/loki/pull/19396 Signed-off-by: Christian Haudum <christian.haudum@gmail.com>	3 months ago
Ashwanth	c24675f854	chore: adds separate v2 engine config section (#19423)	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