Speed up time-series aggregation

[dnhatn]

Time-series aggregations, such as {agg}_over_time and rate, against time-series indices are currently slow due to several reasons:

1. They require two phases:
   • First, grouping by each time-series (by tsid and timebucket).
   • Then, grouping by user-specified groups.
2. For rate aggregations, data must be provided in timestamp order per time-series.

This issue proposes some ideas and tracks optimizations to improve the performance of time-series aggregations in ES|QL.

Source command

• Translate time-series queries without rate to FROM: Avoid sorted source for time_series aggs without rates #127033
• Avoid comparing tsid when iterating over documents in TS source: Optimize time-series source operator #127095
• Extract fields directly from the time-series source: Push down field extraction to time-series source #127445
• Leverage ordinals when loading dimension fields.
• Optimize loading of time-series data using FROM.

Execution

• Support segment data partitioning for TS

Values aggregation

• Emit ordinal output blocks: Emit ordinal output block for values aggregate #127201
• Handle ordinal input blocks.
• Optimize for single-value aggregations (dimension fields?).

Block hash

• Enable time-series block hash: Enable time-series block hash #127488
• Leverage ordinal blocks in time-series block hash: Enable time-series block hash #127488
• Emit ordinal blocks in PackedValuesBlockHash.

Planning

• Use a single aggregation for the second phase.

[elasticsearchmachine]

Pinging @elastic/es-analytical-engine (Team:Analytics)

[elasticsearchmachine]

Pinging @elastic/es-storage-engine (Team:StorageEngine)