Supports skipping partial aggregates

[richox]

Is your feature request related to a problem? Please describe.
as described in SPARK-31973, skipping partial aggregates where data cardinality is high (like group by user_id) sufficiently improves performance.

Describe the solution you'd like
implements partial agg skipping strategy in agg_tables.rs:

1. mark an AggExec as skippable. (in spark side, where requiredDistribution is empty)
2. process the first N records.
3. check the number of input records and the number of aggregated records, if reached threshold, directly outputs all in-memory, spilled and rest records.

Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.

Additional context
Add any other context or screenshots about the feature request here.

[richox]

supported in 50fd3d0