Push down group by for partition columns

[huaxingao]

Push down min/max/count with group by if group by is on partition columns

For example:

CREATE TABLE test (id LONG, ts TIMESTAMP, data INT) USING iceberg PARTITIONED BY (id, ts);
SELECT MIN(data), MAX(data), COUNT(data), COUNT(*) FROM test GROUP BY id, ts;

I have the following changes:

1. Added Expression GroupBy, UnboundGroupBy, BoundGroupBy

2. In Aggregator, I will take consideration of GroupBy. Use MaxAggregator as an example:

   • Add List<BoundGroupBy> in the constructor
   • Add private Map<StructLike, T> maxP which contains max value for each of the partition.
   • The key of the above Map is AggregateEvaluator.ArrayStructLike, which contains the partition values.
   • Add update(R value, StructLike partitionKey) to update value for specific partitions
   • Add Map<StructLike, R> currentPartition() to get current value for each partitions

3. Build the Scan schema to be: group by columns + aggregates (this is what Spark is expecting) Use SELECT MIN(data), MAX(data), COUNT(data), COUNT(*) FROM test GROUP BY id, ts as an example: the schema is LONG, TIMESTAMP, INT, INT, LONG, LONG, which corresponds to id, ts, MIN(data), MAX(data), COUNT(data), COUNT(*)

[huaxingao]

cc @rdblue @aokolnychyi

[rdblue]

Oops, I didn't mean to close this! I want to work on getting it in next

[github-actions[bot]]

This pull request has been marked as stale due to 30 days of inactivity. It will be closed in 1 week if no further activity occurs. If you think that’s incorrect or this pull request requires a review, please simply write any comment. If closed, you can revive the PR at any time and @mention a reviewer or discuss it on the [email protected] list. Thank you for your contributions.

[github-actions[bot]]

This pull request has been closed due to lack of activity. This is not a judgement on the merit of the PR in any way. It is just a way of keeping the PR queue manageable. If you think that is incorrect, or the pull request requires review, you can revive the PR at any time.