## What changes were proposed in this pull request?
This PR is the second step for the following feature:
For hash aggregation in Spark SQL, we use a fast aggregation hashmap to act as a "cache" in order to boost aggregation performance. Previously, the hashmap is backed by a `ColumnarBatch`. This has performance issues when we have wide schema for the aggregation table (large number of key fields or value fields).
In this JIRA, we support another implementation of fast hashmap, which is backed by a `RowBatch`. We then automatically pick between the two implementations based on certain knobs.
In this second-step PR, we enable `RowBasedHashMapGenerator` in `HashAggregateExec`.
## How was this patch tested?
Added tests: `RowBasedAggregateHashMapSuite` and ` VectorizedAggregateHashMapSuite`
Additional micro-benchmarks tests and TPCDS results will be added in a separate PR in the series.
Author: Qifan Pu <qifan.pu@gmail.com>
Author: ooq <qifan.pu@gmail.com>
Closes#14176 from ooq/rowbasedfastaggmap-pr2.
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