Use hash repartitioning for aggregates on dictionaries

[isidentical]

Which issue does this PR close?

Closes #331.

Rationale for this change

Hash repartitioning for aggregates on dictionaries was not available when it was initially implemented since dictionaries couldn't be hashed. The real issue in #331 (implementing vectorized hashing for dictionaries) is already resolved (by @alamb on #812), so as far as I can say we can safely remove this guard in the physical plan builder to leverage hash repartitioning on aggregates with dicts.

What changes are included in this PR?

Changes the physical plan builder to use hash repartitioning on dictionary-based aggregates.

Are there any user-facing changes?

This is an optimization, so there shouldn't be any behavioural change but the physical plans will change on some scenerios (like the example below).

Previous physical plan for the test hash_agg_group_by_partitioned_on_dicts:

AggregateExec: mode=Final, gby=[d1@0 as d1], aggr=[SUM(?table?.d2)]
  CoalescePartitionsExec
    AggregateExec: mode=Partial, gby=[d1@0 as d1], aggr=[SUM(?table?.d2)]
      RepartitionExec: partitioning=RoundRobinBatch(4)
        MemoryExec: partitions=1, partition_sizes=[1]

Current physical plan for it:

AggregateExec: mode=FinalPartitioned, gby=[d1@0 as d1], aggr=[SUM(?table?.d2)]
  CoalesceBatchesExec: target_batch_size=4096
    RepartitionExec: partitioning=Hash([Column { name: "d1", index: 0 }], 4)
      AggregateExec: mode=Partial, gby=[d1@0 as d1], aggr=[SUM(?table?.d2)]
        RepartitionExec: partitioning=RoundRobinBatch(4)
          MemoryExec: partitions=1, partition_sizes=[1]

[codecov-commenter]

Codecov Report

Merging #3445 (8d05c9f) into master (8df5496) will increase coverage by 0.00%.
The diff coverage is 100.00%.

@@           Coverage Diff           @@
##           master    #3445   +/-   ##
=======================================
  Coverage   85.69%   85.69%           
=======================================
  Files         298      298           
  Lines       54644    54654   +10     
=======================================
+ Hits        46826    46836   +10     
  Misses       7818     7818           

Impacted Files	Coverage Δ
datafusion/core/src/physical_plan/planner.rs	77.37% <100.00%> (+0.21%)	⬆️
datafusion/expr/src/logical_plan/plan.rs	77.35% <0.00%> (ø)

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[Dandandan]

Looks good 💯

[alamb]

Thank you @isidentical

[ursabot]

Benchmark runs are scheduled for baseline = 8df5496 and contender = 81addf7. 81addf7 is a master commit associated with this PR. Results will be available as each benchmark for each run completes.
Conbench compare runs links:
[Skipped ⚠️ Benchmarking of arrow-datafusion-commits is not supported on ec2-t3-xlarge-us-east-2] ec2-t3-xlarge-us-east-2
[Skipped ⚠️ Benchmarking of arrow-datafusion-commits is not supported on test-mac-arm] test-mac-arm
[Skipped ⚠️ Benchmarking of arrow-datafusion-commits is not supported on ursa-i9-9960x] ursa-i9-9960x
[Skipped ⚠️ Benchmarking of arrow-datafusion-commits is not supported on ursa-thinkcentre-m75q] ursa-thinkcentre-m75q
Buildkite builds:
Supported benchmarks:
ec2-t3-xlarge-us-east-2: Supported benchmark langs: Python, R. Runs only benchmarks with cloud = True
test-mac-arm: Supported benchmark langs: C++, Python, R
ursa-i9-9960x: Supported benchmark langs: Python, R, JavaScript
ursa-thinkcentre-m75q: Supported benchmark langs: C++, Java