Add metrics for FilterExec

[alamb]

Which issue does this PR close?

Next part #866

Rationale for this change

We want basic understanding of where a plan's time is spent and in what operators. See #866 for more details

What changes are included in this PR?

1. Instrument FilterExec using the API from Add BaselineMetrics, Timestamp metrics, add for CoalescePartitionsExec, rename output_time -> elapsed_compute #909
2. Tests for same

Are there any user-facing changes?

More fields in EXPLAIN ANALYZE are now filled out

Example of how explain analayze is looking:

EXPLAIN ANALYZE selectcount(*) from (SELECTcount(*), c1 FROM aggregate_test_100 WHERE c13 !='C2GT5KVyOPZpgKVl110TyZO0NcJ434'GROUP BY c1 ORDER BY c1)
+-------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan |
+-------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Plan with Metrics | ProjectionExec: expr=[COUNT(UInt8(1))@0asCOUNT(UInt8(1))], metrics=[] |
| | HashAggregateExec: mode=Final, gby=[], aggr=[COUNT(UInt8(1))], metrics=[output_rows=1, elapsed_compute=69.362µs] |
| | CoalescePartitionsExec, metrics=[output_rows=3, elapsed_compute=NOT RECORDED] |
| | HashAggregateExec: mode=Partial, gby=[], aggr=[COUNT(UInt8(1))], metrics=[output_rows=3, elapsed_compute=119.041µs] |
| | RepartitionExec: partitioning=RoundRobinBatch(3), metrics=[send_time{inputPartition=0}=4.775µs, fetch_time{inputPartition=0}=12.77346ms, repart_time{inputPartition=0}=NOT RECORDED] |
| | SortExec: [c1@0ASC], metrics=[output_rows=5, elapsed_compute=232.203µs] |
| | CoalescePartitionsExec, metrics=[output_rows=5, elapsed_compute=NOT RECORDED] |
| | HashAggregateExec: mode=FinalPartitioned, gby=[c1@0as c1], aggr=[COUNT(UInt8(1))], metrics=[output_rows=5, elapsed_compute=373.876µs] |
| | CoalesceBatchesExec: target_batch_size=4096, metrics=[] |
| | RepartitionExec: partitioning=Hash([Column { name: "c1", index: 0 }], 3), metrics=[fetch_time{inputPartition=0}=34.072102ms, repart_time{inputPartition=0}=252.872µs, send_time{inputPartition=0}=NOT RECORDED] |
| | HashAggregateExec: mode=Partial, gby=[c1@0as c1], aggr=[COUNT(UInt8(1))], metrics=[output_rows=5, elapsed_compute=581.405µs] |
| | CoalesceBatchesExec: target_batch_size=4096, metrics=[] |
| | FilterExec: c13@1!= C2GT5KVyOPZpgKVl110TyZO0NcJ434, metrics=[output_rows=99, elapsed_compute=309.095µs] |
| | RepartitionExec: partitioning=RoundRobinBatch(3), metrics=[fetch_time{inputPartition=0}=8.239528ms, send_time{inputPartition=0}=9.864µs, repart_time{inputPartition=0}=NOT RECORDED] |
| | CsvExec: source=Path(ARROW_TEST_DATA/csv/aggregate_test_100.csv: [ARROW_TEST_DATA/csv/aggregate_test_100.csv]), has_header=true, metrics=[] |
+-------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

[alamb]

clippy failure is due to #986 I think