| # | exclusive | inclusive | rows x | rows | loops | node |
|---|---|---|---|---|---|---|
| 1. | 0.000 | 0.000 | ↓ 0.0 |
→
Merge Join (cost=2751752513.84..2753361945.59 rows=1745 width=8) (actual time=.. rows= loops=)
|
||
| 2. | 0.000 | 0.000 | ↓ 0.0 |
→
Sort (cost=20822826.25..21024003.04 rows=80470715 width=16) (actual time=.. rows= loops=)
|
||
| 3. | 0.000 | 0.000 | ↓ 0.0 |
→
Index Scan using gps_data_timestamp_indx on gps_data g (cost=0.00..3380062.55 rows=80470715 width=16) (actual time=.. rows= loops=) |
||
| 4. | 0.000 | 0.000 | ↓ 0.0 |
→
Materialize (cost=2730929687.59..2731935571.53 rows=80470715 width=16) (actual time=.. rows= loops=) |
||
| 5. | 0.000 | 0.000 | ↓ 0.0 |
→
Sort (cost=2730929687.59..2731130864.38 rows=80470715 width=16) (actual time=.. rows= loops=)
|
||
| 6. | 0.000 | 0.000 | ↓ 0.0 |
→
Subquery Scan gg (cost=2624780882.42..2713486923.89 rows=80470715 width=16) (actual time=.. rows= loops=) |
||
| 7. | 0.000 | 0.000 | ↓ 0.0 |
→
GroupAggregate (cost=2624780882.42..2712682216.74 rows=80470715 width=16) (actual time=.. rows= loops=) |
||
| 8. | 0.000 | 0.000 | ↓ 0.0 |
→
Sort (cost=2624780882.42..2642159972.49 rows=6951636031 width=16) (actual time=.. rows= loops=)
|
||
| 9. | 0.000 | 0.000 | ↓ 0.0 |
→
Merge Join (cost=239054097.70..656755789.92 rows=6951636031 width=16) (actual time=.. rows= loops=)
|
||
| 10. | 0.000 | 0.000 | ↓ 0.0 |
→
Sort (cost=119527048.85..119728225.64 rows=80470715 width=16) (actual time=.. rows= loops=)
|
||
| 11. | 0.000 | 0.000 | ↓ 0.0 |
→
Seq Scan on gps_data g1 (cost=100000000.00..102084285.15 rows=80470715 width=16) (actual time=.. rows= loops=) |
||
| 12. | 0.000 | 0.000 | ↓ 0.0 |
→
Materialize (cost=119527048.85..120532932.79 rows=80470715 width=12) (actual time=.. rows= loops=) |
||
| 13. | 0.000 | 0.000 | ↓ 0.0 |
→
Sort (cost=119527048.85..119728225.64 rows=80470715 width=12) (actual time=.. rows= loops=)
|
||
| 14. | 0.000 | 0.000 | ↓ 0.0 |
→
Seq Scan on gps_data g2 (cost=100000000.00..102084285.15 rows=80470715 width=12) (actual time=.. rows= loops=) |