I have the following 2 examples. Now, regarding on the offset if it is small(10) or big(>50000) what is the impact on the performance of the query?? I noticed that if I return more data's(columns) or if I make more joins then the query runs even slower if the OFFSET is bigger. How can I somehow improve the performance on this?
Best regards, Andy.
explain
analyze SELECT o.id FROM report r INNER JOIN orders o ON o.id=r.id_order AND o.id_status=6 ORDER BY 1 LIMIT 10 OFFSET 10
Limit (cost=44.37..88.75 rows=10 width=4) (actual time=0.160..0.275 rows=10 loops=1) -> Merge Join (cost=0.00..182150.17 rows=41049 width=4) (actual time=0.041..0.260 rows=20 loops=1) Merge Cond: ("outer".id_order = "inner".id) -> Index Scan using report_id_order_idx on report r (cost=0.00..157550.90 rows=42862 width=4) (actual time=0.018..0.075 rows=20 loops=1) -> Index Scan using orders_pkey on orders o (cost=0.00..24127.04 rows=42501 width=4) (actual time=0.013..0.078 rows=20 loops=1) Filter: (id_status = 6) Total runtime: 0.373 ms
explain
analyze SELECT o.id FROM report r INNER JOIN orders o ON o.id=r.id_order AND o.id_status=6 ORDER BY 1 LIMIT 10 OFFSET 1000000Limit (cost=31216.85..31216.85 rows=1 width=4) (actual time=1168.152..1168.152 rows=0 loops=1) -> Sort (cost=31114.23..31216.85 rows=41049 width=4) (actual time=1121.769..1152.246 rows=42693 loops=1) Sort Key: o.id -> Hash Join (cost=2329.99..27684.03 rows=41049 width=4) (actual time=441.879..925.498 rows=42693 loops=1) Hash Cond: ("outer".id_order = "inner".id) -> Seq Scan on report r (cost=0.00..23860.62 rows=42862 width=4) (actual time=38.634..366.035 rows=42864 loops=1) -> Hash (cost=2077.74..2077.74 rows=42501 width=4) (actual time=140.200..140.200 rows=0 loops=1) -> Seq Scan on orders o (cost=0.00..2077.74 rows=42501 width=4) (actual time=0.059..96.890 rows=42693 loops=1) Filter: (id_status = 6) Total runtime: 1170.586 ms
