案例：改建分区表

现象描述

如下简单SQL语句查询， 性能瓶颈点在normal_date的Scan上。

1. QUERY PLAN
2. -----------------------------------------------------------------------------------------------------------------------------------------------
3. Seq Scan on normal_date  (cost=0.00..259.00 rows=30 width=12) (actual time=0.100..3.466 rows=30 loops=1)
4. Filter: (("time" >= '2022-09-01 00:00:00'::timestamp without time zone) AND ("time" <= '2022-10-01 00:00:00'::timestamp without time zone))
5. Rows Removed by Filter: 9970
6. Total runtime: 3.587 ms
7. (4 rows)

优化分析

从业务层确认表数据(在time字段上)有明显的日期特征，符合分区表的特征。重新规划normal_date表的表定义：字段time为分区键、月为间隔单位定义分区表normal_date_part。修改后结果如下，性能提升近10倍。

1. QUERY PLAN
2. -----------------------------------------------------------------------------------------------------------------------------------------------------
3. Partition Iterator  (cost=0.00..480.00 rows=30 width=12) (actual time=0.038..0.085 rows=30 loops=1)
4. Iterations: 2
5. ->  Partitioned Seq Scan on normal_date_part  (cost=0.00..480.00 rows=30 width=12) (actual time=0.049..0.063 rows=30 loops=2)
6. Filter: (("time" >= '2022-09-01 00:00:00'::timestamp without time zone) AND ("time" <= '2022-10-01 00:00:00'::timestamp without time zone))
7. Rows Removed by Filter: 31
8. Selected Partitions:  3..4
9. Total runtime: 0.360 ms
10. (7 rows)