Question

我相信这两个查询获得的结果是一样的吗？

第一个查询：

SELECT 
  sensor_id,
  measurement_time,
  measurement_value
FROM 
  public.measurement_pm2_5
  WHERE (sensor_id = 12 AND measurement_time BETWEEN to_timestamp(3000) AND to_timestamp(12000))
  OR (sensor_id = 27 AND measurement_time BETWEEN to_timestamp(3000) AND to_timestamp(12000))
  OR (sensor_id = 1 AND measurement_time BETWEEN to_timestamp(500) AND to_timestamp(1000))
  OR (sensor_id = 1 AND measurement_time BETWEEN to_timestamp(6000) AND to_timestamp(9000));

第二个问题：

SELECT 
  sensor_id,
  measurement_time,
  measurement_value
FROM 
  public.measurement_pm2_5
  WHERE (sensor_id in (12,27) AND measurement_time BETWEEN to_timestamp(3000) AND to_timestamp(12000))
  OR (sensor_id = 1 AND ((measurement_time BETWEEN to_timestamp(500) AND to_timestamp(1000)) OR (measurement_time BETWEEN to_timestamp(6000) AND to_timestamp(9000))));

执行时间怎么样？差异有多大（如果有的话）？

第一个查询：

Start-up Cost: 0
Total Cost: 580.56
Number of Rows: 1
Row Width: 18
Start-up Time: 2.676
Total Time: 2.676
Real Number of Rows: 0
Loops: 1

Hash Join  (cost=0.10..280.06 rows=115 width=18) (actual time=8.596..8.596 rows=0 loops=1)
  Hash Cond: (p.sensor_id = "*VALUES*".column1)
  Join Filter: ((p.measurement_time >= to_timestamp(("*VALUES*".column2)::double precision)) AND (p.measurement_time <= to_timestamp(("*VALUES*".column3)::double precision)))
  Rows Removed by Join Filter: 590
  ->  Seq Scan on measurement_pm2_5 p  (cost=0.00..207.39 rows=12439 width=18) (actual time=0.010..2.558 rows=12443 loops=1)
  ->  Hash  (cost=0.05..0.05 rows=4 width=12) (actual time=0.017..0.017 rows=4 loops=1)
        Buckets: 1024  Batches: 1  Memory Usage: 9kB
        ->  Values Scan on "*VALUES*"  (cost=0.00..0.05 rows=4 width=12) (actual time=0.002..0.003 rows=4 loops=1)
Planning time: 0.148 ms
Execution time: 8.627 ms

第二个问题：

Start-up Cost: 0
Total Cost: 456.17
Number of Rows: 1
Row Width: 18
Start-up Time: 2.237
Total Time: 2.237
Real Number of Rows: 0
Loops: 1

Hash Join  (cost=0.10..280.06 rows=115 width=18) (actual time=8.596..8.596 rows=0 loops=1)
  Hash Cond: (p.sensor_id = "*VALUES*".column1)
  Join Filter: ((p.measurement_time >= to_timestamp(("*VALUES*".column2)::double precision)) AND (p.measurement_time <= to_timestamp(("*VALUES*".column3)::double precision)))
  Rows Removed by Join Filter: 590
  ->  Seq Scan on measurement_pm2_5 p  (cost=0.00..207.39 rows=12439 width=18) (actual time=0.010..2.558 rows=12443 loops=1)
  ->  Hash  (cost=0.05..0.05 rows=4 width=12) (actual time=0.017..0.017 rows=4 loops=1)
        Buckets: 1024  Batches: 1  Memory Usage: 9kB
        ->  Values Scan on "*VALUES*"  (cost=0.00..0.05 rows=4 width=12) (actual time=0.002..0.003 rows=4 loops=1)
Planning time: 0.148 ms
Execution time: 8.627 ms

@ Mike的查询：

Hash Join  (cost=0.10..280.06 rows=115 width=18) (actual time=8.596..8.596 rows=0 loops=1)
  Hash Cond: (p.sensor_id = "*VALUES*".column1)
  Join Filter: ((p.measurement_time >= to_timestamp(("*VALUES*".column2)::double precision)) AND (p.measurement_time <= to_timestamp(("*VALUES*".column3)::double precision)))
  Rows Removed by Join Filter: 590
  ->  Seq Scan on measurement_pm2_5 p  (cost=0.00..207.39 rows=12439 width=18) (actual time=0.010..2.558 rows=12443 loops=1)
  ->  Hash  (cost=0.05..0.05 rows=4 width=12) (actual time=0.017..0.017 rows=4 loops=1)
        Buckets: 1024  Batches: 1  Memory Usage: 9kB
        ->  Values Scan on "*VALUES*"  (cost=0.00..0.05 rows=4 width=12) (actual time=0.002..0.003 rows=4 loops=1)
Planning time: 0.148 ms
Execution time: 8.627 ms

问题是，如果在大型数据库上进行这些查询时，这两个查询之间的执行时间差异是否显着？

Answer 1

尝试使用它：

SELECT 
  sensor_id,
  measurement_time,
  measurement_value
FROM 
  public.measurement_pm2_5 p,
  ( values(12,3000,12000),(27,3000,12000),(1,500,1000),(1,6000,9000) ) as t(sens,t1,t2)
  WHERE p.sensor_id = t.sens
    AND measurement_time BETWEEN to_timestamp(t.t1) AND to_timestamp(t.t2);

此决定通常比任何OR和IN

更快

Answer 2

EXPLAIN ANALYZE //在此处粘贴第一个查询

例如：EXPLAIN ANALYZE select * from employee;

您将详细了解每个子查询的查询和所用时间。

这些SQL查询的执行时间是否相同？

2 个答案: