我有一个简单的查询
select count(*)
from taxi_order.ta_orders o
inner join public.t_bases b on b.id = o.id_base
where o.c_phone2 = '012356789'
and b.id_organization = 1
and o.c_date_end < '2017-12-01'::date
group by date_trunc('month', o.c_date_end);
大多数情况下,此查询在不到100毫秒的时间内快速运行,但有时对于某些c_phone2,id_organization组合,它会以非常慢的速度运行4秒。
快速案件的执行计划:
HashAggregate (cost=7005.05..7005.62 rows=163 width=8)
Group Key: date_trunc('month'::text, o.c_date_end)
-> Hash Join (cost=94.30..7004.23 rows=163 width=8)
Hash Cond: (o.id_base = b.id)
-> Index Scan using ix_ta_orders_c_phone2 on ta_orders o (cost=0.57..6899.41 rows=2806 width=12)
Index Cond: ((c_phone2)::text = $3)
Filter: (c_date_end < $4)
-> Hash (cost=93.26..93.26 rows=133 width=4)
-> Bitmap Heap Scan on t_bases b (cost=4.71..93.26 rows=133 width=4)
Recheck Cond: (id_organization = $2)
-> Bitmap Index Scan on ix_t_bases_id_organization (cost=0.00..4.68 rows=133 width=0)
Index Cond: (id_organization = $2)
缓慢案件的执行计划:
HashAggregate (cost=6604.97..6604.98 rows=1 width=8)
Group Key: date_trunc('month'::text, o.c_date_end)
-> Nested Loop (cost=2195.33..6604.97 rows=1 width=8)
-> Bitmap Heap Scan on t_bases b (cost=2.29..7.78 rows=3 width=4)
Recheck Cond: (id_organization = $2)
-> Bitmap Index Scan on ix_t_bases_id_organization (cost=0.00..2.29 rows=3 width=0)
Index Cond: (id_organization = $2)
-> Bitmap Heap Scan on ta_orders o (cost=2193.04..2199.06 rows=3 width=12)
Recheck Cond: (((c_phone2)::text = $3) AND (id_base = b.id) AND (c_date_end < $4))
-> BitmapAnd (cost=2193.04..2193.04 rows=3 width=0)
-> Bitmap Index Scan on ix_ta_orders_c_phone2 (cost=0.00..58.84 rows=3423 width=0)
Index Cond: ((c_phone2)::text = $3)
-> Bitmap Index Scan on ix_ta_orders_id_base_date_end (cost=0.00..2133.66 rows=83472 width=0)
Index Cond: ((id_base = b.id) AND (c_date_end < $4))
为什么查询刨床有时会选择这么慢的无效计划?
修改
表的架构:
craete table taxi_order.ta_orders (
id bigserial not null,
id_base integer not null,
c_phone2 character varying(30),
c_date_end timestamp with time zone,
...
CONSTRAINT pk_ta_orders PRIMARY KEY (id),
CONSTRAINT fk_ta_orders_t_bases REFERENCES public.t_bases (id)
);
craete table public.t_bases (
id serial not null,
id_organization integer not null,
...
CONSTRAINT pk_t_bases PRIMARY KEY (id)
);
ta_orders~100M行,t_bases~2K行。
EDIT2
解释缓慢案例的分析:
HashAggregate (cost=6355.29..6355.29 rows=1 width=8) (actual time=4075.847..4075.847 rows=1 loops=1)
Group Key: date_trunc('month'::text, o.c_date_end)
-> Nested Loop (cost=2112.10..6355.28 rows=1 width=8) (actual time=114.871..4075.803 rows=2 loops=1)
-> Bitmap Heap Scan on t_bases b (cost=2.29..7.78 rows=3 width=4) (actual time=0.061..0.375 rows=133 loops=1)
Recheck Cond: (id_organization = $2)
Heap Blocks: exact=45
-> Bitmap Index Scan on ix_t_bases_id_organization (cost=0.00..2.29 rows=3 width=0) (actual time=0.045..0.045 rows=133 loops=1)
Index Cond: (id_organization = $2)
-> Bitmap Heap Scan on ta_orders o (cost=2109.81..2115.83 rows=3 width=12) (actual time=30.638..30.638 rows=0 loops=133)
Recheck Cond: (((c_phone2)::text = $3) AND (id_base = b.id) AND (c_date_end < $4))
Heap Blocks: exact=2
-> BitmapAnd (cost=2109.81..2109.81 rows=3 width=0) (actual time=30.635..30.635 rows=0 loops=133)
-> Bitmap Index Scan on ix_ta_orders_c_phone2 (cost=0.00..58.85 rows=3427 width=0) (actual time=0.032..0.032 rows=6 loops=133)
Index Cond: ((c_phone2)::text = $3)
-> Bitmap Index Scan on ix_ta_orders_id_base_date_end (cost=0.00..2050.42 rows=80216 width=0) (actual time=30.108..30.108 rows=94206 loops=133)
Index Cond: ((id_base = b.id) AND (c_date_end < $4))
解释快速案例的分析:
HashAggregate (cost=7005.05..7005.62 rows=163 width=8) (actual time=0.927..0.928 rows=1 loops=1)
Group Key: date_trunc('month'::text, o.c_date_end)
-> Hash Join (cost=94.30..7004.23 rows=163 width=8) (actual time=0.903..0.913 rows=2 loops=1)
Hash Cond: (o.id_base = b.id)
-> Index Scan using ix_ta_orders_c_phone2 on ta_orders o (cost=0.57..6899.41 rows=2806 width=12) (actual time=0.591..0.604 rows=4 loops=1)
Index Cond: ((c_phone2)::text = $3)
Filter: (c_date_end < $4)
Rows Removed by Filter: 2
-> Hash (cost=93.26..93.26 rows=133 width=4) (actual time=0.237..0.237 rows=133 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 13kB
-> Bitmap Heap Scan on t_bases b (cost=4.71..93.26 rows=133 width=4) (actual time=0.058..0.196 rows=133 loops=1)
Recheck Cond: (id_organization = $2)
Heap Blocks: exact=45
-> Bitmap Index Scan on ix_t_bases_id_organization (cost=0.00..4.68 rows=133 width=0) (actual time=0.044..0.044 rows=133 loops=1)
Index Cond: (id_organization = $2)
我知道我可以为每个查询创建单独的索引来加快速度。但我想知道选择错误计划的原因是什么?我的统计数据出了什么问题?
答案 0 :(得分:2)
您必须提供t_bases
输出以获得明确的答案。
计划之间的区别在于第二个计划选择嵌套循环连接,因为它估计只会从ANALYZE
中选择非常少的行。由于您抱怨查询速度很慢,因此该估计可能是错误的,导致内部表上的循环过多。
尝试在增加default_statistics_target
之后运行ta_orders(c_phone2, id_base, c_date_end)
来改善您的统计信息。
public class NumberFormatTest {
public static void main(String[] args) throws ParseException {
String db = "1003.25";
String manualFRA = "1 003,25";
double numberDB = Double.parseDouble(db);
String ger = NumberFormat.getInstance(Locale.GERMAN).format(numberDB);
String fra = NumberFormat.getInstance(Locale.FRENCH).format(numberDB);
String eng = NumberFormat.getInstance(Locale.ENGLISH).format(numberDB);
double gerD = NumberFormat.getNumberInstance(Locale.GERMAN).parse(ger).doubleValue();
double fraD = NumberFormat.getNumberInstance(Locale.FRENCH).parse(fra).doubleValue();
double mfraD = NumberFormat.getNumberInstance(Locale.FRENCH).parse(manualFRA).doubleValue();
double engD = NumberFormat.getNumberInstance(Locale.ENGLISH).parse(eng).doubleValue();
System.out.println("From database: " + db);
System.out.println("\tGerman: " + ger);
System.out.println("\tFrench: " + fra);
System.out.println("\tEnglish: " + eng);
System.out.println("\nTo Database: ");
System.out.println("\tfrom German: "+ gerD);
System.out.println("\tfrom French: "+ fraD);
System.out.println("\tfrom manual French: "+ mfraD);
System.out.println("\tfrom Englisch: "+ engD);
}
}
上的多列索引将改善嵌套循环计划的执行时间。
答案 1 :(得分:0)
不确定,但我可以建议您的查询可能有所改进:删除内部联接。您没有从该表中选择任何内容,为什么还要查询它呢?您应该可以在查询中添加where o.id_base = ?
。
如果您希望每次将以下索引添加到ta_orders
:(id_base, c_phone2, c_date_end)
时此查询都能快速运行。具有>
或<
where子句的列最后是非常重要的(否则Postgres将无法使用它)。