我正在使用
我必须在我的页面上显示与订单相关的信息。通过左连接将三个表合并在一起。 表格:
以下是查询语句:
Postgresql-9.2版本
,Windows 7 64位
,RAM 6GB
。这是一个Java企业项目。我必须在我的页面上显示与订单相关的信息。通过左连接将三个表合并在一起。 表格:
- TV_HD(389772行)
- TV_SNAPSHOT(1564756行)
- TD_MAKKA(419298行)
487252
。它还会逐日增加。
表关系:
- TV_HD与TV_SNAPSHOT之间存在“一对多”的关系
- TV_HD与TD_MAKKA之间存在“一对多”的关系
为更好地理解,我现在提供了一个带有SQL查询的图片视图
SELECT * FROM tv_hd where urino = 1630799
SELECT * FROM tv_snapshot where urino = 1630799
SELECT * FROM td_makka where urino = 1630799 此查询大约需要运行90秒。 我如何改善查询性能?
我也考虑过索引。但据我所知,索引实际上是用于从表中获取2%-4%的数据。但在我的情况下,我需要从这三个表中获取所有数据。以下是查询语句:
SELECT count(*)
FROM (SELECT HD.URINO
FROM
TV_HD HD
LEFT JOIN TV_SNAPSHOT T ON (HD.URINO = T.URINO AND HD.TCODE = T.TCODE AND T.DELFLG = 0 AND T.SYUBETSU = 1)
LEFT JOIN TV_SNAPSHOT T_SQ
ON (HD.URINO = T_SQ.URINO AND HD.SQCODE = T_SQ.TCODE AND T_SQ.DELFLG = 0 AND T_SQ.SYUBETSU = 3)
LEFT JOIN (SELECT N.URINO
FROM
TD_MAKKA N
WHERE
N.UPDATETIME IN (
SELECT MIN(NMIN.UPDATETIME)
FROM
TD_MAKKA NMIN
WHERE
N.URINO = NMIN.URINO
AND
NMIN.TORIKESHIFLG <> -1
)
) NYUMIN
ON (HD.URINO = NYUMIN.URINO)
LEFT JOIN
(
SELECT
NSUM.URINO,
SUM(COALESCE(NSUM.NYUKIN, 0)) NYUKIN,
SUM(COALESCE(NSUM.NYUKIN, 0)) + SUM(COALESCE(NSUM.TESU, 0)) + SUM(COALESCE(NSUM.SOTA, 0)) SUMNYUKIN
FROM
TD_MAKKA NSUM
GROUP BY
URINO
) NYUSUM
ON (HD.URINO = NYUSUM.URINO)
LEFT JOIN
(
SELECT N.URINO
FROM
TD_MAKKA N
WHERE
UPDATETIME = (
SELECT MAX(UPDATETIME)
FROM
TD_MAKKA NMAX
WHERE
N.URINO = NMAX.URINO
AND
NMAX.TORIKESHIFLG <> -1
)
) NYUMAX
ON (HD.URINO = NYUMAX.URINO)
WHERE ((HD.URIBRUI <> '1') OR (HD.URIBRUI = '1' AND T_SQ.NYUKOBEFLG = '-1'))
ORDER BY
HD.URINO DESC
) COUNT_
这是 EXPLAIN ANALYZE
的结果。
Aggregate (cost=7246861.21..7246861.22 rows=1 width=0) (actual time=69549.159..69549.159 rows=1 loops=1)
-> Merge Left Join (cost=7240188.92..7242117.36 rows=379508 width=6) (actual time=68602.689..69510.563 rows=487252 loops=1)
Merge Cond: (hd.urino = n.urino)
-> Sort (cost=3727299.33..3728248.10 rows=379508 width=6) (actual time=62160.072..62557.132 rows=420036 loops=1)
Sort Key: hd.urino
Sort Method: external merge Disk: 6984kB
-> Hash Right Join (cost=169264.26..3686940.26 rows=379508 width=6) (actual time=54796.930..60172.248 rows=420036 loops=1)
Hash Cond: (n.urino = hd.urino)
-> Seq Scan on td_makka n (cost=0.00..3511201.36 rows=209673 width=6) (actual time=24.326..4640.020 rows=419143 loops=1)
Filter: (SubPlan 1)
Rows Removed by Filter: 155
SubPlan 1
-> Aggregate (cost=8.33..8.34 rows=1 width=23) (actual time=0.009..0.009 rows=1 loops=419298)
-> Index Scan using idx_td_makka on td_makka nmin (cost=0.00..8.33 rows=1 width=23) (actual time=0.006..0.007 rows=1 loops=419298)
Index Cond: (n.urino = urino)
Filter: (torikeshiflg <> (-1)::numeric)
Rows Removed by Filter: 0
-> Hash (cost=163037.41..163037.41 rows=379508 width=6) (actual time=54771.078..54771.078 rows=386428 loops=1)
Buckets: 4096 Batches: 16 Memory Usage: 737kB
-> Hash Right Join (cost=75799.55..163037.41 rows=379508 width=6) (actual time=51599.167..54605.901 rows=386428 loops=1)
Hash Cond: ((t_sq.urino = hd.urino) AND (t_sq.tcode = hd.sqcode))
Filter: ((hd.uribrui <> '1'::bpchar) OR ((hd.uribrui = '1'::bpchar) AND (t_sq.nyukobeflg = (-1)::numeric)))
Rows Removed by Filter: 3344
-> Seq Scan on tv_snapshot t_sq (cost=0.00..73705.42 rows=385577 width=15) (actual time=0.053..2002.953 rows=389983 loops=1)
Filter: ((delflg = 0::numeric) AND (syubetsu = 3::numeric))
Rows Removed by Filter: 1174773
-> Hash (cost=68048.99..68048.99 rows=389771 width=14) (actual time=51596.055..51596.055 rows=389772 loops=1)
Buckets: 4096 Batches: 16 Memory Usage: 960kB
-> Hash Right Join (cost=21125.85..68048.99 rows=389771 width=14) (actual time=579.405..51348.270 rows=389772 loops=1)
Hash Cond: (nyusum.urino = hd.urino)
-> Subquery Scan on nyusum (cost=0.00..35839.52 rows=365638 width=6) (actual time=17.435..49996.674 rows=385537 loops=1)
-> GroupAggregate (cost=0.00..32183.14 rows=365638 width=34) (actual time=17.430..49871.702 rows=385537 loops=1)
-> Index Scan using idx_td_makka on td_makka nsum (cost=0.00..21456.76 rows=419345 width=34) (actual time=0.017..48357.702 rows=419298 loops=1)
-> Hash (cost=13969.71..13969.71 rows=389771 width=20) (actual time=491.549..491.549 rows=389772 loops=1)
Buckets: 4096 Batches: 32 Memory Usage: 567kB
-> Seq Scan on tv_hd hd (cost=0.00..13969.71 rows=389771 width=20) (actual time=0.052..242.415 rows=389772 loops=1)
-> Sort (cost=3512889.60..3512894.84 rows=2097 width=6) (actual time=6442.600..6541.728 rows=486359 loops=1)
Sort Key: n.urino
Sort Method: external sort Disk: 8600kB
-> Seq Scan on td_makka n (cost=0.00..3512773.90 rows=2097 width=6) (actual time=0.135..4053.116 rows=419143 loops=1)
Filter: ((updatetime)::text = (SubPlan 2))
Rows Removed by Filter: 155
SubPlan 2
-> Aggregate (cost=8.33..8.34 rows=1 width=23) (actual time=0.008..0.008 rows=1 loops=419298)
-> Index Scan using idx_td_makka on td_makka nmax (cost=0.00..8.33 rows=1 width=23) (actual time=0.005..0.006 rows=1 loops=419298)
Index Cond: (n.urino = urino)
Filter: (torikeshiflg <> (-1)::numeric)
Rows Removed by Filter: 0
Total runtime: 69575.139 ms
这里是解释分析结果的详细信息:
EXPLAIN ANALYZE <long_query_here>
。告诉我们分析结果,然后我们可以讨论如何进行优化。如果不清楚需要修复什么,那就很难说了。 - Makotourino
列将受益于索引。 - Makoto