Sql 这是否解释了Postgres查询如此缓慢的原因
我在PostgresSQL数据库上执行了许多查询，大多数查询执行得非常快，但有一个查询执行得非常慢。即使在测试时，我只将主发布表中的记录限制为100条，所有查询都基于发布表，这需要50秒，而所有其他查询都不到一秒 这里是包含多行的关键表 l_艺术家_录音 录制和发布 艺术家 这是我的问题Sql 这是否解释了Postgres查询如此缓慢的原因,sql,postgresql,postgresql-9.3,explain,Sql,Postgresql,Postgresql 9.3,Explain,我在PostgresSQL数据库上执行了许多查询，大多数查询执行得非常快，但有一个查询执行得非常慢。即使在测试时，我只将主发布表中的记录限制为100条，所有查询都基于发布表，这需要50秒，而所有其他查询都不到一秒 这里是包含多行的关键表 l_艺术家_录音 录制和发布 艺术家 这是我的问题 SELECT DISTINCT t1.entity1 as recordingId, t1.entity0 as artistId, t2.id as linkid, t3.name as type,
SELECT DISTINCT t1.entity1 as recordingId,
t1.entity0 as artistId,
t2.id as linkid,
t3.name as type,
t4.name,
t4.sort_name,
t4.gid,
t9.latinname as latinName,
t9.islatin,
t7.name as linkattribute,
at.name as artistType
FROM l_artist_recording t1
INNER JOIN link t2 on t1.link=t2.id
INNER JOIN link_type t3 on t2.link_type=t3.id
AND (t3.name='performer' OR t3.name='instrument' OR t3.name='vocal' )
LEFT JOIN link_attribute t6
ON t6.link = t2.id
LEFT JOIN link_attribute_type t7
ON t6.attribute_type = t7.id
INNER JOIN artist t4 on t1.entity0=t4.id
INNER JOIN artist_latin t9 on t9.id=t4.id
LEFT JOIN artist_type at on t4.type=at.id
INNER JOIN recording t5 on t1.entity1=t5.id
INNER JOIN recording_release rr ON t5.id = rr.recording_id
WHERE rr.release_id BETWEEN ? AND ?
ORDER BY recordingId, artistId, linkid, linkattribute";
QUERY PLAN
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Unique (cost=336796.42..336797.05 rows=21 width=99) (actual time=93229.472..93233.580 rows=1271 loops=1)
Buffers: shared hit=5215 read=97399, temp read=138990 written=138908
-> Sort (cost=336796.42..336796.48 rows=21 width=99) (actual time=93229.468..93230.653 rows=1286 loops=1)
Sort Key: t1.entity1, t1.entity0, t2.id, t7.name, t3.name, t4.name, t4.sort_name, t4.gid, t9.latinname, t9.islatin, at.name
Sort Method: quicksort Memory: 245kB
Buffers: shared hit=5215 read=97399, temp read=138990 written=138908
-> Nested Loop (cost=334176.87..336795.96 rows=21 width=99) (actual time=91632.892..93226.628 rows=1286 loops=1)
Buffers: shared hit=5197 read=97399, temp read=138990 written=138908
-> Hash Join (cost=334176.44..336665.45 rows=21 width=103) (actual time=91632.830..93211.718 rows=1286 loops=1)
Hash Cond: (rr.recording_id = t1.entity1)
Buffers: shared hit=151 read=97315, temp read=138990 written=138908
-> Index Scan using recording_release_release_id on recording_release rr (cost=0.44..1833.24 rows=891 width=4) (actual time=0.028..2.371 rows=825 loops=1)
Index Cond: ((release_id >= 1) AND (release_id <= 100))
Buffers: shared hit=130 read=121
-> Hash (cost=333485.62..333485.62 rows=55230 width=99) (actual time=91631.881..91631.881 rows=3813157 loops=1)
Buckets: 8192 Batches: 32 (originally 1) Memory Usage: 20481kB
Buffers: shared hit=21 read=97194, temp read=61835 written=116275
-> Hash Left Join (cost=132574.41..333485.62 rows=55230 width=99) (actual time=12380.770..84898.987 rows=3813157 loops=1)
Hash Cond: (t4.type = at.id)
.....
在某些情况下，当使用占位符时，数据库统计信息无法轻松确定将为中间查询返回的行数。因此，有时会返回非最佳解释计划 如果将查询更新为内部联接上的子选择，则会看到更好的结果
Inner Join (select <your cols> from recording_release where release_id between ? and ?) rr
在JOIN子句中添加一个条件过滤器可以帮助优化器解决不足，我发现它比子查询更简短、更可读
INNER JOIN link_type t3 on t2.link_type=t3.id
AND (t3.name='performer' OR t3.name='instrument' OR t3.name='vocal' )
当选择1到100个版本时，它是有效的，但仅仅增加到1000个版本就严重影响了性能。如果你有什么想法的话，我已经为1到100和1到1000的新查询添加了查询计划？性能差异是什么？根据你的解释计划，你将从约1200行增加到约12000行一个数量级。它从不到一秒增加到12秒100次发布到1000次发布，因此在此基础上，在更高的值下速度会太慢，但好消息是，当我增加到20000次发布时，它实际上只增加到26秒，其他一些查询的长度相似，所以性能还是可以接受的：这一点很好，但你的例子是错误的，因为这是我从你开始的，你应该在partFor postgres之间移动WHERE版本，这是不正确的。连接条件可以放在任何地方，生成的查询计划将是相同的。当然，除了左连接
QUERY PLAN
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Unique (cost=336796.42..336797.05 rows=21 width=99) (actual time=93229.472..93233.580 rows=1271 loops=1)
Buffers: shared hit=5215 read=97399, temp read=138990 written=138908
-> Sort (cost=336796.42..336796.48 rows=21 width=99) (actual time=93229.468..93230.653 rows=1286 loops=1)
Sort Key: t1.entity1, t1.entity0, t2.id, t7.name, t3.name, t4.name, t4.sort_name, t4.gid, t9.latinname, t9.islatin, at.name
Sort Method: quicksort Memory: 245kB
Buffers: shared hit=5215 read=97399, temp read=138990 written=138908
-> Nested Loop (cost=334176.87..336795.96 rows=21 width=99) (actual time=91632.892..93226.628 rows=1286 loops=1)
Buffers: shared hit=5197 read=97399, temp read=138990 written=138908
-> Hash Join (cost=334176.44..336665.45 rows=21 width=103) (actual time=91632.830..93211.718 rows=1286 loops=1)
Hash Cond: (rr.recording_id = t1.entity1)
Buffers: shared hit=151 read=97315, temp read=138990 written=138908
-> Index Scan using recording_release_release_id on recording_release rr (cost=0.44..1833.24 rows=891 width=4) (actual time=0.028..2.371 rows=825 loops=1)
Index Cond: ((release_id >= 1) AND (release_id <= 100))
Buffers: shared hit=130 read=121
-> Hash (cost=333485.62..333485.62 rows=55230 width=99) (actual time=91631.881..91631.881 rows=3813157 loops=1)
Buckets: 8192 Batches: 32 (originally 1) Memory Usage: 20481kB
Buffers: shared hit=21 read=97194, temp read=61835 written=116275
-> Hash Left Join (cost=132574.41..333485.62 rows=55230 width=99) (actual time=12380.770..84898.987 rows=3813157 loops=1)
Hash Cond: (t4.type = at.id)
.....
SELECT DISTINCT t1.entity1 as recordingId,
t1.entity0 as artistId, t2.id as linkid,
t3.name as type,
t4.name,
t4.sort_name,
t4.gid,
t9.latinname as latinName,
t9.islatin,
t7.name as linkattribute,
at.name as artistType
FROM
(
SELECT t1.*
FROM recording_release rr
INNER JOIN l_artist_recording t1 on t1.entity1=rr.recording_id
WHERE rr.release_id between ? AND ?
) AS t1
INNER JOIN link t2 on t1.link=t2.id
INNER JOIN link_type t3 on t2.link_type=t3.id
AND (t3.name='performer' OR t3.name='instrument' OR t3.name='vocal' )
LEFT JOIN link_attribute t6 ON t6.link = t2.id
LEFT JOIN link_attribute_type t7 ON t6.attribute_type = t7.id
INNER JOIN artist t4 on t1.entity0=t4.id
INNER JOIN artist_latin t9 on t9.id=t4.id
LEFT JOIN artist_type at on t4.type=at.id
ORDER BY recordingId, artistId, linkid, linkattribute;
QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Unique (cost=49182.37..49183.00 rows=21 width=99) (actual time=917.393..920.229 rows=1271 loops=1)
Buffers: shared hit=21647
-> Sort (cost=49182.37..49182.43 rows=21 width=99) (actual time=917.390..918.206 rows=1286 loops=1)
Sort Key: t1.entity1, t1.entity0, t2.id, t7.name, t3.name, t4.name, t4.sort_name, t4.gid, t9.latinname, t9.islatin, at.name
Sort Method: quicksort Memory: 245kB
Buffers: shared hit=21647
-> Hash Left Join (cost=9574.07..49181.91 rows=21 width=99) (actual time=861.507..915.523 rows=1286 loops=1)
Hash Cond: (t4.type = at.id)
Buffers: shared hit=21629
-> Nested Loop (cost=9572.93..49180.54 rows=21 width=96) (actual time=861.479..913.388 rows=1286 loops=1)
Buffers: shared hit=21628
-> Nested Loop (cost=9572.50..49028.19 rows=21 width=86) (actual time=861.455..904.887 rows=1286 loops=1)
Buffers: shared hit=16484
-> Hash Left Join (cost=9572.08..48875.86 rows=21 width=34) (actual time=861.419..895.695 rows=1286 loops=1)
Hash Cond: (t6.attribute_type = t7.id)
Buffers: shared hit=11340
-> Nested Loop Left Join (cost=9530.00..48833.50 rows=21 width=28) (actual time=859.792..891.958 rows=1286 loops=1)
Buffers: shared hit=11320
-> Hash Join (cost=9529.58..48752.33 rows=21 width=24) (actual time=859.709..884.275 rows=1232 loops=1)
Hash Cond: (t1.link = t2.id)
Buffers: shared hit=7623
-> Nested Loop (cost=0.87..39213.26 rows=2708 width=12) (actual time=0.043..12.256 rows=2559 loops=1)
Buffers: shared hit=4005
-> Index Scan using recording_release_release_id on recording_release rr (cost=0.44..1833.24 rows=891 width=4) (actual time=0.020..1.477 rows=825 loops=1)
Index Cond: ((release_id >= 1) AND (release_id <= 100))
Buffers: shared hit=251
-> Index Scan using l_artist_recording_entity1_idx on l_artist_recording t1 (cost=0.43..41.84 rows=11 width=12) (actual time=0.003..0.007 rows=3 loops=825)
Index Cond: (entity1 = rr.recording_id)
Buffers: shared hit=3754
-> Hash (cost=9487.20..9487.20 rows=3321 width=16) (actual time=859.601..859.601 rows=179079 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 8069kB
Buffers: shared hit=3618
-> Hash Join (cost=23.60..9487.20 rows=3321 width=16) (actual time=0.095..721.936 rows=179079 loops=1)
Hash Cond: (t2.link_type = t3.id)
Buffers: shared hit=3618
-> Seq Scan on link t2 (cost=0.00..7842.74 rows=423374 width=8) (actual time=0.003..286.605 rows=423374 loops=1)
Buffers: shared hit=3609
-> Hash (cost=23.55..23.55 rows=4 width=16) (actual time=0.075..0.075 rows=6 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 1kB
Buffers: shared hit=9
-> Bitmap Heap Scan on link_type t3 (cost=12.84..23.55 rows=4 width=16) (actual time=0.044..0.068 rows=6 loops=1)
Recheck Cond: (((name)::text = 'performer'::text) OR ((name)::text = 'instrument'::text) OR ((name)::text = 'vocal'::text))
Buffers: shared hit=9
-> BitmapOr (cost=12.84..12.84 rows=4 width=0) (actual time=0.032..0.032 rows=0 loops=1)
Buffers: shared hit=6
-> Bitmap Index Scan on link_type_name_idx (cost=0.00..4.28 rows=1 width=0) (actual time=0.015..0.015 rows=2 loops=1)
Index Cond: ((name)::text = 'performer'::text)
Buffers: shared hit=2
-> Bitmap Index Scan on link_type_name_idx (cost=0.00..4.28 rows=1 width=0) (actual time=0.012..0.012 rows=2 loops=1)
Index Cond: ((name)::text = 'instrument'::text)
Buffers: shared hit=2
-> Bitmap Index Scan on link_type_name_idx (cost=0.00..4.28 rows=1 width=0) (actual time=0.003..0.003 rows=2 loops=1)
Index Cond: ((name)::text = 'vocal'::text)
Buffers: shared hit=2
-> Index Only Scan using link_attribute_pkey on link_attribute t6 (cost=0.42..3.84 rows=2 width=8) (actual time=0.003..0.003 rows=1 loops=1232)
Index Cond: (link = t2.id)
Heap Fetches: 0
Buffers: shared hit=3697
-> Hash (cost=29.81..29.81 rows=981 width=14) (actual time=1.602..1.602 rows=981 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 47kB
Buffers: shared hit=20
-> Seq Scan on link_attribute_type t7 (cost=0.00..29.81 rows=981 width=14) (actual time=0.011..0.827 rows=981 loops=1)
Buffers: shared hit=20
-> Index Scan using artist_pkey on artist t4 (cost=0.43..7.24 rows=1 width=52) (actual time=0.003..0.004 rows=1 loops=1286)
Index Cond: (id = t1.entity0)
Buffers: shared hit=5144
-> Index Scan using artist_latin_pkey on artist_latin t9 (cost=0.43..7.24 rows=1 width=18) (actual time=0.003..0.004 rows=1 loops=1286)
Index Cond: (id = t1.entity0)
Buffers: shared hit=5144
-> Hash (cost=1.06..1.06 rows=6 width=11) (actual time=0.014..0.014 rows=6 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 1kB
Buffers: shared hit=1
-> Seq Scan on artist_type at (cost=0.00..1.06 rows=6 width=11) (actual time=0.003..0.007 rows=6 loops=1)
Buffers: shared hit=1
Total runtime: 922.078 ms
(75 rows)
QUERY PLAN
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Unique (cost=213157.51..213163.93 rows=214 width=99) (actual time=27763.225..27797.833 rows=11003 loops=1)
Buffers: shared hit=186910 read=59034, temp read=26077 written=26047
-> Sort (cost=213157.51..213158.04 rows=214 width=99) (actual time=27763.223..27774.013 rows=17087 loops=1)
Sort Key: t1.entity1, t1.entity0, t2.id, t7.name, t3.name, t4.name, t4.sort_name, t4.gid, t9.latinname, t9.islatin, at.name
Sort Method: quicksort Memory: 3291kB
Buffers: shared hit=186910 read=59034, temp read=26077 written=26047
-> Hash Left Join (cost=184770.48..213149.22 rows=214 width=99) (actual time=26757.748..27732.727 rows=17087 loops=1)
Hash Cond: (t4.type = at.id)
Buffers: shared hit=186892 read=59034, temp read=26077 written=26047
-> Nested Loop (cost=184769.35..213145.63 rows=214 width=96) (actual time=26757.717..27705.989 rows=17087 loops=1)
Buffers: shared hit=186891 read=59034, temp read=26077 written=26047
-> Nested Loop (cost=184768.92..211593.13 rows=214 width=86) (actual time=26757.687..27597.879 rows=17087 loops=1)
Buffers: shared hit=118447 read=59034, temp read=26077 written=26047
-> Hash Left Join (cost=184768.49..210040.78 rows=214 width=34) (actual time=26757.646..27484.937 rows=17087 loops=1)
Hash Cond: (t6.attribute_type = t7.id)
Buffers: shared hit=50080 read=59034, temp read=26077 written=26047
-> Nested Loop Left Join (cost=184726.42..209995.76 rows=214 width=28) (actual time=26756.055..27456.678 rows=17087 loops=1)
Buffers: shared hit=50060 read=59034, temp read=26077 written=26047
-> Hash Join (cost=184726.00..209168.66 rows=214 width=24) (actual time=26756.000..27370.294 rows=14507 loops=1)
Hash Cond: (rr.recording_id = t1.entity1)
Buffers: shared hit=6525 read=59034, temp read=26077 written=26047
-> Index Scan using recording_release_release_id on recording_release rr (cost=0.44..17820.60 rows=8992 width=4) (actual time=0.019..13.477 rows=10502 loops=1)
Index Cond: ((release_id >= 1) AND (release_id <= 1000))
Buffers: shared hit=2416
-> Hash (cost=184035.19..184035.19 rows=55230 width=24) (actual time=26755.546..26755.546 rows=3637342 loops=1)
Buckets: 8192 Batches: 16 (originally 1) Memory Usage: 20481kB
Buffers: shared hit=4109 read=59034, temp written=17302
-> Hash Join (cost=9528.71..184035.19 rows=55230 width=24) (actual time=850.530..23553.356 rows=3637342 loops=1)
Hash Cond: (t1.link = t2.id)
Buffers: shared hit=4109 read=59034
-> Seq Scan on l_artist_recording t1 (cost=0.00..129942.91 rows=7041791 width=12) (actual time=0.027..4867.525 rows=7041650 loops=1)
Buffers: shared hit=491 read=59034
-> Hash (cost=9487.20..9487.20 rows=3321 width=16) (actual time=850.421..850.421 rows=179079 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 8069kB
Buffers: shared hit=3618
-> Hash Join (cost=23.60..9487.20 rows=3321 width=16) (actual time=0.100..713.303 rows=179079 loops=1)
Hash Cond: (t2.link_type = t3.id)
Buffers: shared hit=3618
-> Seq Scan on link t2 (cost=0.00..7842.74 rows=423374 width=8) (actual time=0.003..281.553 rows=423374 loops=1)
Buffers: shared hit=3609
-> Hash (cost=23.55..23.55 rows=4 width=16) (actual time=0.079..0.079 rows=6 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 1kB
Buffers: shared hit=9
-> Bitmap Heap Scan on link_type t3 (cost=12.84..23.55 rows=4 width=16) (actual time=0.042..0.070 rows=6 loops=1)
Recheck Cond: (((name)::text = 'performer'::text) OR ((name)::text = 'instrument'::text) OR ((name)::text = 'vocal'::text))
Buffers: shared hit=9
-> BitmapOr (cost=12.84..12.84 rows=4 width=0) (actual time=0.034..0.034 rows=0 loops=1)
Buffers: shared hit=6
-> Bitmap Index Scan on link_type_name_idx (cost=0.00..4.28 rows=1 width=0) (actual time=0.016..0.016 rows=2 loops=1)
Index Cond: ((name)::text = 'performer'::text)
Buffers: shared hit=2
-> Bitmap Index Scan on link_type_name_idx (cost=0.00..4.28 rows=1 width=0) (actual time=0.011..0.011 rows=2 loops=1)
Index Cond: ((name)::text = 'instrument'::text)
Buffers: shared hit=2
-> Bitmap Index Scan on link_type_name_idx (cost=0.00..4.28 rows=1 width=0) (actual time=0.003..0.003 rows=2 loops=1)
Index Cond: ((name)::text = 'vocal'::text)
Buffers: shared hit=2
-> Index Only Scan using link_attribute_pkey on link_attribute t6 (cost=0.42..3.84 rows=2 width=8) (actual time=0.002..0.003 rows=1 loops=14507)
Index Cond: (link = t2.id)
Heap Fetches: 0
Buffers: shared hit=43535
-> Hash (cost=29.81..29.81 rows=981 width=14) (actual time=1.568..1.568 rows=981 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 47kB
Buffers: shared hit=20
-> Seq Scan on link_attribute_type t7 (cost=0.00..29.81 rows=981 width=14) (actual time=0.010..0.785 rows=981 loops=1)
Buffers: shared hit=20
-> Index Scan using artist_pkey on artist t4 (cost=0.43..7.24 rows=1 width=52) (actual time=0.003..0.004 rows=1 loops=17087)
Index Cond: (id = t1.entity0)
Buffers: shared hit=68367
-> Index Scan using artist_latin_pkey on artist_latin t9 (cost=0.43..7.24 rows=1 width=18) (actual time=0.003..0.004 rows=1 loops=17087)
Index Cond: (id = t1.entity0)
Buffers: shared hit=68444
-> Hash (cost=1.06..1.06 rows=6 width=11) (actual time=0.013..0.013 rows=6 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 1kB
Buffers: shared hit=1
-> Seq Scan on artist_type at (cost=0.00..1.06 rows=6 width=11) (actual time=0.003..0.006 rows=6 loops=1)
Buffers: shared hit=1
Total runtime: 27805.582 ms
(78 rows)
SELECT DISTINCT t1.entity1 as recordingId,
t1.entity0 as artistId,
t2.id as linkid,
t3.name as type,
t4.name,
t4.sort_name,
t4.gid,
t9.latinname as latinName,
t9.islatin,
t7.name as linkattribute,
at.name as artistType
FROM recording_release rr
INNER JOIN l_artist_recording t1 on t1.entity1=rr.recording_id
AND rr.release_id between ? AND ?
INNER JOIN link t2 on t1.link=t2.id
INNER JOIN link_type t3 on t2.link_type=t3.id
AND (t3.name='performer' OR t3.name='instrument' OR t3.name='vocal' )
LEFT JOIN link_attribute t6
ON t6.link = t2.id
LEFT JOIN link_attribute_type t7
ON t6.attribute_type = t7.id
INNER JOIN artist t4 on t1.entity0=t4.id
INNER JOIN artist_latin t9 on t9.id=t4.id
LEFT JOIN artist_type at on t4.type=at.id
ORDER BY recordingId, artistId, linkid, linkattribute;
Inner Join (select <your cols> from recording_release where release_id between ? and ?) rr
INNER JOIN link_type t3 on t2.link_type=t3.id
AND (t3.name='performer' OR t3.name='instrument' OR t3.name='vocal' )
--Major rework a la @joop
WITH selected AS (
SELECT ar.entity1, ar.entity0, ar.link
FROM l_artist_recording ar
WHERE EXISTS (
SELECT *
FROM recording_release rr
WHERE ar.entity1=rr.recording_id
AND rr.release_id between ? AND ?
)
)
SELECT sel.entity1 as recordingId
, sel.entity0 as artistId
, lnk.id as linkid
, atyp.name as artistType
, rol.name as roletype
, art.name as artname
, art.sort_name
, art.gid
, lat.latinname as latinName
, lat.islatin
, att.name as linkattribute
FROM selected sel
JOIN artist art on art.id = sel.entity0
JOIN artist_latin lat on lat.id= art.id
JOIN link lnk on lnk.id = sel.link
JOIN link_type rol on rol.id = lnk.link_type AND rol.name IN ('performer', 'instrument', 'vocal' )
LEFT JOIN link_attribute la ON la.link = lnk.id
/*LEFT*/ JOIN link_attribute_type att ON att.id = la.attribute_type
LEFT JOIN artist_type atyp on atyp.id = art.type
ORDER BY 1,2,3,4
;
-- The same without the CTE:
SELECT sel.entity1 as recordingId
, sel.entity0 as artistId
, lnk.id as linkid
, atyp.name as artistType
, rol.name as roletype
, art.name as artname
, art.sort_name
, art.gid
, lat.latinname as latinName
, lat.islatin
, att.name as linkattribute
FROM (
SELECT ar.entity1, ar.entity0 , ar.link
FROM l_artist_recording ar
WHERE EXISTS (
SELECT *
FROM recording_release rr
WHERE ar.entity1=rr.recording_id
AND rr.release_id between ? AND ?
)
) sel
JOIN artist art on art.id = sel.entity0
JOIN artist_latin lat on lat.id= art.id
JOIN link lnk on lnk.id = sel.link
JOIN link_type rol on rol.id = lnk.link_type AND rol.name IN ('performer', 'instrument', 'vocal' )
LEFT JOIN link_attribute la ON la.link = lnk.id
/*LEFT*/ JOIN link_attribute_type att ON att.id = la.attribute_type
LEFT JOIN artist_type atyp on atyp.id = art.type
ORDER BY 1,2,3,4
;