说明:这个例子转自老白的DBA日记
刚刚坐下,电话就响了,一个客户打过来的,说是碰到一个很奇怪的问题。在一张上千万记录的大表里,做一个SELECT * FROM <TAB_NAME> WHERE ROWNUM<100,居然十多秒钟才出来。我问他这张表是不是碎片很厉害,他所不可能有碎片,昨天才IMP进去的,昨天还没问题,今天就出问题了。而且这张是话单表,不可能会做删除操作的,不会有碎片。我让他马上做个10046发过来。
--相关知识点参考:
http://blog.csdn.net/tianlesoftware/article/details/5857023
10分钟后,他通过QQ把TRACE发过来了: SELECT * FROM ttt where rownum<100
call count cpu elapsed disk query currentrows
------- ------ -------- ---------- -------------------- ---------- ----------
Parse 1 0.14 0.17 44 198 0 0
Execute 1 0.00 0.00 0 0 0 0
Fetch 8 3.71 5.86 67489 68340 0 99
------- ------ -------- -------------------- ---------- ---------- ----------
total 10 3.85 6.03 67533 68538 0 99
从这上面看,确实产生了67533个物理读和68538个逻辑读。执行时间为6.03秒。从等待事件来看:
BINDS #39:
EXEC #39:c=0,e=88,p=0,cr=0,cu=0,mis=0,r=0,dep=0,og=1,tim=1422207486718
WAIT #39: nam='SQL*Net message to client'ela= 7 driver id=1650815232 #bytes=1 p3=0 obj#=206418 tim=1422207486810
WAIT #39: nam='SQL*Net more data to client'ela= 203 driver id=1650815232 #bytes=2002 p3=0 obj#=206418 tim=1422207487071
WAIT #39: nam='SQL*Net more data to client'ela= 66 driver id=1650815232 #bytes=2020 p3=0 obj#=206418 tim=1422207487175
WAIT #39: nam='db file scattered read' ela=515 file#=146 block#=92900 blocks=5 obj#=206418 tim=1422207488208
WAIT #39: nam='db file scattered read' ela=918 file#=146 block#=92905 blocks=8 obj#=206418 tim=1422207489579
WAIT #39: nam='db file scattered read' ela=2121 file#=146 block#=92914 blocks=7 obj#=206418 tim=1422207492091
WAIT #39: nam='db file scattered read' ela=617 file#=146 block#=92921 blocks=8 obj#=206418 tim=1422207493135
WAIT #39: nam='db file scattered read' ela=493 file#=146 block#=92930 blocks=7 obj#=206418 tim=1422207494016
WAIT #39: nam='db file scattered read' ela=1666 file#=147 block#=897417 blocks=8 obj#=206418 tim=1422207496049
WAIT #39: nam='db file scattered read' ela=1026 file#=147 block#=897426 blocks=7 obj#=206418 tim=1422207497350
WAIT #39: nam='db file scattered read' ela=378 file#=147 block#=897433 blocks=8 obj#=206418 tim=1422207498049
WAIT #39: nam='db file scattered read' ela=1075 file#=147 block#=897442 blocks=7 obj#=206418 tim=1422207499416
WAIT #39: nam='db file scattered read' ela=1649 file#=147 block#=897449 blocks=3 obj#=206418 tim=1422207501237
WAIT #39: nam='db file scattered read' ela=2768 file#=147 block#=897453 blocks=4 obj#=206418 tim=1422207504191
WAIT #39: nam='db file scattered read' ela=653 file#=147 block#=897458 blocks=7 obj#=206418 tim=1422207505141
WAIT #39: nam='db file scattered read' ela=1588 file#=147 block#=897465 blocks=8 obj#=206418 tim=1422207507029
WAIT #39: nam='db file scattered read' ela=460 file#=147 block#=897474 blocks=7 obj#=206418 tim=1422207507787
WAIT #39: nam='db file scattered read' ela=608 file#=147 block#=897481 blocks=8 obj#=206418 tim=1422207508697
WAIT #39: nam='db file scattered read' ela=564 file#=147 block#=897490 blocks=7 obj#=206418 tim=1422207509571
WAIT #39: nam='db file scattered read' ela=832 file#=147 block#=897497 blocks=8 obj#=206418 tim=1422207510668
WAIT #39: nam='db file scattered read' ela=846 file#=148 block#=102411 blocks=16 obj#=206418 tim=1422207512030
WAIT #39: nam='db file scattered read' ela=4872 file#=148 block#=102427 blocks=16 obj#=206418 tim=1422207517488
WAIT #39: nam='db file scattered read' ela=1624 file#=148 block#=102443 blocks=16 obj#=206418 tim=1422207520062
确实存在大量的DB FILE SCATTERD READ。这更加坚信了我的观点,表里存在大量的碎片。找第一个SCATTERD READ的参数 file#=146 block#=92900,让客户执行alter system dump datafile 146 block min 92900 block max 92904。
--相关知识点参考:
http://blog.csdn.net/tianlesoftware/article/details/6654786
获得的结果如下:
data_block_dump,data header at0x6000000000208e64
===============
tsiz: 0x1f98
hsiz: 0x4c
pbl: 0x6000000000208e64
bdba: 0x24816ae4 76543210
flag=--------
ntab=1
nrow=29
frre=0
fsbo=0x4c
fseo=0xf7
avsp=0x1f4c
tosp=0x1f4c
0xe:pti[0] nrow=29 offs=0
0x12:pri[0] sfll=1
0x14:pri[1] sfll=2
0x16:pri[2] sfll=3
0x18:pri[3] sfll=4
0x1a:pri[4] sfll=5
0x1c:pri[5] sfll=6
0x1e:pri[6] sfll=7
0x20:pri[7] sfll=8
0x22:pri[8] sfll=9
0x24:pri[9] sfll=10
0x26:pri[10] sfll=11
0x28:pri[11] sfll=12
0x2a:pri[12] sfll=13
0x2c:pri[13] sfll=14
0x2e:pri[14] sfll=15
0x30:pri[15] sfll=16
0x32:pri[16] sfll=17
0x34:pri[17] sfll=18
0x36:pri[18] sfll=19
0x38:pri[19] sfll=20
0x3a:pri[20] sfll=21
0x3c:pri[21] sfll=22
0x3e:pri[22] sfll=23
0x40:pri[23] sfll=24
0x42:pri[24] sfll=25
0x44:pri[25] sfll=26
0x46:pri[26] sfll=27
0x48:pri[27] sfll=28
0x4a:pri[28] sfll=-1
block_row_dump:
end_of_block_dump
里面全部是空块。建议客户做一个ALTER TABLE <table> MOVE;表重组后,发现原来12G的表只剩下800M了。再执行这个SQL,只有12个BUFFER GET了:
Statistics
----------------------------------------------------------
1 recursive calls
0 db block gets
12 consistent gets
1 physical reads
0 redo size
18921 bytes sent via SQL*Net to client
558 bytes received via SQL*Net from client
8 SQL*Net roundtrips to/from client
老白的这个小例子很简单,但是从这个例子里可以看到优化的一个流程。遇到SQL 的问题,可以做10046 事件,获取详细的信息,通过trace,分析原因,找到原因后,就可以解决问题,这里发现是碎片的问题,通过Move table 后,表从原来的12G 变成了800M,解决了碎片的问题,SQL 的性能得到提高。
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