共计 8604 个字符,预计需要花费 22 分钟才能阅读完成。
明天遇到了一个比拟奇怪的问题,客户说把一个表分区后 SELECT 解决变慢了。原本 SELECT 解决变慢是很常见的问题,可是我看了 10046Trace 后还是感觉有些中央值得深究一下。
咱们先来看看 Tkprof 之后的 10046Trace。
◆分区前
call count cpu elapsed disk query current rows
------- ------ -------- ---------- ---------- ---------- ---------- ----------
Parse 1 0.00 0.00 0 40 0 0
Execute 1 0.00 0.00 0 0 0 0
Fetch 1 2.41 2.58 15177 15177 0 1
------- ------ -------- ---------- ---------- ---------- ---------- ----------
total 3 2.42 2.59 15177 15217 0 1
Misses in library cache during parse: 1
Optimizer mode: ALL_ROWS
Parsing user id: 78
Number of plan statistics captured: 1
Rows (1st) Rows (avg) Rows (max) Row Source Operation
---------- ---------- ---------- ---------------------------------------------------
1 1 1 SORT AGGREGATE (cr=15177 pr=15177 pw=0 time=2583401 us)
0 0 0 FIRST ROW (cr=15177 pr=15177 pw=0 time=2583388 us cost=5601 size=14 card=1)
0 0 0 INDEX RANGE SCAN (MIN/MAX) XXXX_IX03 (cr=15177 pr=15177 pw=0 time=2583385 us cost=5601 size=14 card=1)(object id 254189)
Elapsed times include waiting on following events:
Event waited on Times Max. Wait Total Waited
---------------------------------------- Waited ---------- ------------
db file sequential read 15177 0.00 0.36
◆分区后
call count cpu elapsed disk query current rows
------- ------ -------- ---------- ---------- ---------- ---------- ----------
Parse 1 0.00 0.00 0 0 0 0
Execute 1 0.00 0.00 0 0 0 0
Fetch 1 2.46 4.10 14828 14828 0 1
------- ------ -------- ---------- ---------- ---------- ---------- ----------
total 3 2.46 4.10 14828 14828 0 1
Misses in library cache during parse: 1
Optimizer mode: ALL_ROWS
Parsing user id: 78
Number of plan statistics captured: 1
Rows (1st) Rows (avg) Rows (max) Row Source Operation
---------- ---------- ---------- ---------------------------------------------------
1 1 1 SORT AGGREGATE (cr=14828 pr=14828 pw=0 time=4103521 us)
0 0 0 FIRST ROW (cr=14828 pr=14828 pw=0 time=4103511 us cost=4508 size=14 card=1)
0 0 0 INDEX RANGE SCAN (MIN/MAX) XXXX_IX15 (cr=14828 pr=14828 pw=0 time=4103509 us cost=4508 size=14 card=1)(object id 352194)
Elapsed times include waiting on following events:
Event waited on Times Max. Wait Total Waited
---------------------------------------- Waited ---------- ------------
db file sequential read 14828 0.00 1.85
从下面的数据来看,咱们发现执行工夫的差别次要来自索引的 I / O 待机“db file sequential read”。为了看看具体有啥区别,咱们再来看看 Tkprof 之前的 10046Trace 文件。
◆分区前
**-----------------------------------------------
WAIT #139891128650264: nam='db file sequential read' ela= 12 file#=15 block#=702838 blocks=1 obj#=254189 tim=45007446902
WAIT #139891128650264: nam='db file sequential read' ela= 11 file#=15 block#=702839 blocks=1 obj#=254189 tim=45007447264
WAIT #139891128650264: nam='db file sequential read' ela= 11 file#=15 block#=702840 blocks=1 obj#=254189 tim=45007447457
WAIT #139891128650264: nam='db file sequential read' ela= 75 file#=15 block#=702841 blocks=1 obj#=254189 tim=45007447706
WAIT #139891128650264: nam='db file sequential read' ela= 12 file#=15 block#=702842 blocks=1 obj#=254189 tim=45007447908
WAIT #139891128650264: nam='db file sequential read' ela= 10 file#=15 block#=702843 blocks=1 obj#=254189 tim=45007448123
WAIT #139891128650264: nam='db file sequential read' ela= 11 file#=15 block#=702844 blocks=1 obj#=254189 tim=45007448314
WAIT #139891128650264: nam='db file sequential read' ela= 15 file#=15 block#=702845 blocks=1 obj#=254189 tim=45007448503
WAIT #139891128650264: nam='db file sequential read' ela= 10 file#=15 block#=702846 blocks=1 obj#=254189 tim=45007448804
WAIT #139891128650264: nam='db file sequential read' ela= 11 file#=15 block#=702847 blocks=1 obj#=254189 tim=45007449000
-----------------------------------------------**
◆分区后
-----------------------------------------------
WAIT #139891129837744: nam='db file sequential read' ela= 1535 file#=15 block#=5593761 blocks=1 obj#=352194 tim=45021020310
WAIT #139891129837744: nam='db file sequential read' ela= 1642 file#=15 block#=5593777 blocks=1 obj#=352194 tim=45021022129
WAIT #139891129837744: nam='db file sequential read' ela= 1037 file#=15 block#=5593538 blocks=1 obj#=352194 tim=45021023332
WAIT #139891129837744: nam='db file sequential read' ela= 947 file#=15 block#=5593554 blocks=1 obj#=352194 tim=45021024455
WAIT #139891129837744: nam='db file sequential read' ela= 1220 file#=15 block#=5593570 blocks=1 obj#=352194 tim=45021025868
WAIT #139891129837744: nam='db file sequential read' ela= 998 file#=15 block#=5593586 blocks=1 obj#=352194 tim=45021027237
WAIT #139891129837744: nam='db file sequential read' ela= 1109 file#=15 block#=5593602 blocks=1 obj#=352194 tim=45021028638
WAIT #139891129837744: nam='db file sequential read' ela= 1138 file#=15 block#=5593618 blocks=1 obj#=352194 tim=45021030019
WAIT #139891129837744: nam='db file sequential read' ela= 1251 file#=15 block#=5593634 blocks=1 obj#=352194 tim=45021031509
WAIT #139891129837744: nam='db file sequential read' ela= 1518 file#=15 block#=5593650 blocks=1 obj#=352194 tim=45021033196
…略…
WAIT #139891129837744: nam='db file sequential read' ela= 11 file#=15 block#=5593539 blocks=1 obj#=352194 tim=45021040872
WAIT #139891129837744: nam='db file sequential read' ela= 10 file#=15 block#=5593555 blocks=1 obj#=352194 tim=45021041034
WAIT #139891129837744: nam='db file sequential read' ela= 10 file#=15 block#=5593571 blocks=1 obj#=352194 tim=45021041198
WAIT #139891129837744: nam='db file sequential read' ela= 10 file#=15 block#=5593587 blocks=1 obj#=352194 tim=45021041350
WAIT #139891129837744: nam='db file sequential read' ela= 11 file#=15 block#=5593603 blocks=1 obj#=352194 tim=45021041498
WAIT #139891129837744: nam='db file sequential read' ela= 10 file#=15 block#=5593619 blocks=1 obj#=352194 tim=45021041661
WAIT #139891129837744: nam='db file sequential read' ela= 11 file#=15 block#=5593635 blocks=1 obj#=352194 tim=45021041813
WAIT #139891129837744: nam='db file sequential read' ela= 26 file#=15 block#=5593651 blocks=1 obj#=352194 tim=45021041980
WAIT #139891129837744: nam='db file sequential read' ela= 10 file#=15 block#=5593667 blocks=1 obj#=352194 tim=45021042177
…略…
WAIT #139891129837744: nam='db file sequential read' ela= 1007 file#=15 block#=5593882 blocks=1 obj#=352194 tim=45021070164
WAIT #139891129837744: nam='db file sequential read' ela= 1437 file#=15 block#=5593898 blocks=1 obj#=352194 tim=45021071788
WAIT #139891129837744: nam='db file sequential read' ela= 1158 file#=15 block#=5593914 blocks=1 obj#=352194 tim=45021073104
WAIT #139891129837744: nam='db file sequential read' ela= 1040 file#=15 block#=5593930 blocks=1 obj#=352194 tim=45021074307
WAIT #139891129837744: nam='db file sequential read' ela= 958 file#=15 block#=5593946 blocks=1 obj#=352194 tim=45021075424
WAIT #139891129837744: nam='db file sequential read' ela= 1145 file#=15 block#=5593962 blocks=1 obj#=352194 tim=45021076743
WAIT #139891129837744: nam='db file sequential read' ela= 997 file#=15 block#=5593978 blocks=1 obj#=352194 tim=45021077917
WAIT #139891129837744: nam='db file sequential read' ela= 1011 file#=15 block#=5593994 blocks=1 obj#=352194 tim=45021079129
WAIT #139891129837744: nam='db file sequential read' ela= 898 file#=15 block#=5594010 blocks=1 obj#=352194 tim=45021080218
WAIT #139891129837744: nam='db file sequential read' ela= 1450 file#=15 block#=5594026 blocks=1 obj#=352194 tim=45021081838
WAIT #139891129837744: nam='db file sequential read' ela= 1266 file#=15 block#=5594042 blocks=1 obj#=352194 tim=45021083270
…略…
WAIT #139891129837744: nam='db file sequential read' ela= 11 file#=15 block#=5593867 blocks=1 obj#=352194 tim=45021088206
WAIT #139891129837744: nam='db file sequential read' ela= 11 file#=15 block#=5593883 blocks=1 obj#=352194 tim=45021088362
WAIT #139891129837744: nam='db file sequential read' ela= 10 file#=15 block#=5593899 blocks=1 obj#=352194 tim=45021088494
WAIT #139891129837744: nam='db file sequential read' ela= 10 file#=15 block#=5593915 blocks=1 obj#=352194 tim=45021088628
WAIT #139891129837744: nam='db file sequential read' ela= 10 file#=15 block#=5593931 blocks=1 obj#=352194 tim=45021088764
WAIT #139891129837744: nam='db file sequential read' ela= 9 file#=15 block#=5593947 blocks=1 obj#=352194 tim=45021088899
WAIT #139891129837744: nam='db file sequential read' ela= 10 file#=15 block#=5593963 blocks=1 obj#=352194 tim=45021089031
WAIT #139891129837744: nam='db file sequential read' ela= 11 file#=15 block#=5593979 blocks=1 obj#=352194 tim=45021089205
WAIT #139891129837744: nam='db file sequential read' ela= 10 file#=15 block#=5593995 blocks=1 obj#=352194 tim=45021089339
WAIT #139891129837744: nam='db file sequential read' ela= 10 file#=15 block#=5594011 blocks=1 obj#=352194 tim=45021089485
…略…
WAIT #139891129837744: nam='db file sequential read' ela= 1412 file#=15 block#=5597225 blocks=1 obj#=352194 tim=45021203277
WAIT #139891129837744: nam='db file sequential read' ela= 1238 file#=15 block#=5597240 blocks=1 obj#=352194 tim=45021204680
WAIT #139891129837744: nam='db file sequential read' ela= 1027 file#=15 block#=5597255 blocks=1 obj#=352194 tim=45021205889
WAIT #139891129837744: nam='db file sequential read' ela= 1084 file#=15 block#=5597270 blocks=1 obj#=352194 tim=45021207169
WAIT #139891129837744: nam='db file sequential read' ela= 1263 file#=15 block#=5597285 blocks=1 obj#=352194 tim=45021208594
WAIT #139891129837744: nam='db file sequential read' ela= 1265 file#=15 block#=5597300 blocks=1 obj#=352194 tim=45021210019
…略…
-----------------------------------------------
通过下面的原始 Trace, 咱们能够看到分区前的“db file sequential read”都是比拟均匀的 10 几个微秒,而分区后则呈现间歇性的高达数千微秒的长待机。
对于具体的起因,当初还在考察,先说说我的几个猜想吧。
1. 拜访对象数据块的地位和随机 I / O 的影响。表被分区后,索引的“CLUSTERING_FACTOR”受到分区 Key 的影响,聚簇状况发生变化。2. 单纯的 I / O 性能的变动影响。
等调查结果进去后我再更新。
正文完