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5#
发表于 2012-5-22 10:51:44
Linux x86 64-bit + 11.1.0.7.0 RAC=NO
Logical reads: 526,850.6 732,606.6 每秒逻辑读 4116 MB
Host CPU (CPUs: 16 Cores: 16 Sockets: 4) 16core
Event Waits Time(s) Avg wait (ms) % DB time Wait Class
DB CPU 44,665 89.28
db file sequential read 4,113,358 5,156 1 10.31 User I/O
TOP 5中 DB CPU 占了大头
CPU Time (s) Elapsed Time (s) Executions CPU per Exec (s) % Total % Total DB Time SQL Id SQL Module SQL Text
5,848 5,932 2 2924.04 11.45 11.31 4w3hv8m3t8n4x JDBC Thin Client merge into INDICATOR_20398_1 t...
5,842 5,927 2 2921.07 11.43 11.30 a2zkkyuwt6p5v JDBC Thin Client merge into INDICATOR_20404_1 t...
5,576 5,658 2 2788.16 10.91 10.79 27wq448z9ndrg JDBC Thin Client merge into INDICATOR_20424_1 t...
5,567 5,646 2 2783.34 10.90 10.76 77bp0shay1kaj JDBC Thin Client merge into INDICATOR_20417_1 t...
5,479 5,592 2 2739.57 10.72 10.66 fk7x594y5w5vj JDBC Thin Client merge into INDICATOR_20394_1 t...
4,897 5,177 1 4896.69 9.58 9.87 d0cjz4k9v95m3 JDBC Thin Client merge into INDICATOR_20408_1 t...
1,582 1,583 120 13.18 3.10 3.02 dn07zhxsf7wbm JDBC Thin Client select indicatorid, sourcemot...
Buffer Gets Executions Gets per Exec %Total CPU Time (s) Elapsed Time (s) SQL Id SQL Module SQL Text
429,466,232 2 214,733,116.00 11.40 5848.08 5932.42 4w3hv8m3t8n4x JDBC Thin Client merge into INDICATOR_20398_1 t...
429,464,270 2 214,732,135.00 11.40 5842.15 5926.98 a2zkkyuwt6p5v JDBC Thin Client merge into INDICATOR_20404_1 t...
412,473,134 2 206,236,567.00 10.95 5576.31 5657.84 27wq448z9ndrg JDBC Thin Client merge into INDICATOR_20424_1 t...
412,203,228 2 206,101,614.00 10.94 5566.67 5645.51 77bp0shay1kaj JDBC Thin Client merge into INDICATOR_20417_1 t...
401,970,344 2 200,985,172.00 10.67 5479.14 5592.45 fk7x594y5w5vj JDBC Thin Client merge into INDICATOR_20394_1 t...
349,568,508 1 349,568,508.00 9.28 4896.69 5176.81 d0cjz4k9v95m3 JDBC Thin Client merge into INDICATOR_20408_1 t...
消耗 大量 buffer gets的语句 对应于 消耗大量cpu time的语句, 都是只 执行2次的 merge select * 语句 ,这些语句 耗费大量的逻辑读 单次达到214,733,116 , 建议你考虑调优SQL 减少逻辑读 。
或者你希望通过增加cpu负载来加速merge的话 , 考虑使用并行查询。 |
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