oracle IO性能分析

拼搏现实的明天。 2022-02-14 16:27 442阅读 0赞

我们在IO问题发生时间段：  
1，可以查dba\_hist\_system\_event 来看该IO相关等待时间的平均响应时间的变化趋势，  
2，直接查dba\_hist\_event\_histogram或者sys.WRH$\_EVENT\_HISTOGRAM ， 来看该IO相关等待事件的等待时间直方图分布。  
3， 我们也可以从整体数据库的IO变化量上（dba\_hist\_sysstat）， 看出问题时段的总体IO量， 比正常时候的IO量到底是否有增加。  
4， 我们也可以从某个IO function 即某个进程上面（dba\_hist\_iostat\_function），看问题时间段某个进程的IO request次数、IO 的量。  
比如说LGWR进程的写request次数、 写的量。

说明：  
1， 如上视图均可关联dba\_hist\_snapshot  
2， 所有dba\_hist 相关视图都是由对应的v$ 动态性能视图汇聚而来， 当时的数据可以查对应的v$视图。  
福利： 后附sql。

例2：  
直方图分布可能更加精确， 因为查看平均响应时间可能会因为粒度太粗、时间跨度长而被平均了。  
正常情况下，应该<8ms的占据了90%甚至更多， > 32ms 的应该占比接近为0。  
可以看到， 昨天smscp异常时候，在16 – 32 ms 之间的已经占比很多了。

END_INTERVAL_TIME    SNAP_ID    TIME_HISTG    TOTAL_WAIT    PER_OF_WAITS

1 22-10月-14 03.00.49.801 下午 20536 <1ms 89464 0.71  
2 22-10月-14 03.00.49.801 下午 20536 <2ms 89464 11.32  
3 22-10月-14 03.00.49.801 下午 20536 <4ms 89464 26.39  
4 22-10月-14 03.00.49.801 下午 20536 <8ms 89464 18.28  
5 22-10月-14 03.00.49.801 下午 20536 <16ms 89464 13.16  
6 22-10月-14 03.00.49.801 下午 20536 <32ms 89464 8.21  
7 22-10月-14 03.00.49.801 下午 20536 <64ms 89464 7.56  
8 22-10月-14 03.00.49.801 下午 20536 <128ms 89464 6.06  
9 22-10月-14 03.00.49.801 下午 20536 <256ms 89464 4.72  
10 22-10月-14 03.00.49.801 下午 20536 <512ms 89464 2.72  
11 22-10月-14 03.00.49.801 下午 20536 <1s 89464 0.83  
12 22-10月-14 03.00.49.801 下午 20536 <2s 89464 0.03  
13 22-10月-14 03.00.49.801 下午 20536 <4s 89464 0  
14 22-10月-14 03.00.49.801 下午 20536 >=4s 89464 0

正常情况下是这样的，8ms以上的占比很少：

END_INTERVAL_TIME    SNAP_ID    TIME_HISTG    TOTAL_WAIT    PER_OF_WAITS

1 22-10月-14 07.00.49.701 下午 20540 <1ms 1091640 38.28  
2 22-10月-14 07.00.49.701 下午 20540 <2ms 1091640 51.09  
3 22-10月-14 07.00.49.701 下午 20540 <4ms 1091640 9.03  
4 22-10月-14 07.00.49.701 下午 20540 <8ms 1091640 1.37  
5 22-10月-14 07.00.49.701 下午 20540 <16ms 1091640 0.17  
6 22-10月-14 07.00.49.701 下午 20540 <32ms 1091640 0.04  
7 22-10月-14 07.00.49.701 下午 20540 <64ms 1091640 0.01  
8 22-10月-14 07.00.49.701 下午 20540 <128ms 1091640 0  
9 22-10月-14 07.00.49.701 下午 20540 <256ms 1091640 0  
10 22-10月-14 07.00.49.701 下午 20540 <512ms 1091640 0  
11 22-10月-14 07.00.49.701 下午 20540 <1s 1091640 0  
12 22-10月-14 07.00.49.701 下午 20540 <2s 1091640 0  
13 22-10月-14 07.00.49.701 下午 20540 <4s 1091640 0  
14 22-10月-14 07.00.49.701 下午 20540 >=4s 1091640 0

例3：  
可以看到昨天下午的整库的physical read total IO requests 并没有明显增加， 但是physical read total bytes 增加到了3000GB 一个小时。  
其它时候也有这么高的，但是都是在晚上， 只有昨天是在下午15点这个生产时间的snapshot，开发有大量direct path read 所以对应用产生了较大影响。

例4：可以看到问题发生时段，10.22 14点-15点， LGWR的large\_write\_megabytes 和requests有明显增加， 而 平时有如此高峰的是有晚上和凌晨。  
Smll read 的bytes和request 都没有增加。

附sql：  
\--- 查等待事件的等待时间直方图分布：  
select b.end\_interval\_time,a.\*  
from  
(select snap\_id,

decode(wait_time_milli,
              1,
              '<1ms',
              2,
              '<2ms',
              4,
              '<4ms',
              8,
             '<8ms',
             16,
             '<16ms',
             32,
             '<32ms',
             64,
             '<64ms',
             128,
             '<128ms',
             256,
             '<256ms',
             512,
             '<512ms',
             1024,
             '<1s',
             2048,
             '<2s',
             4096,
             '<4s',
             8192,
             '>=4s',
             wait_time_milli) time_histg,
      total_wait,
      round(delta_wait_count / total_wait * 100, 2) as per_of_waits

from (select snap\_id,

wait_time_milli,
              delta_wait_count,
              sum(delta_wait_count) over(partition by snap_id order by snap_id) as total_wait
         from (select xx.snap_id,
                      xx.wait_time_milli,
                      xx.wait_count - yy.wait_count as delta_wait_count
                 from dba_hist_event_histogram xx,
                      dba_hist_event_histogram yy
                where xx.event_name = 'log file parallel write'
                  and xx.event_id = yy.event_id
                  and xx.snap_id = yy.snap_id + 1
                  and xx.instance_number = yy.instance_number
                  and xx.wait_time_milli = yy.wait_time_milli
                  and xx.snap_id in (20540)))

order by snap\_id, wait\_time\_milli) a , dba\_hist\_snapshot b  
where a.snap\_id=b.snap\_id;

\--- 查等待事件的平均等待时间的变化趋势：  
with t as (  
select s.snap\_id, s.instance\_number, s.end\_interval\_time ,

total_waits - lag(total_waits, 1) over (partition by s.instance_number order by s.snap_id) waits,
         (time_waited_micro - lag(time_waited_micro, 1) over (partition by s.instance_number order by s.snap_id))/1000 twt
    from dba_hist_system_event ev, dba_hist_snapshot s

where ev.instance\_number = s.instance\_number and ev.snap\_id = s.snap\_id

and event_name = 'log file parallel write'
     and s.end_interval_time BETWEEN TO_DATE('20140401 10:00:00', 'yyyymmdd hh24:mi:ss') AND  TO_DATE('20140414 11:00:00', 'yyyymmdd hh24:mi:ss') )

select to\_char(end\_interval\_time,'YYYYMMDD HH24:MI'), instance\_number, sum(waits), sum(twt), round(sum(twt)/sum(waits), 2) wt  
from t  
where (to\_char(end\_interval\_time, 'hh24') between 9 and 12 or to\_char(end\_interval\_time, 'hh24') between 14 and 17)  
group by to\_char(end\_interval\_time,'YYYYMMDD HH24:MI'), instance\_number  
order by 1, instance\_number;

\--- 查整库IO相关指标：

\--get\_stat\_10g.sql  
with s as (  
select sn.instance\_number, sn.snap\_id, sn.end\_interval\_time stime, (s.value - lag(s.value, 1) over (partition by sn.instance\_number order by sn.snap\_id)) value  
\--(sn.end\_interval\_time - lag(sn.end\_interval\_time, 1) over (order by sn.snap\_id))*24*60\*60 elap\_time,  
\--round((s.value - lag(s.value, 1) over (order by sn.snap\_id))/((sn.end\_interval\_time - lag(sn.end\_interval\_time, 1) over (order by sn.snap\_id))*24*60\*60)) value\_s  
from dba\_hist\_snapshot sn, dba\_hist\_sysstat s  
where s.snap\_id = sn.snap\_id and s.stat\_name = '&1' and s.instance\_number = sn.instance\_number  
)  
select instance\_number , snap\_id, stime, value ,  
rank() over (partition by instance\_number order by value desc) ranking, min(value) over (partition by instance\_number) min\_phy,  
max(value) over (partition by instance\_number) max\_phy, round(avg(value) over (partition by instance\_number)) avg\_phy  
from s  
where (to\_char(stime, 'hh24') between 9 and 12 or to\_char(stime, 'hh24') between 14 and 17)  
and to\_char(stime, 'D') not in ('1', '7')  
and stime between to\_date(&2, 'yyyymmdd') and to\_date(&3, 'yyyymmdd')  
order by instance\_number, snap\_id  
/

\---eg: @get\_stat\_10g.sql 'parse count (hard)' 20100716 20100726

\---physical read total IO requests  
\---physical read total bytes  
\---physical write total IO requests  
\---physical write total bytes  
\---以上四个指标即IOPS（requests）、IO吞吐量（bytes）

\--- 查整库IO相关指标2：

select e.snap\_id,

to_char(e.startup_time, 'yyyy-mm-dd hh24:mi:ss') instance_startup_time,
       to_char(e.end_interval_time, 'yyyy-mm-dd hh24:mi:ss') snapshot_end_time,
       b.value - a.value IO_requests,
       round((d.value - c.value)/1024/1024/1024) IO_GB

from dba\_hist\_sysstat a,

dba_hist_sysstat  b,
       dba_hist_sysstat  c,
       dba_hist_sysstat  d,
       dba_hist_snapshot e

where a.stat\_name = 'physical read total IO requests'  
and b.stat\_name = 'physical read total IO requests'  
and c.stat\_name = 'physical read total bytes'  
and d.stat\_name = 'physical read total bytes'  
and a.snap\_id = e.snap\_id - 1  
and b.snap\_id = e.snap\_id  
and c.snap\_id = e.snap\_id - 1  
and d.snap\_id = e.snap\_id  
and e.end\_interval\_time BETWEEN

TO_DATE('20141021 09:00:00', 'yyyymmdd hh24:mi:ss') AND
       TO_DATE('20141023 18:00:00', 'yyyymmdd hh24:mi:ss')

order by e.begin\_interval\_time;

\--- 查某个IO 进程的读写指标， 例如LGWR：

SQL> select \* from dba\_hist\_iostat\_function\_name;

DBID FUNCTION_ID FUNCTION_NAME

\---------- ----------- ------------------------------  
1154030563 0 RMAN  
1154030563 1 DBWR  
1154030563 2 LGWR  
1154030563 3 ARCH  
1154030563 4 XDB  
1154030563 5 Streams AQ  
1154030563 6 Data Pump  
1154030563 7 Recovery  
1154030563 8 Buffer Cache Reads  
1154030563 9 Direct Reads  
1154030563 10 Direct Writes  
1154030563 11 Smart Scan  
1154030563 12 Archive Manager  
1154030563 13 Others

14 rows selected

SQL>

\--- 查某个IO进程例如LGWR的IO requset和IO bytes dba\_hist\_iostat\_function：

select e.snap\_id,

to_char(e.end_interval_time, 'yyyy-mm-dd hh24:mi:ss') snapshot_end_time,
       b.SMALL_READ_MEGABYTES  - a.SMALL_READ_MEGABYTES     SMALL_READ_MEGABYTES   ,                                                                                                
       b.SMALL_WRITE_MEGABYTES - a.SMALL_WRITE_MEGABYTES    SMALL_WRITE_MEGABYTES  ,                                                                                              
       b.LARGE_READ_MEGABYTES  - a.LARGE_READ_MEGABYTES     LARGE_READ_MEGABYTES   ,                                                                                             
       b.LARGE_WRITE_MEGABYTES - a.LARGE_WRITE_MEGABYTES    LARGE_WRITE_MEGABYTES  ,                                                                                            
       b.SMALL_READ_REQS       - a.SMALL_READ_REQS          SMALL_READ_REQS        ,                                                                                           
       b.SMALL_WRITE_REQS      - a.SMALL_WRITE_REQS         SMALL_WRITE_REQS       ,                                                                                          
       b.LARGE_READ_REQS       - a.LARGE_READ_REQS          LARGE_READ_REQS        ,                                                                                         
       b.LARGE_WRITE_REQS      - a.LARGE_WRITE_REQS         LARGE_WRITE_REQS       ,                                                                                        
       b.NUMBER_OF_WAITS       - a.NUMBER_OF_WAITS          NUMBER_OF_WAITS        ,                                                                                       
       b.WAIT_TIME             - a.WAIT_TIME                WAIT_TIME

from dba\_hist\_iostat\_function a,

dba_hist_iostat_function  b,
       dba_hist_snapshot e

where a.FUNCTION\_NAME = 'LGWR'  
and b.FUNCTION\_NAME = 'LGWR'  
and a.snap\_id = e.snap\_id - 1  
and b.snap\_id = e.snap\_id  
and e.end\_interval\_time BETWEEN

TO_DATE('20141021 09:00:00', 'yyyymmdd hh24:mi:ss') AND
       TO_DATE('20141023 18:00:00', 'yyyymmdd hh24:mi:ss')

order by e.begin\_interval\_time;