Reading AWR reports: case study

In my previous post I described some sections that are typically useful when interpreting AWR data. However, sometimes the answer comes from an unexpected source. For example, the workload profile section of the report contains key information for understanding what the database looks like, but it seldom gives a direct answer to the problem (except for maybe excessive parsing and excessive commits). But recently I came across a case when this section was enough to identify the root cause of a non-trivial issue:

               Per Second   Per Transaction
Redo size:     1,895,241.12 12,004.40
Logical reads: 832,945.54   5,275.85
Block changes: 11,937.82    75.61
Physical reads: 7,458.75    47.24
Physical writes: 759.33     4.81
User calls:      449.83     2.85
Parses:          225.18     1.43
Hard parses:      15.90     0.10
Sorts:           467.90     2.96
Logons:            1.38     0.01
Executes:    103,266.84     654.09
Transactions:    157.88

This excerpt was coming from an AWR report for a database that virtually froze with 100% CPU consumption on the box. The question was what causing this high CPU consumption (the SAs ruled out possibility of blaming other processes on the box).

When looking carefully at the numbers above, one could notice that executes per second looks enormous. This becomes even more apparent when looking at the rate of user calls, which is a few orders of magnitude lower. These numbers, combined with high CPU usage, are enough to suspect context switching as the primary suspect: a SQL statement containing a PL/SQL function, which executes a SQL statement hundreds of thousands of time per function call.

Further investigation confirmed that it was indeed the case. There was a stats job running shortly before the incident, leading to invalidation of the SQL plan, and the new plan was calling the PL/SQL function at an early stage, before most rows were eliminated.

The point I am trying to make is that one should try to maintain a good balance between focusing on just few key performance indicators, and paying attention to secondary details as well.

Other posts on AWR

16 thoughts on “Reading AWR reports: case study

  1. Very Nice… Unfortunately,my job is to analyze AWR before the problem arises and take some proactive measures to prevent the problem to occur. I have couple of questions regarding interpreting AWR. Hope you don’t mind if i ask you?

      1. Hi Nikolay

        Can you explain..:

        1)DB CPU
        2)CPU TIME
        3)CPU used by this session

        If I have a 30 min awr report, how should i deduce how much CPU does oracle took during these 20 mins?


    1. Hi Yasir,

      thanks for an excellent question. It calls for a full-size blog post with some examples, but I only have time to answer it briefly.

      The meaning of all these metrics is essentially the same (CPU time by all user calls, i.e. except background sessions), and it should be assessed versus (elapsed time) x (number of CPUs). Differences in these values have to do with how they are calculated and how frequently they are updated (e.g. see

      In order to understand database CPU usage it is also helpful to look at CPU consumption on the OS level (can be calculated from OS statistics section as BUSY_TIME/(BUSY_TIME+IDLE_TIME).

      Another quantity that is useful for troubleshooting CPU problems is time wait to get CPU, but it’s not readily available (there are wait to estimate it from ASH, e.g.

      Best regards,

      PS. I’ve added “ask me a question” page so that in the future one could ask questions which aren’t related directly to any post, feel free to use it :)

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        1. I forgot to mention that there is an option to subscribe for updates for this blog — that way you can be sure that you won’t miss anything interesting :)

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  3. Excellent Info Savvinov!! Really glad to be in a place to know and learn so much. Thanks again and keep Blogging!! :-)


  4. Savvinov its really tough to find such good material on AWR on google. Thanks for your blog really helpful.


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