Oracle memory troubleshooting article

Randolf Geist has written a good article about systematic troubleshooting of a PL/SQL memory allocation & CPU utilization problem – and he has used some of my tools too!

http://oracle-randolf.blogspot.com/2010/05/advanced-oracle-troubleshooting-session.html

cursor: pin S waits, sporadic CPU spikes and systematic troubleshooting

I recently consulted one big telecom and helped to solve their sporadic performance problem which had troubled them for some months. It was an interesting case as it happened in the Oracle / OS touchpoint and it was a product of multiple “root causes”, not just one, an early Oracle mutex design bug and a Unix scheduling issue – that’s why it had been hard to resolve earlier despite multiple SRs opened etc.

Martin Meyer, their lead DBA, posted some info about the problem and technical details, so before going on, you should read his blog entry and read my comments below after this:

Problem:

So, the problem was, that occasionally the critical application transactions which should have taken very short time in the database (<1s), took 10-15 seconds or even longer and timed out.

Symptoms:

  1. When the problem happened, the CPU usage also jumped up to 100% for the problem duration (from few tens of seconds up to few minutes).
  2. In AWR snapshots (taken every 20 minutes), the “cursor: pin S” popped into top TOP5 waits (around 5-10% of total instance wait time) and sometimes also “cursor: pin S wait on X” which is a different thing, also “latch: library cache” and interestingly “log file sync”. These waits had then much higher average wait times per wait occurrence than normal (tens or hundreds of milliseconds per wait, on average).
  3. The V$EVENT_HISTOGRAM view showed lots of cursor: pin S waits taking very long time (over a second, some even 30+ seconds) and this certainly isn’t normal (Martin has these numbers in his blog entry)

AWR and OS CPU usage measurement tools are system-wide tools (as opposed to session-wide tools).

Troubleshooting:

I can’t give you exact numbers or AWR data here, but will explain the flow of troubleshooting and reasoning.

  • As the symptoms involved CPU usage spikes, I first checked whether there were perhaps logon storms going on due a bad application server configuration, where the app server suddenly decides to fire up hundreds of more connections at the same time (that happens quite often, so it’s a usual suspect when troubleshooting such issues). A logon storm can consume lots of CPU as all these new processes need to be started up in OS, they attach to SGA (syscalls, memory pagetable set-up operations) and eventually they need to find & allocate memory from shared pool and initialize session structures. This all takes CPU.However the logons cumulative statistic in AWR didn’t go up almost at all during the 20 minute snapshot, so that ruled out a logon storm. As the number of sessions in the end of AWR snapshot (compared to the beginning of it) did not go down, this ruled out a logoff storm too (which also consumes CPU as now the exiting processes need to release their resources etc).
  • It’s worth mentioning that log file sync waits also went up by over an order of magnitude (IIRC from 1-2ms to 20-60 ms per wait) during the CPU spikes. However as log file parallel write times didn’t go up so radically, this indicated that the log file sync wait time was wasted somewhere else too – which is very likely going to be CPU scheduling latency (waiting on the CPU runqueue) when CPUs are busy.
  • As one of the waits which popped up during the problem was cursor: pin S, then I chcecked V$MUTEX_SLEEP_HISTORY and it did not show any specific cursor as a significant contention point (all contention recorded in that sleep history buffer was evenly spread across many different cursors), so that indicated to me that the problem was likely not related to a single cursor related issue (a bug or just too heavy usage of that cursor). Note that this view was not queried during the worst problem time, so there was a chance that some symptoms were not in there anymore (V$MUTEX_SLEEP_HISTORY is a circular buffer of few hundred last mutex sleeps).
  • So, we had CPU starvation and very long cursor: pin S waits popping up at the same time. cursor: pin S operation should happen really fast as it’s a very simple operation (few tens of instructions only) of marking the cursor’s mutex in-flux so its reference count could be bumped up for a shared mutex get.
  • Whenever you see CPU starvation (CPUs 100% busy and runqueues are long) and latch or mutex contention, then the CPU starvation should be resolved first, as the contention may just be a symptom of the CPU starvation. The problem is that if you get unlucky and a latch or mutex holder process is preempted and taken off CPU by the scheduler, the latch/mutex holder can’t release the latch before it gets back onto CPU to complete its operation! But OS doesn’t have a clue about this, as latches/mutexes are just Oracle’s memory structures in SGA. So the latch/mutex holder is off CPU and everyone else who gets onto CPU may want to take the same latch/mutex. They can’t get it and spin shortly in hope that the holder releases it in next few microseconds, which isn’t gonna happen in this case, as the latch/mutex holder is still off CPU!
  • And now comes a big difference between latches and mutexes in Oracle 10.2: When a latch getter can’t get the latch after spinning, it will go to sleep to release the CPU. Even if there are many latch getters in the CPU runqueue before the latch holder, they all spin quickly and end up sleeping again. But when a mutex getter doesn’t get the mutex after spinning, it will not go to sleep!!! It will yield() the CPU instead, which means that it will go to the end of runqueue and try to get back onto CPU as soon as possible. So, mutex getters in 10.2 are much less graceful, they can burn a lot of CPU when the mutex they want is held by someone else for long time.
  • But so what, if a mutex holder is preempted and taken off CPU by OS scheduler – it should get back onto CPU pretty fast, once it works its way through the CPU runqueue?
  • Well, yes IF all the processes in the system have the same priority.
  • This is where a second problem comes into play – Unix process priority decay. When a process eats a lot of CPU (and does little IO / voluntary sleeping) then the OS lowers that processes CPU scheduling priority so that other, less CPU hungry processes would still get their fair share of CPU (especially when coming back from an IO wait for example etc).
  • When a mutex holder has a lower priority than most other processes and is now taken off CPU, a thing called priority inversion happens. Even though other processes do have higher priority, they can not proceed, as the critical lock or resource they need, is already held by the other process with a lower priority who can’t complete its work as the “high priority” processes keep the CPUs busy.
  • In case of latches, the problem is not that bad as the latch getters go to sleep until they are posted when the latch is released by the holder process (I’ve written about it here). But the priority inversion takes a crazy turn in case of mutexes – as their getters don’t sleep (not even for a short time) by default, but yield the CPU and try to get back to it immediately and so on until they get the mutex. That can lead to huge CPU runqueue spikes, unresponsive systems and even hangs.
  • This is why starting from Oracle 11g the mutex getters do sleep instead of just yielding the CPU and also Oracle has backported the fix into Oracle 10.2.0.4, where a patch must be applied and where the _first_spare_parameter will specify the sleep duration in centiseconds.
  • So, knowing how mutexes worked in 10.2, all the symptoms led me to suspect this priority inversion problem, greatly amplified by how the mutex getters do never sleep by default. And we checked the effective priorities of all Oracle processes in the server, and we hit the jackpot – there was a number of processes with significantly lower priorities than all other processes had. And it takes only one process with low priority to cause all this trouble, just wait until it starts modifying a mutex and is preempted while doing this.
  • So, in order to fix both of the problems which amplified each other, we had to enable HPUX_SCHED_NOAGE Oracle parameter, to prevent priority decay of the processes and set the _first_spare_parameter to 10, which meant that default mutex sleep time will be 10 centiseconds (which is pretty long time in mutex/latching world, but better than crazily retrying without any sleeping at all). That way no process (the mutex holder) is pushed back and kept away from CPU for long periods of time.

This was not a trivial problem, as it happened in Oracle / OS touchpoint and happened not because a single reason, but as a product of multiple separate reasons, amplifying each other.

There are few interesting, non-technical points here:

  1. When troubleshooting, don’t let performance tools like AWR (or any other tool!) tell you what your problem is! Your business, your users should tell you what the problem is and the tools should only be used for symptom drilldown (This is what Cary Millsap has been constantly telling us). Note how I mentioned the problem and symptoms separately in the beginning of my post – and the problem was that some business transactions (systemwide) timed out because the database response time was 5-15 seconds!
  2. The detail and scope of your performance data must have at least as good detail and scope of your performance problem!
    In other words, if your problem is measured in few seconds, then your performance data should also be sampled at least every few seconds in order to be fully systematic.The classic issue in this case was that the 20 minute AWR reports still showed IO wait times as main DB time consumers, but that was averaged over 20 minutes. But our problem happened severely and shortly within few seconds in that 20 minutes, so the averaging and aggregation over long period of time did hide the extreme performance issue that happened in a very short time.

Next time when it seems to be impossible to diagnose a problem and if the troubleshooting effort ends up going in circles, then you should ask, “what’s the real problem and who and how is experiencing it” and see if your performance data’s detail and scope matches that problem!

Oh, this is a good point to mention that in addition to my Advanced Oracle Troubleshooting/SQL Tuning seminars I also actually perform advanced Oracle troubleshooting consulting too! I eat mutexes for breakfast ;-)

Update: Srivenu Kadiyala has experienced the same problem and has written about it here.

 

Non-trivial performance problems

Gwen Shapira has written an article about a good example of a non-trivial performance problem.

I’m not talking about anything advanced here (such as bugs or problems arising at OS/Oracle touchpoint) but that sometimes the root cause of a problem (or at least the reason why you notice this problem now) is not something deeply technical or related to some specific SQL optimizer feature or a configuration issue. Instead of focusing on the first symptom you see immediately, it pays off to take a step back and see how the problem task/application/SQL is actually used by the users or client applications.

In other words, talk to the users, ask how exactly they experience the problem and then drill down from there.

Oracle Latch Contention Troubleshooting

I wrote a latch contention troubleshooting article for IOUG Select journal last year (it was published earlier this year). I have uploaded this to tech.E2SN too, I recommend you to read it if you want to become systematic about latch contention troubleshooting:

http://tech.e2sn.com/oracle/troubleshooting

I’m working on getting the commenting & feedback work at tech.E2SN site too, but for now you can comment here at this blog entry…

Oracle Session Snapper v3.10

Hi all, long time no see!  =8-)

Now as I’m done with the awesome Hotsos Symposium (and the training day which I delivered) and have got some rest, I’ll start publishing some of the cool things I’ve been working on over the past half a year or so.

The first is Oracle Session Snapper version 3!

There are some major improvements in Snapper 3, like ASH style session activity sampling!

When you troubleshoot a session’s performance (or instance performance) then the main things you want to know first are very very simple:

  1. Which SQL statements are being executed
  2. What are they doing, are they working on CPU or waiting.
  3. If waiting, then for what

Often this is enough for troubleshooting what’s wrong. For example, if a session is waiting for a lock, then wait interface will show you that. If a single SQL statement is taking 99% of total response time, the V$SESSION (ASH style) samples will point out the problem SQL and so on. Simple stuff.

However there are cases where you need to go beyond wait interface and use V$SESSTAT (and other) counters and even take a “screwdriver” and open Oracle up from outside by stack tracing :-)

When I wrote the first version of Snapper for my own use some 4-5 years ago I wrote it mainly having the “beyond wait interface” part in mind. So I focused on V$SESSTAT and various other counters and left the basic troubleshooting to other tools. I used to manually sample V$SESSION/V$SESSION_WAIT a few times in a row to get a rough overview of what a session was doing or some other special-purpose scripts.

However after Snapper got more popular and I started getting some feedback about it I saw the need for covering more with Snapper, not just the “beyond wait interface” part, but also the “wait interface” and “which SQL” part too.

So, now I’m presenting Snapper v3 which does all the 3 points above using ASH style V$SESSION sampling and it still has the first step to “beyond wait interface” part in it, which is very useful for advanced performance troubleshooting and diagnosis – I’m talking about the V$SESSTAT counters above.

I’ve made some syntax changes in Snapper too and right now the v3 doesn’t work on Oracle 9.2 (it will work some day :)

To give you an idea of the new ASH style sampling capabilities, heres some example output:

SQL> @snapper ash=sid+event+wait_class,ash1=plsql_object_id+plsql_subprogram_id+sql_id,ash2=program+module+action 5 1 all
Sampling...
-- Session Snapper v3.10 by Tanel Poder @ E2SN ( http://tech.e2sn.com ) --------------------------------------------------------------
Active% |    SID | EVENT                     | WAIT_CLASS
-------------------------------------------------------------- 100% |    133 | db file scattered read    | User I/O 5% |    165 | control file parallel wri | System I/O 2% |    162 | ON CPU                    | ON CPU 2% |    167 | db file parallel write    | System I/O 2% |    166 | log file parallel write   | System I/O
--------------------------------------------------- Active% | PLSQL_OBJE | PLSQL_SUBP | SQL_ID --------------------------------------------------- 77% |            |            | a5xyjp9gt796s 23% |            |            | 4g4u44bk830ms 12% |            |            |
------------------------------------------------------------------------------------------- Active% | PROGRAM                   | MODULE                    | ACTION ------------------------------------------------------------------------------------------- 100% | sqlplus@mac01 (TNS V1-V3) | sqlplus@mac01 (TNS V1-V3) | 5% | oracle@solaris02 (CKPT)   |                           | 2% | oracle@solaris02 (DBW0)   |                           | 2% | oracle@solaris02 (CJQ0)   |                           | 2% | oracle@solaris02 (LGWR)   |                           | --  End of ASH snap 1, end=2010-03-22 17:35:06, seconds=5, samples_taken=43

You can read some usage examples and download it here:

P.S. People who attended Hotsos Symposium Training Day where I demoed the initial version of Snapper v3 – download the new version from above link (v3.10), it’s much more flexible than the one I demoed couple of weeks ago!


New versions of LatchProf and LatchProfX for latch contention troubleshooting and tuning

The LatchProf and LatchProfX scripts allow you to be more systematic with latch contention troubleshooting and tuning. No more guesswork is needed as these scripts give you exact session IDs and in this version also SQLIDs of the troublemaking applications.

You can download the new versions here:

Example output (with SQLID info) is below:

SQL> @latchprof name,sid,sqlid % % 100000

-- LatchProf 1.21 by Tanel Poder ( http://www.tanelpoder.com )

NAME                                       SID SQLID               Held       Gets  Held %     Held ms Avg hold ms
----------------------------------- ---------- ------------- ---------- ---------- ------- ----------- -----------
cache buffers chains                       133 3jbwa65aqmkvm        349        348     .35      14.169        .041
simulator lru latch                        133 3jbwa65aqmkvm         51         51     .05       2.071        .041
row cache objects                          133 3jbwa65aqmkvm          5          5     .01        .203        .041
cache buffers chains                        24                        5          5     .01        .203        .041
cache buffers chains                       149 3jbwa65aqmkvm          3          3     .00        .122        .041
resmgr group change latch                   33 147a57cxq3w5y          2          2     .00        .081        .041
cache buffers chains                         9 5raw2bzx227wp          2          1     .00        .081        .081
In memory undo latch                       149 f3y38zthh270n          2          1     .00        .081        .081
active checkpoint queue latch                5                        2          1     .00        .081        .081
cache buffers chains                       149 75621g9y3xmvd          2          2     .00        .081        .041
cache buffers chains                         9 gvgdv2v90wfa7          2          2     .00        .081        .041
cache buffers chains                        33 75621g9y3xmvd          2          2     .00        .081        .041
checkpoint queue latch                       5                        1          1     .00        .041        .041
ksuosstats global area                       8                        1          1     .00        .041        .041
cache buffers lru chain                    133 3jbwa65aqmkvm          1          1     .00        .041        .041
multiblock read objects                    155 75ju2gn3s8009          1          1     .00        .041        .041
resmgr group change latch                    9 0w2qpuc6u2zsp          1          1     .00        .041        .041
resmgr group change latch                   33 apgb2g9q2zjh1          1          1     .00        .041        .041
resmgr group change latch                  133 apgb2g9q2zjh1          1          1     .00        .041        .041
space background task latch                 17                        1          1     .00        .041        .041
cache buffers chains                       149 5raw2bzx227wp          1          1     .00        .041        .041
cache buffers chains                        33 5raw2bzx227wp          1          1     .00        .041        .041
cache buffers chains                        33 05s4vdwsf5802          1          1     .00        .041        .041
cache buffers chains                        31 0yas01u2p9ch4          1          1     .00        .041        .041
cache buffers chains                         9 41zu158rqf4kf          1          1     .00        .041        .041
In memory undo latch                        33 0bzhqhhj9mpaa          1          1     .00        .041        .041
In memory undo latch                        31 gvgdv2v90wfa7          1          1     .00        .041        .041
In memory undo latch                         9 gvgdv2v90wfa7          1          1     .00        .041        .041
simulator lru latch                        149 3jbwa65aqmkvm          1          1     .00        .041        .041
row cache objects                          133 5yq51dtyc6qf2          1          1     .00        .041        .041
SQL memory manager workarea list la        133 3jbwa65aqmkvm          1          1     .00        .041        .041
enqueues                                   141                        1          1     .00        .041        .041
row cache objects                          132                        1          1     .00        .041        .041

33 rows selected.

LatchProf scripts allow you to easily identify which session and SQLID (or sqlhash in 9i) cause the latch(es) to be held the most.

Let’s check what’s the most “latch-holding” SQL reported by LatchProf:

SQL> @sqlid 3jbwa65aqmkvm

HASH_VALUE  CH# SQL_TEXT
---------- ---- ------------------------------------------------------------------------------------------------------------------------------------------------------
1432996723    0 SELECT O.ORDER_ID, LINE_ITEM_ID, PRODUCT_ID, UNIT_PRICE, QUANTITY, ORDER_MODE, ORDER_STATUS, ORDER_TOTAL, SALES_REP_ID, PROMOTION_ID, C.CUSTOMER_ID,
 CUST_FIRST_NAME, CUST_LAST_NAME, CREDIT_LIMIT, CUST_EMAIL, ORDER_DATE FROM ORDERS O , ORDER_ITEMS OI, CUSTOMERS C WHERE O.ORDER_ID = OI.ORDER_ID AND
 O.CUSTOMER_ID = C.CUSTOMER_ID AND O.ORDER_STATUS <= 4

If you want to read more about the capabilities of LatchProf and LatchProfX, go here:

Note that the latest version (v1.21) also fixes a problem with Oracle 11.2 where the script execution plan order was wrong, causing the sampling to not happen in correct order. I added a NO_TRANSFORM_DISTINCT_AGG hint to disable a new transformation happening in 11.2 to make the scripts behave correctly…

Oracle Wait Event reference

Kyle Hailey has started putting together a much needed Oracle wait event reference.

You can access it here.

By the way, Oracle documentation also has a wait event reference section, it has more events, but it’s less detailed…

I have plans to go deep into some wait events and cover some less common ones in tech.E2SN too… in the future ;-)

Oracle Peformance Visualization…

Coskan Gundogar and Karl Arao have written two interesting articles about Oracle performance analysis and visualization, check these out!

Coskan’s article:

Karl’s article:

Note that in March I will be releasing PerfSheet v3.0, which will have lots of improvements! ;-)

Bind Variable Peeking – execution plan inefficiency

In my Beyond Oracle Wait interface article I troubleshooted a test case where an execution plan somehow went “crazy” and started burning CPU, lots of logical IOs and the query never completed.

I have uploaded the test case I used to my new website, to a section where I will upload some of my demo scripts which I show at my seminars (and people can download & test these themselves too):

http://tech.e2sn.com/oracle-seminar-demo-scripts

Basically what I do is this:

  1. I run the query with bind variable values where only a handful of rows match the filter condition. Thus Oracle picks nested loop join (and indexed access path)
  2. Then I run the same query with different bind values, where a lot of rows match the filter condition. Oracle reuses existing execution plan (with nested loops!!!). Oracle ends up looping through a lot of blocks again and again (because nested loop visits the “right” side of the join once for every row coming from the “left” side of the join).

Using nested loops over lots of rows is a sure way to kill your performance.

And an interesting thing with my script is that the problem still happens in Oracle 11.1 and 11.2 too!

Oracle 11g has Adaptive Cursor Sharing, right? This should take care of such a problem, right? Well no, adaptive bind variable peeking is a reactive technique – it only kicks in after the problem has happened!

So feel free to download the script, review it and test it out!

Beyond Oracle Wait Interface – Part 2

This is the second part of the joint blog “project” with James Morle, called “The Wait Interface Is Useless (Sometimes)”.

We already did a joint presentation on this topic at UKOUG and more conferences will follow :) Read the first part by James here for intro.

So, where do we go when Oracle’s wait interface doesn’t help us? We will show multiple techniques over time, but here’s where I normally continue when wait interface is “useless”.

I use V$SESSTAT.

Oh, were you expecting something more “advanced” instead of boring old V$SESSTAT’s performance counters which has been available in Oracle for ages? ;-)

Well, there is a reason why the V$SESSTAT has been available in Oracle for ages, very likely even before Wait Interface was introduced (but I wouldn’t know for sure, I was still in elementary school back then or something :).

And the reason is that session level performance counters are VERY useful about finding out WHAT Oracle is doing. Every time you parse, a counter goes up by one in V$SESSTAT for the session. Every time you execute, a counter goes up. Every time you do a logical IO, a counter goes up. Every time you commit, a counter goes up. Every time an index block is split, a counter goes up. You get the point.

Oracle’s V$SESSTAT tells you WHAT Oracle is doing. Wait interface tells you how much TIME is spent waiting for something, but V$SESSTAT counters just tell you how many times some operation was done. You can not conclude how much time was spent by looking just at the number of times something has happened (as Cary will tell you) but nevertheless, the V$SESSTAT counters definitely give you a good clue into WHAT THE [FU|HE]CK is an Oracle session doing – especially when wait interface says you’re not waiting for anything and SQL trace doesn’t print a line.

How many different operations are counted for each session in Oracle? Let’s check (Oracle 11.2):


SQL> select count(*) from v$sesstat where sid = 14;

COUNT(*)
----------
611

Oracle 11.2 keeps track of the counts of 611 different operations, for each session!

That’s VERY valuable source of information for understanding what Oracle is doing and its relatively easy to use.

And that’s exactly the reason why I wrote my Snapper script – I wanted this information to be VERY EASY to use!

And here’s an example – session 14 is stuck, doesn’t respond, user complains. Let’s check the wait interface:

If I want to know what a session is doing, I sample V$SESSION_WAIT first, with my sw.sql script (or I could just query ASH which gives me the same data with history):

SQL> @sw 14

    SID STATE   EVENT                                          SEQ# SEC_IN_WAIT P1                 P2                 P3                 P1TRANSL
------- ------- ---------------------------------------- ---------- ----------- ------------------ ------------------ ------------------ ------------------------------------------
     14 WORKING On CPU / runqueue                              3486         130

1 row selected.

SQL>
SQL> @sw 14

    SID STATE   EVENT                                          SEQ# SEC_IN_WAIT P1                 P2                 P3                 P1TRANSL
------- ------- ---------------------------------------- ---------- ----------- ------------------ ------------------ ------------------ ------------------------------------------
     14 WORKING On CPU / runqueue                              3486         137

1 row selected.

SQL>
SQL>
SQL> @sw 14

    SID STATE   EVENT                                          SEQ# SEC_IN_WAIT P1                 P2                 P3                 P1TRANSL
------- ------- ---------------------------------------- ---------- ----------- ------------------ ------------------ ------------------ ------------------------------------------
     14 WORKING On CPU / runqueue                              3486         139

1 row selected.

SQL>

From here we see 2 things:

  1. 3 samples out of 3 the session was ON CPU (not waiting). 3 samples is not too good for precise statistical sampling but there’s something else I spot in the output
  2. SEC_IN_WAIT (read: seconds in current state) is over 130. This means that this session has been in the current state (ON CPU) for over 130 seconds in row, without waiting for anything in between (the moment the wait state changes, the SEC_IN_WAIT goes back to 0).

So, it’s pretty evident that this session is just burning CPU and wait interface is useless here (as we are not waiting for anything, as far as Oracle sees it of course). Alternatively I could just run top or prstat and check whether the process is 100% on CPU or not.

So, before going on to Snapper, lets look into what kind of SQL this session executes right now (we could sample this also multiple times, to check whether we are constantly running the same statement):

SQL> <strong>select * from table(select dbms_xplan.display_cursor(sql_id,sql_child_number) from v$session where sid = 14);</strong>

PLAN_TABLE_OUTPUT
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
SQL_ID  5vy5qjd3fsn5c, child number 0
-------------------------------------
SELECT     MIN(t1.created), MAX(t1.created) FROM     t1   , t2   , t3
WHERE     t1.object_id = t2.object_id AND t2.object_id = t3.object_id
AND t1.owner = :v AND t2.owner = :v AND t3.owner = :v

Plan hash value: 3271631391

----------------------------------------------------------------------------------------
| Id  | Operation                       | Name | Rows  | Bytes | Cost (%CPU)| Time     |
----------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                |      |       |       |     4 (100)|          |
|   1 |  SORT AGGREGATE                 |      |     1 |    66 |            |          |
|*  2 |   HASH JOIN                     |      |     7 |   462 |     4  (25)| 00:00:01 |
|   3 |    NESTED LOOPS                 |      |       |       |            |          |
|   4 |     NESTED LOOPS                |      |     7 |   329 |     2   (0)| 00:00:01 |
|   5 |      TABLE ACCESS BY INDEX ROWID| T1   |     7 |   196 |     1   (0)| 00:00:01 |
|*  6 |       INDEX RANGE SCAN          | I1   |     7 |       |     1   (0)| 00:00:01 |
|*  7 |      INDEX RANGE SCAN           | I2   |    27 |       |     1   (0)| 00:00:01 |
|*  8 |     TABLE ACCESS BY INDEX ROWID | T2   |     1 |    19 |     1   (0)| 00:00:01 |
|   9 |    TABLE ACCESS BY INDEX ROWID  | T3   |    40 |   760 |     1   (0)| 00:00:01 |
|* 10 |     INDEX RANGE SCAN            | I3   |    40 |       |     1   (0)| 00:00:01 |
----------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

2 - access("T2"."OBJECT_ID"="T3"."OBJECT_ID")
6 - access("T1"."OWNER"=:V)
7 - access("T2"."OWNER"=:V)
8 - filter("T1"."OBJECT_ID"="T2"."OBJECT_ID")
10 - access("T3"."OWNER"=:V)

33 rows selected.

SQL>

Hmm… can anyone reliably tell why this SQL statement is slow and burns all the CPU time?

The answer is no. An execution PLAN is a plan of actions which would be executed when someone runs the execution plan. It doesn’t tell you anything about what’s exactly going on right now, it doesn’t tell you what exactly is using all the CPU time. Anything we would say at this point, would be a guess! Lets use V$SESSTAT instead, for gathering more hard evidence!

(The syntax of Snapper is documented inside the script or just search for snapper in my blog, plenty of examples :)

SQL> <strong>@snapper out 5 1 14
</strong>
-- Session Snapper v2.02 by Tanel Poder ( http://www.tanelpoder.com )

--
----------------------------------------------------------------------------------------------------------------------
  SID, USERNAME  , TYPE, STATISTIC                               ,         DELTA, HDELTA/SEC,    %TIME, GRAPH
----------------------------------------------------------------------------------------------------------------------
   14, SYS       , STAT, session logical reads                   ,         81351,     16.27k,
   14, SYS       , STAT, consistent gets                         ,         81351,     16.27k,
   14, SYS       , STAT, consistent gets from cache              ,         81351,     16.27k,
   14, SYS       , STAT, consistent gets from cache (fastpath)   ,         81352,     16.27k,
   14, SYS       , STAT, no work - consistent read gets          ,         81381,     16.28k,
   14, SYS       , STAT, table fetch by rowid                    ,       2904784,    580.96k,
   14, SYS       , STAT, index scans kdiixs1                     ,            93,       18.6,
   14, SYS       , STAT, buffer is pinned count                  ,       5736560,      1.15M,
   14, SYS       , STAT, buffer is not pinned count              ,         75248,     15.05k,
   14, SYS       , STAT, no buffer to keep pinned count          ,             1,         .2,
   14, SYS       , TIME, DB CPU                                  ,       6050000,      1.21s,   121.0%, |@@@@@@@@@@|
   14, SYS       , TIME, sql execute elapsed time                ,       6059922,      1.21s,   121.2%, |@@@@@@@@@@|
   14, SYS       , TIME, DB time                                 ,       6059922,      1.21s,   121.2%, |@@@@@@@@@@|
--  End of snap 1, end=2010-01-15 17:33:22, seconds=5

PL/SQL procedure successfully completed.

As our previous sw.sql output showed  – we are not waiting for anything. If we were, then snapper would show you WAIT lines from wait interface (V$SESSION_EVENT) as well. But we don’t see any waits.

So, now its the time to go through all the V$SESSTAT stats reported in Snapper! These are the lines with STAT in them (TIME lines are V$SESS_TIME_MODEL breakdown available since 10g, but they are not detailed enough for diagnosing complex problems).

One thing we see, there is a statistic session logical reads and from the last column of Snapper output we see that this session did over 16000 logical reads (buffer gets) per second during snapper run time (of 5 seconds). That’s already a good indication of why we burn so much CPU time – we are doing lots of logical IOs.

Also, we see that we did 18.6 index range scans per second (the statistic index scans kdiixs1 shows that). That doesn’t seem “much” does it. However, check the value for buffer is pinned count statistic! This counter is updated every time we go to a buffer to get some data from it AND it already happens to be open by my session! Oracle keeps buffers pinned  and relevant buffer handles cached during a database call in some cases (like nested loop joins and index scans) to avoid reopening the buffer again (getting a buffer again if its closed would mean another logical IO).

Nevertheless, we can see that we re-visited some buffers again and again and again – over a million times per second! When checking my index structures I see that every index has only a few hundred blocks, so having millions and millions of buffer visits (buffer is pinned count + session logical reads) means we are heavily re-visiting the same blocks again and again and again! This points directly to NESTED LOOPS (and also INDEX RANGE SCANS) in the execution plan. Nested loops, as the name says loops through inner rowsource and revisits some of its data as many times as the number of rows coming from the outer rowsource (with few special cases, as usual).

And there’s one more statistic in Snapper output which I do NOT see – execute count. This statistic shows how many times the session executed cursors (executed new ones or re-executed the same one). NB! Snapper only reports these V$SESSTAT statistics which changed during the snapshot – as execute count is not reported, it means that the execute count did not increase during the snapshot, thus the session still executed the same statement! (so for example we were not hard parsing and lots of different statements to “justify” this CPU usage, Snapper would have shown parse count (hard) going up if this session had done so).

So, using the above diagnosis, this is the place where I would take a serious look whether the NESTED LOOPS in the above execution plan are a right thing to do. I would check how many rows would actually match the bind variable values (more about that later) in the SQL statement predicates – NESTED LOOPS is not a good operation for joining large number of rows. More about SQL tuning very soon ;-)

To finish this blog entry, this is the sequence of troubleshooting which I usually use (if a user complains or “something” is slow):

  1. Identify the session(s) servicing the user/task with the problem
  2. Check wait interface for these sessions (sw.sql, ASH query) – this gives quick overview whether the session is 100% stuck waiting for something, 100% busy working and burning CPU or somewhere in between
  3. Run Snapper on the sessions to (very easily) see which V$SESSTAT counters have gone up (some counters such memory usage and open cursors current can go down too)
  4. If all this fails or doesn’t give enough evidence of the problem for whatever reason, then it’s time to take a screwdriver and open up Oracle from outside – using stack traces, truss, DTrace etc. We will be blogging about this ;-)

Note that Snapper is just an anonymous PL/SQL block and it doesn’t require any changes to the database!

Ok, back to James now!