Apex Library Cache Latch Contention

I recently encountered an unusual contention issue on the library cache latch, and thought it was worth recording what happened and how the issue was resolved.

The problem occurred with one of our Oracle Apex applications running on v3.1.2 of Oracle Apex and v10.2.0.5 of Oracle RDBMS. For the sake of completeness the application was hosted on an IBM AIX 6 server but that was not relevant to the investigation.

The site who reported the problem are a relatively high volume site, with over 800 users and around 400,000 page views per day. The were reporting a serious degradation in performance under load, to the point where the application was almost unusable so an urgent investigation was required.

The site had already run off some AWR reports that clearly showed the problem lay with the library cache latch – the Top 5 Timed Events from the report are shown below.

Top 5 Timed Events Avg %Total
~~~~~~~~~~~~~~~~~~ wait Call
Event Waits Time (s) (ms) Time
---------------------------- ----------- ----------- ------ ------
latch: library cache 692,012 86,615 125 20.0
CPU time 41,692 9.7
db file sequential read 3,656,449 30,389 8 7.0
latch: row cache objects 164,161 23,585 144 5.5
latch: library cache lock 176,975 21,011 119 4.9


So the problem was contention for library cache latch but what was causing it ?

The site had recently applied a patch to the application, so naturally that was carrying the blame – but the patch was relatively minor and did not seem like it could be responsible for the problems we were seeing.

So what are the most likely causes for contention on the library cache latch ?

Experience tells us that we should be looking for SQL statements that are not being reused (maybe using literals rather than bind variables) or possibly that the shared pool is simpy too big. The site in question had similar problems in the past due to poorly configured Automatic Shared Memory Management parameters that had allowed the shared pool to grow to over 10GB in size.

The shared pool was a reasonable size so the focus initially was on looking for SQL statements that weren’t being reused. Sure enough we found a couple of candidate statements that were showing a very high version count – statements with a high version count are reported in AWR and StatsPack reports but the script top10.sql is also useful for identifying them.

However the SQL statements we had identified were not new and were also showing similar high version counts at other sites who were not experiencing the same contention.

We needed to find out exactly what was causing the contention on the library cache latch – and I was under the impression that was going to be difficult.

Enter the frankly invaluable latchprof.sql script from Tanel Poder which does exactly that.

There’s even a handy guide that tells how to use it to troubleshoot latch contention – how had I not found this before ?

Running latchprof.sql against the database showed the following

NAME SQLID Held Gets Held % Held ms Avg hold ms
----------------------------------- ------------- ---------- ---------- ------- ----------- -----------
library cache lock allocation 4dqasqjrvudqn 7880 3548 78.80 17367.520 4.895
library cache lock allocation 6472 3034 64.72 14264.288 4.701
library cache pin allocation 408 373 4.08 899.232 2.411
library cache lock allocation g78p6p30n7srb 87 11 .87 191.748 17.432


So that was pretty conclusive, the contention was down to one particular SQL statement – but what was it ?

Well it turns out this was the call to

dbms_session.reset_package

that is invoked by every request that is made to the Oracle Apex application – its a consequence of the Oracle Apex architecture.

There is simply no way we can stop the application from calling this routine – but why was it suddenly causing such crippling contention ?

To cut a long story short the customer had set the following database initialisation parameter

*.session_cached_cursors=75

Now on the face of it that doesn’t seem unreasonable – caching session cursors is a good thing isn’t it ?

Well actually when you’re dealing with an Oracle Apex application caching session cursors is largely irrelevant.

As we have already discovered Oracle Apex calls dbms_session.reset_package essentially for each page view recorded in the application, and one of the many things this routine does is to close all session cursors. All of which means that Oracle Apex applications will hardly ever reuse cursors, and you should be expecting to see a relatively high number of Soft Parses in your database.

Consequently the recommendation for our application has always been to stick with the default value for the session_cached_cursors parameter – at Oracle v10.2.0.5 this is 20, although it increases to 50 at Oracle v11.2.0.2.

The theory we were now operating under was that since each session in the Oracle Apex session pool was potentially caching up to 75 cursors, the repeated calls to dbms_session.reset_package were that much more expensive and were therefore resulting in the latch contention that we were seeing.

This fix was obvious – we needed to remove the session_cached_cursors parameter from the database and revert back to the recommended configuration for the Oracle Apex application.

After making that change the latch contention disappeared and performance at the site returned to normal – although the number of Soft Parses did increase!

The lessons to be learned here are

1. Oracle Apex applications hardly ever reuse session cached cursors
2. If you’re suffering from latch contention then you need latchprof!

Hope all that proves useful should you find yourself in a similar situation.  🙂