In my last blog post I covered some details of our recent battle with memory fragmentation problems on an OL6 server (Exadata compute node). It was mostly focused around page cache growth which was the main scenario. However, in addition to that, there was also a secondary scenario that had a completely different mechanism, and I will describe it in this post.Continue reading “Memory fragmentation via inode cache growth”
Database query tuning is mostly about getting better plans. Mostly, but not always. Sometimes, the problem has nothing to do with the plan, and you might need to get a bit creative to find a solution. In this recent case a query was showing a decent performance when running from SQL Developer, but it took about 5 times longer to complete when running from R. The plan was the same, so I knew that it was irrelevant. The R session wasn’t showing as active most of the time, so it was fairly clear that the problem was fetching data — i.e. it was fetching too few rows at a time which lead to a large number of roundtrips, and consequently, high waits on “idle” event “SQL*Net message from client”.
In my earlier post, I mentioned an interesting case which among other symptoms, featured high CPU usage. In this post I would like to tell more about that case.
I was investigating poor performance on a 10.2.0.5 Oracle database, and I was asked to look at it after yet another outage (the database wasn’t accepting any connections for over two hours). The AWR report showed massive mutex and latch contention: