Or, Why is My Transaction So Big?
My team and I still use old-style rollback segments for one of my client’s 10g production databases. We just never found the need to switch to automatic undo management. There are a number of 1GB rollback segments. They are that size because they need to be able to support large transactions. At the same time, we don’t want to have transactions bigger than 1GB as this is an OLTP system.
For the past few weeks we’ve had a strange problem. One of the web calls would cause one of the rollback segments to become full by using 1GB of undo data. Eventually the session would do a rollback, but we couldn’t track just what was filling up the transaction.
We could have installed logminer and analyzed the redo logs, but I had a better idea that required less time.
First I looked at
v$lock to see which (and how many) tables were been accessed. I got a list of about 5 tables. Not a big list, and we needed to know more than just tables. We began to suspect a bug in the client’s system causing a section of the code to loop endlessly without committing and inserting or updating some rows. We wanted to know exactly which table and possibly what data were in the inserts.
I took samples of
v$session_wait_history. There were lots of “db file sequential read” from the rollback process. Looking at the file number, I saw that some of them were on the rollback tablespace, others were in other datafiles. It happened that most of the non-rollback reads were on a specific tablespace that had only 1 table. So now I know which table it is (it is a logging table), but I still need to find out what was being inserted (the table is insert only, no updates).
Since this is a production database, we have a standby. I immediately stopped the standby recovery, and opened it read-only. It being a standby, there are no dirty blocks, and no checkpoint needed. I dumped some of the blocks being rolled back, looked at their contents… and saw a large number of very similar records.
I took a few of them and decoded the hex data to extract all the values of what was been inserted, and included that in an email to the client’s developers. I hope it will help them pinpoint the location of that loop.