I would like to talk about Flashback Data Archive (or Flashback Archive – FBA) in 12c. FBA was introduced in 11g. It is not new but it has very important new features that allow us to use FBA very efficiently and for free. I would like to talk about new features more than what it does and and how it works but let’s give a quick look.
What is FBA?
Basically FBA is a module that let you store historical information about data in your table. When you enable FBA for a table then Oracle will start to watch this table and store every change on the table. this is a large definition and it is not wrong because all the DML changes will be started to log but also physical changes will be recorded too. you will be able to flashback your table before truncate or any other table alter. if you dropped a column, you can take it back or vice versa.
What is new in 12c?
First of all, and I believe the most important one, it is free anymore! in 11g FBA was using compressed tables by default which requires “Advanced Compression License” and that means additional costs. in 12c this is an optional feature. By default Oracle does not create those table as compressed so you don’t have to pay anything unless you don’t want to use compression option.
Secondly, FBA can store context information along the data changes anymore which I needed most and couldn’t use it in 11g just because of that. if you have a web application then probably application will be using a common user and managing users itself. this causes you not to identify sessions because they are all same users but if you have a good developer team then you can ask them to set some context information like client_identifier. This data can be used to separate sessions and identify real users for example. With 12c FBA is able to store those information with changes and when we check historical data we can see all context information too.
Is FBA better than Log Triggers?
In my opinion, YES! of course there are many things to check but I will try to make a demonstration about performance of FBA.
This is my test case:
So we have two tables, TMP and TMP_FBA. I created a logging trigger on TMP and write every DML into TMP_LOG table with some context information like, client identifier, os_user, terminal etc. In this point you can see that my trigger is a for each row trigger and it will be writing every change one by one to log table. Some might use a compound trigger and store changed rows into a collection write it to log table at after statement section. This can optimize your logging while using Bulk DMLs but if your DMLs change too much rows then this can cause you consume too much PGA and memory problems. So I didn’t use it in my example. By the way to provide stability I created T_Base_Data table and I will use this to insert my original test tables.
My FBA is not compressed one (I didn’t use “optimize data” clause) as well as my Tmp_Log table too. I will do some DML and compare the performance. Also I want to compare size of the tables it will give useful information too. First I will insert some data with “insert select” statement then insert same data row by row using a for loop.
When we check timings, we see unbelievable difference:
Trigger Bulk Insert: 22.13 seconds
FBA Bulk Insert : 00.07 seconds
Trigger Row By Row Insert: 33.62 seconds
FBA Row By Row Insert : 05.12 seconds
so for performance of our Insert statements, winner is definitely FBA. if we check log sizes, Our log table which is inserted by trigger, has reach to 112MB but FBA related objects are 35MB. One of the best things about FBA is it does not generate much INSERT log records because the original data is already in our table. This feature has already given us a lot of space. So we can say that about logging size FBA is winner again!
PS: While running my codes, I want you to know that only FBA table is Tmp_FBA so while checking size of FBA related object I used “object_name like ‘SYS_FBA%” condition. I will explain those objects at the end.
Let’s run some UPDATE:
Trigger Update : 53.38 seconds
FBA Update : 02.25 seconds
Trigger Log Size : 96 MB (208 – 112)
FBA Log Size : 91 MB (126 – 35)
Winner is still FBA.
Trigger Delete : 48.24 seconds
FBA Delete : 01.92 seconds
Trigger Log Size : 104 MB (312-208)
FBA Log Size : 48 MB (174-126)
and winner is again FBA!
Everything is awesome but how can we see our logs in FBA? where are those logs? of course we can check the tables that FBA created automatically but there is a better way to see logs, Flashback Query:
you don’t even need to find the log table, just a flashback query will be enough to see historical data.
In my example I inserted 2 times all dba_objects into t_base_data table and I used this table to insert 2 times again into Tmp_FBA, that is why you see 4 COL$ tables.
finally, if you want to see FBA tables:
SYS_FBA_DDL_COLMAP_nnnnn is used to store column changes.
SYS_FBA_TCRV_nnnnn is used to store transaction informations.
SYS_FBA_HIST_nnnnn is used to store data changes.
also there are 2 default indexes on those tables.
Why FBA is so much faster?
trigger logging cause 2 actions. first calling a trigger which is a plsql object and then running an another insert statement. That means too much job to complete and context switch between sql and plsql.
FBA is using UNDO segments so basically it does no extra job! whenever you run a DML statement, Oracle copies all data which you are about to change to undo segments. if you commit, undo segments become obsolete (unless there is no select actively running) but if you rollback then all data in undo segments copied back to original table blocks. that is why commit is too fast but rollback is slow. Anyway, FBA reads undo segments which means your DML already generated undo blocks and FBA just read and save them. That’s all.
How about the Security?
One more time, FBA is the winner! You can not modify FBA related tables and by saying modify we mean any DML or DDL. even if SYS user can not drop or delete FBA related tables:
any user with drop any table or delete any table can delete your trigger base logging table but not with FBA! that brings a huge security advantage. of course a user who has flashback archive administer privilege can remove FBA from your table but this will be an obvious action because previous data will be also lost!
Based on results of my test case I decided to convert all my log structure to FBA but there are a few more tests that I must complete first like checking PMOs (partition management operation), compression on FBA (since I have advanced compression license) etc.
thanks for reading.