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Postgresql block internals, part 2

This is the second part of a blogpost about Postgresql database block internals. If you found this blogpost, and are interested in getting started with it, please read the first part, and then continue with this post.
I am doing the investigations on Oracle Linux 7u3 with postgres 9.6 (both the latest versions when this blogpost was written).

In the first part I talked about the pageinspect extension, and investigated the page header and line pointer array. This blogpost looks at the actual tuples, including the index, and how these are stored in the pages.

Postgresql block internals

This blogpost is the result of me looking into how postgres works, and specifically the database blocks. The inspiration and essence of this blogpost comes from two blogs from Jeremiah Peschka: https://facility9.com/2011/03/postgresql-row-storage-fundamentals/ and https://facility9.com/2011/04/postgresql-update-internals/
I am using Oracle Linux 7u3 and postgres 9.6 (current versions when this blogpost was written).

Postgres is already installed, and a database cluster is already running. Let’s create a database ‘test’ for the sake of our tests:

$ createdb test

Once the database is created, logging on is done with ‘psql’:

12c Multitenant Internals: VPD for V$ views

I described in an earlier post on AWR views how the dictionary views were using metadata and object links to show information from other containers. But this mechanism cannot work for fixed views (aka V$) because they don’t have their definition in the dictionary.

The big difference is that most of V$ views are available long before the dictionary is opened or even created. Just start an instance in NOMOUNT and you can query the V$ views. Even in multitenant, you can switch to different containers in MOUNT, and query V$ views, when no dictionary is opened.

What is in a transportable tablespace dumpfile?

On 31st of May in Düsseldorf, at DOAG Datenbank, I’ll talk about transportable tablespaces and pluggable databases. Both methods are transporting data physically, the difference is in the transport of the metadata, which can be more flexible when transported logically, as with TTS, but faster when transported physically with PDB. I have a lot of demos to show transportable tablespaces with RMAN, and the different cloning features available in 12cR2. If I have time I’ll show what is inside the dumpfile when using Data Pump to export the metadata. Here is the idea.

expdp transport_tablespaces

Here is how we export metadata with Data Pump for transportable tablespaces.

A performance deep dive into column encryption

Actually, this is a follow up post from my performance deep dive into tablespace encryption. After having investigated how tablespace encryption works, this blogpost is looking at the other encryption option, column encryption. A conclusion that can be shared upfront is that despite they basically perform the same function, the implementation and performance consequences are quite different.

Oracle 12.2 wait event ‘PGA memory operation’

When sifting through a sql_trace file from Oracle version 12.2, I noticed a new wait event: ‘PGA memory operation’:

WAIT #0x7ff225353470: nam='PGA memory operation' ela= 16 p1=131072 p2=0 p3=0 obj#=484 tim=15648003957

The current documentation has no description for it. Let’s see what V$EVENT_NAME says:

SQL> select event#, name, parameter1, parameter2, parameter3, wait_class 
  2  from v$event_name where name = 'PGA memory operation';

EVENT# NAME                                  PARAMETER1 PARAMETER2 PARAMETER3 WAIT_CLASS
------ ------------------------------------- ---------- ---------- ---------- ---------------
   524 PGA memory operation                                                   Other

Well, that doesn’t help…

Advanced Oracle memory profiling using pin tool ‘pinatrace’

In my previous post, I introduced Intel Pin. If you are new to pin, please follow this link to my previous post on how to set it up and how to run it.

One of the things you can do with Pin, is profile memory access. Profiling memory access using the pin tool ‘pinatrace’ is done in the following way:

$ cd ~/pin/pin-3.0-76991-gcc-linux
$ ./pin -pid 12284 -t source/tools/SimpleExamples/obj-intel64/pinatrace.so

The pid is a pid of an oracle database foreground process. Now execute something in the session you attached pin to and you find the ‘pinatrace’ output in $ORACLE_HOME/dbs:

Introduction to Intel Pin

This blogpost is an introduction to Intel’s Pin dynamic instrumentation framework. Pin and the pintools were brought to my attention by Mahmoud Hatem in his blogpost Tracing Memory access of an oracle process: Intel PinTools. The Pin framework provides an API that abstracts instruction-set specifics (on the CPU layer). Because this is a dynamic binary instrumentation tool, it requires no recompiling of source code. This means we can use it with programs like the Oracle database executable.
The Pin framework download comes with a set of pre-created tools called ‘Pintools’. Some of these tools are really useful for Oracle investigation and research.

Oracle 12cR2: Database parameters

For those in a desperate need to learn all 4841 database parameter variations of the…

Oracle Database Block Visualizer

Recently I wanted to demonstrate to some people on my training, how Oracle database maintains blocks in a datafile – what happens after truncate, truncate with drop storage clause, delete, regular insert, direct path insert and so on…

I didn’t find any tool for that so I’ve written my own. It’s core code is based on my previous database block research – project RICO http://blog.ora-600.pl/2015/09/03/rico/

Tool is very small and simple and right now it supports only regular blocks with data and no compression.

And this is how it works – let’s create a tablespace and 3 new tables in HR schema: