I have been experimenting with empirical tests of file system and device
level writes to determine the actual constraints in order to speed up the WAL
logging code.
Using a raw file partition and a time-based technique for determining the
optimal write position, I am able to get 8K writes
tom lane wrote:
What can you do *without* using a raw partition?
I dislike that idea for two reasons: portability and security. The
portability disadvantages are obvious. And in ordinary system setups
Postgres would have to run as root in order to write on a raw partition.
It occurs to me
Curtis, have you considered comparing raw writes versus file system writes
on a raw multi-disk partition?
I always set up my machines to store data on a mirror set (RAID1) or RAID5
set, and it seems your method should be tested there too.
P.s., Tom, the postgresql user would NOT need to run
Bravo Curtis,
This is all excellent research.
:-)
Regards and best wishes,
Justin Clift
Curtis Faith wrote:
snip
Disk space is much cheaper than CPU and memory so I think that a logging
system that used as much as three or four times the space but is three or
four times faster would be a
I have been experimenting with empirical tests of file system and device
level writes to determine the actual constraints in order to speed up the WAL
logging code.
Using a raw file partition and a time-based technique for determining the
optimal write position, I am able to get 8K writes
Curtis Faith [EMAIL PROTECTED] writes:
Using a raw file partition and a time-based technique for determining the
optimal write position, I am able to get 8K writes physically written to disk
synchronously in the range of 500 to 650 writes per second using FreeBSD raw
device partitions on IDE
