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Re: optimising filesystem for many small files
- From: Viji V Nair <viji fedoraproject org>
- To: Peter Grandi <pg_ext3 ext3 to sabi co uk>
- Cc: Linux ext4 <linux-ext4 vger kernel org>, Linux ext3 <ext3-users redhat com>
- Subject: Re: optimising filesystem for many small files
- Date: Sun, 18 Oct 2009 21:40:28 +0530
On Sun, Oct 18, 2009 at 7:45 PM, Peter Grandi
<pg_ext3 ext3 to sabi co uk> wrote:
>>>>> Hi, System : Fedora 11 x86_64 Current Filesystem: 150G ext4
>>>>> (formatted with "-T small" option) Number of files: 50
>>>>> Million, 1 to 30K png images We are generating these files
>>>>> using a python programme and getting very slow IO
>>>>> performance. While generation there in only write, no
>>>>> read. After generation there is heavy read and no write.
>>>>> I am looking for best practices/recommendation to get a
>>>>> better performance. Any suggestions of the above are
>>>>> greatly appreciated.
> The first suggestion is to report issues in a less vague way.
> Perhaps you are actually getting very good performance, but it is
> not sufficient for the needs of your application; or perhaps you
> are really getting poor performance, and emoving the cause would
> make it sufficient for the needs of your application. But no
> information on what is the current and what is the desired
> performance is available, and that should have been the first
> thing stated.
There are two issues mainly.
1. I am generating 50 Million 256 x 256 png images using two
application, mapnik and tilecache. Both the application are open
source and the seeder programme in tilecache which is used to
precache these tiles from mapnik and gis data source is single
threaded. So I was running 4 processes and it was taking 20 sec to
create a file. Now I have reduced the number of process to one and I
am getting 6 sec per tile.
2. The goal is to achieve to generate a tile in less than 1 sec. The
backend gis data source is postgres+postgis, the application, mapnik,
is making only one query at a time to generate a single tile. The
postgres is a 50G DB running on 16GB dual xeon boxes.
>>>> [ ... ] these files are not in a single directory, this is a
>>>> pyramid structure. There are total 15 pyramids and coming down
>>>> from top to bottom the sub directories and files are
>>>> multiplied by a factor of 4. The IO is scattered all over!!!!
>>>> [ ... ]
> Is that a surprise? First one creates a marvellously pessimized
> data storage scheme, and then "surprise!" IO is totally random
> (and it is likely to be somewhat random at the application level
>>> [ ... ] What is the application trying to do, at a high level?
>>> Sometimes it's not possible to optimize a filesystem against a
>>> badly designed application. :-( [ ... ]
>> The application is reading the gis data from a data source and
>> plotting the map tiles (256x256, png images) for different zoom
>> levels. The tree output of the first zoom level is as follows in
>> each zoom level the fourth level directories are multiplied by a
>> factor of four. Also the number of png images are multiplied by
>> the same number. Some times a single image is taking around 20
>> sec to create. [ ... ]
> Once upon a time in the Land of the Silly Fools some folks wanted
> to store many small records, and being silly fools they worried
> about complicated nonsense like locality of access, index fanout,
> compact representations, caching higher index tree levels, and
> studied indexed files and DBMSes; and others who wanted to store
> large images with various LODs studied ways to have compact,
> progressive representations of those images.
> As any really clever programmer and sysadm knows, all those silly
> fools wasted a lot of time because it is very easy indeed instead
> to just represent large small-record image collections as files
> scattered in a many-level directory tree, and LODs as files of
> varying size in subdirectories of that tree. :-)
> [ ... ]
>>> With a sufficiently bad access patterns, there may not be a lot
>>> you can do, other than (a) throw hardware at the problem, or
>>> (b) fix or redesign the application to be more intelligent (if
> "if possible" here is a big understatement. :-)
>> The file system is crated with "-i 1024 -b 1024" for larger
>> inode number, 50% of the total images are less than 10KB.
>> I have disabled access time and given a large value to the
>> commit also.
> These are likely to be irrelevant or counteproductive, and do not
> address the two main issues, the acess pattern profile of the
> application and how stunningly pessimized the current setup is.
>> Do you have any other recommendation of the file system
> Get the application and the system redeveloped by some not-clever
> programmers and sysadms who come from the Land of the Silly Fools
> and thus have heard of indexed files and databases and LOD image
> representations and know why silly fools use them. :-)
I am trying to get some more hardware, SSD is not possible now. I am
tring to get SAS 15k disks with more spindles.
Now the image tiles are 50Million, with in an year it will become
1Billion, we will be receiving UGC/Satellite images as well, so with
in couple of years
the total image size will be close to 4TB :). So started thinking
about the scalability/performance issues....,
as suggested I will be searching for some silly fools to design and
deploy the same with me .......:)
> Since that recommendation is unlikely to happen (turkeys don't
> vote for Christmas...), the main alternative is use some kind of
> SLC SSD (e.g. recent Intel 160GB one) so as to minimize the impact
> of a breathtakingly pessimized design thanks to a storage device
> that can do very many more IOP/s than a hard disk. On a flash SSD
> I would suggest using 'ext2' (or NILFS2, and I wish that UDF were
> in a better state):
> Actually I would use an SSD even with an indexed file or a DBMS
> and a LOD friendly image representation, because while that will
> avoid the pessimized 15-layer index tree of directories, even in
> the best of cases the app looks like having extremly low locality
> of reference for data, and odds are that there will be 1-3 IOPs
> per image cess (while probably currently there are many more).
> The minor alternative is to use a file system like ReiserFS that
> uses index trees internally and handles particularly well file
> "tails", and also spread the excitingly pessimized IOP load across
> a RAID5 (this application seems one of the only 2 cases where a
> RAID5 makes sense), not a single disk. A nice set of low access
> time 2.5" SAS drives might be the best choice. But considering the
> cost of a flash 160GB SSD today, I'd go for a flash SSD drive (or
> a small RAID of those) and a suitable fs
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