Despite common misconception HDFS inodes do not store the entire file
paths just the names.
The underlying namespace data structure is pretty straightforward.
It reflects the actual namespace tree. Each directory node has pointers
to its children, which
are combined in a TreeMap. So the access to directory entries is
logarithmically reasonable (or
reasonably logarithmic if you wish :-) unlike traditional FSs.
200 bytes per file is theoretically correct, but rather optimistic :-(
From a real system memory utilization I can see that HDFS uses 1.5-2K
per file.
And since each real file is internally represented by two files (1 real
+ 1 crc) the real
estimate per file should read 3-4K.
But this includes everything - block to data-node map, node to block
map, etc.
Storing of a 2M file directory will require 6-8Gb (on 64bit hardware)
but is still feasible.
As far as I know HDFS does not have explicit restrictions on the number
of files in one directory.
File path is limited, but not the directory size.
I haven't heard that anybody tried to push it to the limit in this
direction yet.
This could be interesting.
--Konstantin
Bryan A. P. Pendleton wrote:
Looks like an interesting problem. The number of files stored in HDFS is,
roughly, limited to the amount of memory in the NameNode needed to track
each file. Each file is going to require some number of bytes of
storage on
the NameNode (at a minimum, enough to represent its name(~full path size
now, but could be made to be parent/differential to just the unique file
prefix), the names of each block (so, 64bits per 64mb, given the current
defaults), and, for each block, a reference to the nodes that contain
that
block. So, a 100Mb MapFile is going to require two filename strings, 3
64bit
block references, and at least a platform pointer for each block for each
replication - I'd guess you could squeeze that to 100-200 bytes per
file in
a pinch, though I'd guess that it's more in the current implementation of
the NameNode code.
So, for your example numbers (a 200Tb HBase, with, thus, 2M MapFiles),
you'd
need 2M*2*200 bytes, or something like 400Mb of memory on the
NameNode. So,
*shrug*, it sounds theoretically possible, and probably means it's not
the
point to spend time optimizing against right now.
By the way - I'm at PARC, but hide behind a personal e-mail address for
Hadoop discussion. Fun to see what you guys at Powerset are working
on. :)
On 2/5/07, Jim Kellerman <[EMAIL PROTECTED]> wrote:
Bryan,
Storing many low-record-count files is not what I am concerned about so
much
as, storing many high-record-count files. In the example
(http://wiki.apache.org/lucene-hadoop/Hbase/HbaseArchitecture#example),
for one column of one table we are talking about 2M MapFiles to hold the
data for one column of a particular table. Now they have to have some
HDFS
name, so does that mean they need to live in a HDFS directory or can
HDFS
files live outside the HDFS directory space even if they are to be
persistent? (This is an area of HDFS I haven't explored much, so I don't
know if we have to do something to make it work.) Certainly you could
not
put 2M files in a Unix directory and expect it to work. I'm just
trying to
understand if there are similar limitations in Hadoop.
Any light that could shed on the matter would be greatly appreciated.
Thanks.
-Jim
On 2/2/07 12:21 PM, "Bryan A. P. Pendleton" <[EMAIL PROTECTED]> wrote:
> We have a cluster of about 40 nodes, with about 14Tb of aggregate raw
> storage.. At peak times, I have had up to 3 or 4 terabytes of data
stored in
> HDFS, stored in probably 100-200k files.
>
> To make things work for my tasks, I had to hash through a few
different
> tricks for dealing with large sets of data - not all of the tools you
might
> like for combining different sequential streams of data in Hadoop are
> around. In particular, running MapReduce processes to re-key or
variously
> mix sequential inputs for further processing can be problematic when
your
> dataset is already taxing your storage. If you read through the
history
of
> this list, you'll see that I'm often agitating about bugs in handling
> low-disk-space conditions, storage balancing, and problems related to
> numbers of simultaneous open files.
>
> I haven't generally run into files-per-directory problems, because I
> introduce my data into SequenceFile or MapFile formats as soon as
possible,
> then do work across segments of that. Storing individual
low-record-count
> files in HDFS is definitely a no-no given the current limits of the
system.
>
> Feel free to write me off-list if you want to know more particulars of
how
> I've been using the system.
>
> On 2/2/07, Jim Kellerman <[EMAIL PROTECTED]> wrote:
>>
>> I am part of a working group that is developing a Bigtable-like
structured
>> storage system for Hadoop HDFS (see
>> http://wiki.apache.org/lucene-hadoop/Hbase).
>>
>> I am interested in learning about large HDFS installations:
>>
>> - How many nodes do you have in a cluster?
>>
>> - How much data do you store in HDFS?
>>
>> - How many files do you have in HDFS?
>>
>> - Have you run into any limitations that have prevented you from
growing
>> your application?
>>
>> - Are there limitations in how many files you can put in a single
>> directory?
>>
>> Google's GFS, for example does not really implement directories
per-se,
>> so it does not suffer from performance problems related to
having too
>> many files in a directory as traditional file systems do.
>>
>> The largest system I know about has about 1.5M files and about
150GB of
>> data. If anyone has a larger system in use, I'd really like to hear
from
>> you. Were there particular obstacles you had in growing your
system to
>> that
>> size, etc?
>>
>> Thanks in advance.
>> --
>> Jim Kellerman, Senior Engineer; Powerset
[EMAIL PROTECTED]
>>
>
>
--
Jim Kellerman, Senior Engineer; Powerset [EMAIL PROTECTED]
