Hello,

I'm not sure if I understand your requirements correctly, but I have my doubts 
about NILFS being a silver bullet for latency constrained workloads. First, the 
idea behind log-structured file systems is to optimize for writes - batching 
several unrelated write requests into a single continuous write. Your workload 
seems to be read-mostly (BTW, ReiserFS is noted for very good small file 
performance and it worked stable for me). Second, performace of any file system 
depends on performance of the underlying hardware and magnetic disks simply 
cannot deliver enough IOPs, especially for random reads/writes. So if you want 
really low latency and high IO rate you probably need to either go for SSDs 
(and NILFS for that matter), or keep the whole working set in memory (which is 
usually prohibitive in terms of price). Third, there are other things than file 
systems that are probably more suited to the task. I mean, you can put several 
machines together to form a cluster and than run a distribited key-value store 
on it. Key-value stores are something in between a file system and relational 
database. These are optimized for retrieving/storing small objects with low 
latency. Most known key-value store is probably Amazon's Dynamo 
(http://www.allthingsdistributed.com/2007/10/amazons_dynamo.html), but there 
are others. You can find a decent introduction here: 
http://www.metabrew.com/article/anti-rdbms-a-list-of-distributed-key-value-stores/
 I understand that my answers are probably not what you expected, but that's 
what I think. And I'm sure others will have come up with something more 
substantial and more related to NILFS performace for your workload.

Cheers

Ales Blaha

hi all,

Read an interesting article online on NILFS suggesting it would be ok for fast latency.

Very interesting.

Now my use case is rather simple. It is for read-only of EGTBs. (chess endgametablebases).

During a game tree search of (for example) a chessprogram if reaching far endgame,
it will go into the file system and do a lot of random reads.
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