Hi Everyone, i got recently interested in rocks and have a couple of questions 
if anyone else is doing/done some migrations to this engine:   1. Noticed that 
compared to toku - I/O overhead for range SELECT's with cold caches is much 
higher, especially on vmware I/O utilization (WAit) goes over 50% of available 
CPU on standard cfq scheduler and 4 cores. Changing it to noop helps and 
utilization drops around tenfold to 5-10%. It doesn't matter if we're 
doing full table scan or range scan with index. Basically i thought for LSM 
lists there'll be almost no IOPs and I/O utilization will be non-existing 
because all you need to do is reading a long, continuous block on disk 
(we're using SSDs). Any reason for that or am i doing something 
incorrectly? (default config + 6gb rocks key cache) Any reason it's working 
so badly with cfq and much better with noop?   2. Now with keys 100% cached - 
rocks is still around 2-3 times slower than toku for range scans, and even 
considerably slower than innodb. From what i understand keycache for rocks 
stores uncompressed keys, so is there some performance issue eg. with copying 
data from global keycache to local storage and is it going to be fixed or 
that's something related to how rocks works internally and there's no 
way of making it work better in the future?   3. In general it was a huge 
surprise that toku which is (at least it seems) so complicated to implement, 
and is based on very complex variation of b tree is having so much better read 
performance and so much better i/o characteristics... than "simple" 
(from what i understand) sorted list, which could be probably just read in bulk 
like a simple log file...   4. I found some info that having rocks databases 
which are over 100gb in size is not recommended (and it seems this is tiny... 
we were able to work with myisam tables which were close to 2TB). Also merging 
data could make the DB to end up being twice as big for some time. Are there 
any plans of implementing one-file-per-table like for inno?   5. What's the 
future of toku? I understand that percona is considering dropping it, will you 
take developement if that will happen or are you going to obsolete it and focus 
on rocks? From what i saw it seems that rocks and toku have totally different 
characteristics. So rocks is decent for point-reads (seems faster than toku 
when number of row reads is low)... and it seems to require less memory than 
toku, but for range scans it isn't going nowhere close. So both engines may 
have completely different use cases (eg. toku is great for long running 
statistical queries and servers with a lot of memory)   Thanks
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