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From Josh Dzielak <>
Subject Guaranteeing globally unique TimeUUID's in a high throughput distributed system
Date Sat, 16 Mar 2013 21:24:40 GMT
I have a system where a client sends me arbitrary JSON events containing a timestamp at millisecond
resolution. The timestamp is used to generate column names of type TimeUUIDType.

The problem I run into is this - if I client sends me 2 events with the same timestamp, the
TimeUUID that gets generated for each is the same, and we get 1 insert and 1 update instead
of 2 inserts. I might be running many processes (in my case Storm supervisors) on the same
node, so the machine-specific part of the UUID doesn't help.

I have noticed how the Cassandra UUIDGen class lets you work around this. It has a 'createTimeSafe'
method that adds extra precision to the timestamp such that you can actually get up to 10k
unique UUID's for the same millisecond. That works pretty good for a single process (although
it's still possible to go over 10k, it's unlikely in our actual production scenario). It does
make searches at boundary conditions a little unpredictable – 'equal' may or may not work
depending on whether extra ns intervals were added – but I can live with that.)  

However, this still leaves vulnerability across a distributed system. If 2 events arrive in
2 processes at the exact same millisecond, one will overwrite the other. If events keep flowing
to each process evenly over the course of the millisecond, we'll be left with roughly half
the events we should have. To work around this, I add a distinct 'component id' to my row
keys that roughly equates to a Storm worker or a JVM process I can cheaply synchronize.

The real problem is that this trick of adding ns intervals only works when you are generating
timestamps from the current time (or any time that's always increasing). As I mentioned before,
my client might be providing a past or future timestamp, and I have to find a way to make
sure each one is unique.

For example, a client might send me 10k events with the same millisecond timestamp today,
and 10k again tomorrow. Using the standard Java library stuff to generate UUID's, I'd end
up with only 1 event stored, not 20,000. The warning in UUIDGen.getTimeUUIDBytes is clear
about this.  

Adapting the ns-adding 'trick' to this problem requires synchronized external state (i.e.
storing that the current ns interval for millisecond 12330982383 is 1234, etc) - definitely
a non-starter.

So, my dear, and far more seasoned Cassandra users, do you have any suggestions for me?  

Should I drop TimeUUID altogether and just make column names a combination of millisecond
and a big enough random part to be safe? e.g. '1363467790212-a6c334fefda'. Would I be able
to run proper slice queries if I did this? What other problems might crop up? (It seems too
easy :)  

Or should I just create a normal random UUID for every event as the column key and create
the non-unique index by time in some other way?  

Would appreciate any thoughts, suggestions, and off-the-wall ideas!  

PS- I assume this could be a problem in any system (not just Cassandra) where you want to
use 'time' as a unique index yet might have multiple records for the same time. So any solutions
from other realms could be useful too.   

Josh Dzielak     
VP Engineering • Keen IO
Twitter • @dzello (
Mobile • 773-540-5264

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