Thanks, I did read through that pdf doc, and went through the counters code in 0.8-rc2, I think I understand the logic in that code.
in my hypothetical implementation, I am not suggesting to overstep the complicated logic in counters code, since the extra module will still need to enter the increment through StorageProxy.mutate( My_counter.delta=1 ) , so that the logical clock is still handled by the Counters code. the only difference is, as you said, that rainbird collapses many +1 deltas. but my claim is that in fact this "collapsing" is already done by cassandra since the write always hit the memtable first, so collapsing in Cassandra memtable vs collapsing in rainbird memory takes the same time, while rainbird introduces an extra level of caching (I am strongly suspecting that rainbird is vulnerable to losing up to 1minute's worth of data , if the rainbird dies before the writes are flushed to cassandra ---- unless it does implement its own commit log, but that is kind of re-implementing many of the wheels in Cassandra ....) I thought at one time probably the reason was because that from one given url, rainbird needs to create writes on many keys, so that they keys need to go to different Cassandra nodes. but later I found that this can also be done in a module on the coordinator, since the client request first hits a coordinator, instead of the data node, in fact, in a multi-insert case, the coordinator already sends the request to multiple data nodes. the extra module I am proposing simply translates a single insert into multi-insert, and then cassandra takes over from there Thanks Yang On Sun, May 22, 2011 at 3:47 AM, aaron morton <aa...@thelastpickle.com> wrote: > The implementation of distributed counters is more complicated than your > example, there is a design doc attached to the ticket > here https://issues.apache.org/jira/browse/CASSANDRA-1072 > By collapsing some of those +1 increments together at the application level > there is less work for the cluster to do. This can be important when the > numbers are big http://blog.twitter.com/2011/03/numbers.html > Cheers > ----------------- > Aaron Morton > Freelance Cassandra Developer > @aaronmorton > http://www.thelastpickle.com > On 21 May 2011, at 09:04, Yang wrote: > > (sorry if Rainbird is not a topic relevant enough, I'd appreciate if > someone could point me to a more appropriate venue in that case) > > > Rainbird buffers up 1 minute worth of events first before writing to > Cassandra. > > it seems that this extra layer of buffering is repetitive, and could > be avoided : Cassandra's memtable already does buffering, whose > internal implementation is just > Map.put(key, CF ) , I guess rainbird does similar things : > column_to_count = map.get(key); column_to_count++ ; map.put(key, > column_to_count) ?? > the "++" part is probably already done by the Distributed Counters in > Cassandra. > then I guess Rainbird layer exists because it needs to parse an > incoming event into various attributes that it is interested in: for > example from an url, we bump up the counts of > FQDN , domain, path etc, Rainbird does the transformation from > url--->3 attrs. > > but I guess that transformation might as well be done in the cassandra > JVM itself, if we could provide some hooks, so that a module > translates incoming request into > multiple keys, and bump up their counts. that way we avoid the > intermediate communication from clients to rainbird, and rainbird to > Cassandra. are there some points I'm missing? > > Thanks > Yang > >
