No, they are on seperate machines. Its a 4 machine cluster - 2 workers, 1 nimbus and 1 zookeeper.
I suppose I could just create a new cluster but Id like to know why this is occurring to avoid future production outages. Thanks, S On Sun, Mar 2, 2014 at 6:19 PM, Michael Rose <[email protected]>wrote: > Are you running Zookeeper on the same machine as the Nimbus box? > > Michael Rose (@Xorlev <https://twitter.com/xorlev>) > Senior Platform Engineer, FullContact <http://www.fullcontact.com/> > [email protected] > > > On Sun, Mar 2, 2014 at 6:16 PM, Sean Solbak <[email protected]> wrote: > >> This is the first step of 4. When I save to db I'm actually saving to a >> queue, (just using db for now). The 2nd step we index the data and 3rd we >> do aggregation/counts for reporting. The last is a search that I'm >> planning on using drpc for. Within step 2 we pipe certain datasets in real >> time to the clients it applies to. I'd like this and the drpc to be sub 2s >> which should be reasonable. >> >> Your right that I could speed up step 1 by not using trident but our >> requirements seem like a good use case for the other 3 steps. With many >> results per second batching should effect performance a ton if the batch >> size is small enough. >> >> What would cause nimbus to be at 100% CPU with the topologies killed? >> >> Sent from my iPhone >> >> On Mar 2, 2014, at 5:46 PM, Sean Allen <[email protected]> >> wrote: >> >> Is there a reason you are using trident? >> >> If you don't need to handle the events as a batch, you are probably going >> to get performance w/o it. >> >> >> On Sun, Mar 2, 2014 at 2:23 PM, Sean Solbak <[email protected]> wrote: >> >>> Im writing a fairly basic trident topology as follows: >>> >>> - 4 spouts of events >>> - merges into one stream >>> - serializes the object as an event in a string >>> - saves to db >>> >>> I split the serialization task away from the spout as it was cpu >>> intensive to speed it up. >>> >>> The problem I have is that after 10 minutes there is over 910k tuples >>> emitted/transfered but only 193k records are saved. >>> >>> The overall load of the topology seems fine. >>> >>> - 536.404 ms complete latency at the topolgy level >>> - The highest capacity of any bolt is 0.3 which is the serialization one. >>> - each bolt task has sub 20 ms execute latency and sub 40 ms process >>> latency. >>> >>> So it seems trident has all the records internally, but I need these >>> events as close to realtime as possible. >>> >>> Does anyone have any guidance as to how to increase the throughput? Is >>> it simply a matter of tweeking max spout pending and the batch size? >>> >>> Im running it on 2 m1-smalls for now. I dont see the need to upgrade it >>> until the demand on the boxes seems higher. Although CPU usage on the >>> nimbus box is pinned. Its at like 99%. Why would that be? Its at 99% >>> even when all the topologies are killed. >>> >>> We are currently targeting processing 200 million records per day which >>> seems like it should be quite easy based on what Ive read that other people >>> have achieved. I realize that hardware should be able to boost this as >>> well but my first goal is to get trident to push the records to the db >>> quicker. >>> >>> Thanks in advance, >>> Sean >>> >>> >> >> >> -- >> >> Ce n'est pas une signature >> >> > -- Thanks, Sean Solbak, BsC, MCSD Solbak Technologies Inc. 780.893.7326 (m)
