Actually I have my infraestructure splitted in multiple datacenters in an Active/active mode. So how can I manage to have a PIO instance running in each DC? Do I have to deploy also HBASE as well? How can I maintain HBASE data?
On Thu, Jun 1, 2017 at 5:23 PM, Pat Ferrel <[email protected]> wrote: > I haven’t done this, it can be done. But why? You always give up > performance when instances are not on the same physical LAN. Recommenders > are generally not considered mission critical where the ultimate HA is > required. > > > On Jun 1, 2017, at 11:19 AM, Martin Fernandez <[email protected]> > wrote: > > Thanks Pat for your reply. I am doing Video on Demand e-commerce in which > reatime query would be very helpful but I want to minimize the risks of > HDFS synchronization latency between datacenters. Do you have experience > running predictionIO + Universal Recommender in multiple DCs that you can > share? Did you face any latency issue with the HBASE cluster? > > Thanks in advance > > On Thu, Jun 1, 2017 at 2:53 PM, Pat Ferrel <[email protected]> wrote: > >> First, I’m not sure this is a good idea. You loose the realtime nature of >> recommendations based on the up-to-the-second recording of user behavior. >> You get this with live user event input even without re-calculating the >> model in realtime. >> >> Second, no you can’t disable queries for user history, it is the single >> most important key to personalized recommendations. >> >> I’d have to know more about your application but the first line of cost >> cutting for us in custom installations (I work for ActionML the maintainer >> of the UR Template) is to make the Spark cluster temporary since it is not >> needed to serve queries and only needs to run during training. We start it >> up, train. then shut it down. >> >> If you really want to shut the entire system down and don’t want realtime >> user behavior you can query for all users and put the results in your DB or >> in-memory cache like a hashmap, then just serve from your db or in-memory >> cache. This takes you back to the days of the old Mahout Mapreduce >> recommenders (pre 2014) but maybe it fits your app. >> >> If you are doing E-Commerce think about a user’s shopping behavior. They >> shop, browse, then buy. Once they buy that old shopping behavior is no >> longer indicative of realtime intent. If you miss using that behavior you >> may miss the shopping session altogether. But again, your needs may vary. >> >> >> On Jun 1, 2017, at 6:19 AM, Martin Fernandez <[email protected]> >> wrote: >> >> Hello guys, >> >> we are trying to deploy Universal Recommender + predictionIO in our >> infrastructure but we don't want to distribute hbase accross datacenters >> cause of the latency. So the idea is to build and train the engine offline >> and then copy the model and ealstic data to PIO replicas. I noticed when I >> deploy engine, it always tries to connect to HBASE server since it is used >> to query user history. Is there any way to disable those user history >> queries and avoid connection to HBASE? >> >> Thanks >> >> Martin >> >> > > > -- > Saludos / Best Regards, > > *Martin Gustavo Fernandez* > Mobile: +5491132837292 <+54%209%2011%203283-7292> > > > -- > You received this message because you are subscribed to the Google Groups > "actionml-user" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > To post to this group, send email to [email protected]. > To view this discussion on the web visit https://groups.google.com/d/ > msgid/actionml-user/CAGQyoRcZtFs9BdGx4y9qSd0qyJBxP > QN7NuGrgStT%2BNo%2B7nn0Mw%40mail.gmail.com > <https://groups.google.com/d/msgid/actionml-user/CAGQyoRcZtFs9BdGx4y9qSd0qyJBxPQN7NuGrgStT%2BNo%2B7nn0Mw%40mail.gmail.com?utm_medium=email&utm_source=footer> > . > For more options, visit https://groups.google.com/d/optout. > > -- Saludos / Best Regards, *Martin Gustavo Fernandez* Mobile: +5491132837292
