Re: Universal Recommender and PredictionIO 0.12.0 incompatibility

Yes, easy enough to do but rather annoying. Rather than supporting 1.x and 5.x I think the UR 0.6.1 will be EOL for ES 1.x and UR 0.7.0 will be ES 5.x from then on. We have a major speedup in 0.7.0 and an even greater speedup in the next after that, which will start using Spark dataframes

Re: Universal Recommender and PredictionIO 0.12.0 incompatibility

Hi Pat, On 4 October 2017 at 22:04, Pat Ferrel wrote: > It looks like PIO 0.12.0 will require a code change in the UR. PIO changed > ES1 support drastically when ES5 support was added and broke the UR code. > > We will do a quick fix to the template to address this. In the

Re: [ERROR] Timeout when read recent events

When you query for all users in batch, the system is easily overloaded. This is the worst case query situation where no caching applies (for instance). 1) run batch queries at low input load time, because you are competing with input for access to HBase 2) throttle your query speed and/or

Re: Adding Spark Context (sc) to predict method?

Thanks for the guidance Daniel and Donald. A few follow up items to check my understanding... Daniel, here is the link to the documentation I think you were referencing on how to save a model with RDD. I read through it and see a way to train with an RDD but did not see a way to get the

Re: [ERROR] [TaskSetManager] Task 2.0 in stage 10.0 had a not serializable result

Hi Pat, I have adapted the integration test for my app. I attach the integration test as I'm running it, the data file and the screen output of the integration test. In the latter you can see the same error as before even though now I have much more data. I wanted to implement a small example (a