Hi, Thank you! I came into further more confusion here, actually I installed prediction IO version 0.10.0 from here http://predictionio.incubator.apache.org/install/install-sourcecode/ and have been fighting to configure mysql as a storage in my local linux machine.
But I see there is a different documentation of installing in actionml website, I'm not sure for which I would have to go. Currently there is no " pio-env.sh". file inside conf folder however there is pio-env.sh.template file. I commented the pgsql section and uncommented the mysql section with the username and password, but whenever I do . sudo PredictionIO-0.10.0-incubating/bin/pio eventserver there seems to be an error that says that authentication failed with pgsql, however I don't want to use pgsql. # Storage Repositories # Default is to use PostgreSQL PIO_STORAGE_REPOSITORIES_METADATA_NAME=pio_meta PIO_STORAGE_REPOSITORIES_METADATA_SOURCE=PGSQL PIO_STORAGE_REPOSITORIES_EVENTDATA_NAME=pio_event PIO_STORAGE_REPOSITORIES_EVENTDATA_SOURCE=PGSQL PIO_STORAGE_REPOSITORIES_MODELDATA_NAME=pio_model PIO_STORAGE_REPOSITORIES_MODELDATA_SOURCE=PGSQL # Storage Data Sources # PostgreSQL Default Settings # Please change "pio" to your database name in PIO_STORAGE_SOURCES_PGSQL_URL # Please change PIO_STORAGE_SOURCES_PGSQL_USERNAME and # PIO_STORAGE_SOURCES_PGSQL_PASSWORD accordingly #PIO_STORAGE_SOURCES_PGSQL_TYPE=jdbc #PIO_STORAGE_SOURCES_PGSQL_URL=jdbc:postgresql://localhost/pio #PIO_STORAGE_SOURCES_PGSQL_USERNAME=pio #PIO_STORAGE_SOURCES_PGSQL_PASSWORD=pio # MySQL Example PIO_STORAGE_SOURCES_MYSQL_TYPE=jdbc PIO_STORAGE_SOURCES_MYSQL_URL=jdbc:mysql://localhost/pio PIO_STORAGE_SOURCES_MYSQL_USERNAME=root PIO_STORAGE_SOURCES_MYSQL_PASSWORD=root This is how the pio-env.sh.template looks like. And again when I visited the actionml site, it suggests that I do have to have ELASTICSEARCH. but prediction.io site doesn't tells us the same. Which one should I follow and where would I find the current working version of installation guide. I actually wanaa use prediction.io in my production shortly after I implemented in local. Please help me, thank you very much for your help, I appreciate it so much. Vaghawan On Thu, Mar 23, 2017 at 9:27 PM, Pat Ferrel <[email protected]> wrote: > Since PIO has moved to Apache, the namespace of PIO code changed and so > all templates need to be updated. None of the ones in https://github.com/ > PredictionIO/ > <https://github.com/PredictionIO/template-scala-parallel-universal-recommendation> > will > work with Apache PIO. For the upgraded UR see: https://github.com/ > actionml/universal-recommender Docs for the UR are here: > http://actionml.com/docs/ur > > Also look on the Template gallery page here for a description of template > status. Some have not been moved to the new namespace and converted to run > with PIO but this is pretty easy to do yourself. http://predictionio. > incubator.apache.org/gallery/template-gallery/ > > user_id, product_id and purchase_date is all you need to use any > recommender. If you plan to gather other events in the future, use the UR. > As far as item or user based recommendations, the UR will give either based > on the query with the same data and model, as some others will do. The UR > allows you to mix both types in a single query, which may be useful with > small amounts of individual user data. > > Also the accepted wisdom about this it to put item-based recs on item > detail pages, and user-based recs elsewhere, when you don’t have an item to > base recs on, or in another placement on any page. > > You can have many different placements of recs in any page by changing the > queries. This is how Netflix gets rows and rows of specialized recs for > different things all based on the same data. The UR queries are quite > flexible. > > > On Mar 23, 2017, at 7:08 AM, Vaghawan Ojha <[email protected]> wrote: > > Hi, > > I've been trying to deploy a recommendation system using > https://github.com/PredictionIO/template-scala-parallel-universal- > recommendation. > > I've purchase history of user something like this: > user_id, product_id and purchase_date, so I will be using user_id and > product_id to determine the recommendation. I'm not sure if I would be able > to customize the default even parameter. > > Do you have any suggestions like which template would be more suitable for > my problem. I don't have data like rating or view state, I only have data > about user and product they purchased. I need something like item based > similarity as well as user based item similarity. > > Any help would be great > > Thank you > Vaghawan > >
