Hi, Yes I did that but still I get the same output, it's weird.
Thanks On Thu, Mar 23, 2017 at 10:00 PM, Marius Rabenarivo < [email protected]> wrote: > You have to change this section > > # 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 > > Put MYSQL in place of PGSQL > > 2017-03-23 20:07 GMT+04:00 Vaghawan Ojha <[email protected]>: > >> Hi, Thank you! >> >> I came into further more confusion here, actually I installed prediction >> IO version 0.10.0 from here http://predictionio.incub >> ator.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/action >>> ml/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-paralle >>> l-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 >>> >>> >> >
