Description Arguments Slots Examples
The core implementation of Recommender and furthermore
MyrrixRecommender that lies inside the Serving Layer.
This is the recommendation engine class.
The ServerRecommender has a local model, allowing it to
build recommendation models based on data which are
locally stored on your disk.
Next to the local
serving, it also allows to build recommendation models
based on data which is distributed on Hadoop. Special
out-of-the-box classes exists to let it run on CDH, AWS
and on Hadoop clusters. If you run the ServerRecommender
in a distributed mode, we assume that you have set up the
Computation layer already. This R package allows to
ingest new data, update the model, get recommendations
and similarities based on the recommendation engine which
is running.
bucket |
character string with the bucket that Serving Layer is using for instances |
instanceID |
character string with the instance ID that the Serving Layer is serving. May be 0 for local mode. |
localInputDir |
character string with the local input and model file directory |
partition |
integer with the partition number in a partitioned distributed mode. 0 if not partitioned. |
allPartitions |
reference to an object that can describe all partitions; only used to get their count (seee http://myrrix.com/docs/serving/javadoc/index.html) |
recommender
:A java object of class net.myrrix.online.ServerRecommender
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