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Recommendation Engine - Streaming Component

Description

This repository contains the streaming component of the recommender engine. The component is written using Apache Spark.

The code in this repository has a simple structure. It does the following things:

  • Fetches streaming user reviews from Kafka.
  • Loads a learning model from a path specified in the arguments. (For the learning model, we use ALSModel.)
  • Generates recommendations for users by using the learning model.
  • Stores the generated recommendations in MongoDB.

Usage

Run

This component cannot be run by itself. In order to run this component, all of the project components must be run using docker-compose. See Recommender Engine - Docker Files

If you want to change the code and run, after you change the code do the following steps:

  • Go to the root directory of the repository.
  • Run sbt clean assembly
  • Get the recom-engine-docker repository from here.
  • Move the jar file that is created from target/scala-2.11/recom-engine-streaming-assembly-0.1.jar to images/spark/master/target under recom-engine-docker's root directory.
  • Go to the root diretory of recom-engine-docker and run the command docker-compose up.

Watch the Outputs

If you want to watch the outputs of the streaming, do the following steps:

  • First run all of the components with docker-compose.
  • Go to the worker's web page from http://localhost:8082.
  • In this page, you can see the running drivers, click stdout link of the streaming application, then you can watch the outputs of the application.

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