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environment.yml
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environment.yml
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# ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
#
# Containerized Amazon Recommender System (CARS) Project
#
# Authors: Brianna Blain-Castelli, Nikkolas Irwin, Adam Cassell, and Andrew Munoz
# Date: 04/01/2020
# Purpose: Build a Big Data application using a Conda environment and Docker.
# Course: CS 636 Big Data Systems
# Project: CARS is an application that builds a recommender system from datasets provided by
# UCSD (see citation below).
#
# Dataset URL: https://nijianmo.github.io/amazon/index.html
#
# ***IMPORTANT*** You must download the dataset files for a particular category to your local machine yourself due
# to their size. As long as your dataset files are in the same directory as the Dockerfile, then
# they will be added to the volume and usable by the container as expected.
#
# ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
#
# Citation: Justifying recommendations using distantly-labeled reviews and fined-grained aspects
# Jianmo Ni, Jiacheng Li, Julian McAuley
# Empirical Methods in Natural Language Processing (EMNLP), 2019
# PDF: http://cseweb.ucsd.edu/~jmcauley/pdfs/emnlp19a.pdf
#
# ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
#
# Conda Environmental File: This file specifies our Conda environment for the Docker container.
#
# Top-Level Keys Explained:
# 1. name - Specifies the name of the Conda environment we will use for the containerized application. For our
# purposes, it it set to base, which is the default environment that is supplied when installing Conda.
#
# 2. channels - Specifies the locations where packages are stored that we will install dependencies from.
#
# 3. dependencies - Specifies the explicit dependencies that must be installed when the conda environment is
# created for our application.
#
# 4. prefix - Specifies the target directory for creating the environment (for our purposes this is in the
# container, but it could also be on the local file system.).
#
# ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
name: base
channels:
- defaults
- conda-forge
dependencies:
- plotly
- matplotlib
- pyspark
prefix: /opt/anaconda3/envs/base