Amazon food analyzer

The goal of this task is to analyze and transform the > 500.000 reviews from Amazon. Please go to Kaggle.com and download (please take the 300MB csv file): https://www.kaggle.com/snap/amazon-fine-food-reviews

Task description

Finding 1000 most active users (profile names)
Finding 1000 most commented food items (item ids).
Finding 1000 most used words in the reviews
We want to translate all the reviews using Google Translate API. You can send up to 1000 characters per HTTP call. API has 200ms average response time. How to do it efficiently and cost effective (you pay for API calls and we have concurrency limits - 100 requests in parallel max) - please mock the calls to google translate API.

Result to be printed of point: 1,2,3 to standard output sorted alphabetically and executes point 4 to mocked endpoint (when launched with the argument ‘translate=true’)

Requirements

Using full multi core CPU power.
Memory limitation - 500MB of RAM. (Using Xmx500m VM option).

Technologies used

Akka
Commons CSV

How to build

Use gradlew ot gradlew.bat script to build project. See more at https://docs.gradle.org/current/userguide/gradle_wrapper.html.
Run application jar with main class com.dzidzoiev.amazonreviews.Invoker.

Program arguments

Path to file
Number of items to process
Parameter ‘translate=true’ - translate reviews (mocked)

Memory consumption

Analyzed with jconsole