yelp_dataset

---

Welcome to yelp dataset analysis

This is a spark application which reads in the yelp dataset published in json format json_dataset and runs some basic sql queries on top of it.

Executing the application:

1. Standalone sbt version:

To execute this, you will need scala and sbt installed on your system.

make run_local FILEPATH=<path_to_your_json_dataset.tar>

2. Docker version:

To execute docker version, only docker installation is needed on your system.

make run_docker FILEPATH=<path_to_your_json_dataset.tar>

Note: This takes looooooooong to build as sbt tries to download a lot of data.

3. Pull the image directly from docker hub (FASTEST)

This dataset should be your extracted jsons directory, i.e. it should look something like this:

$ ls dataset/
business.json  checkin.json  photos.json  review.json  tip.json  user.json

And then execute:

docker run -it --rm -v `pwd`/dataset:/lib/dataset  ansrivas/yelp_dataset:latest

Usage:

To run the application, execute make in the root of the project.

$ make
help:           Show available options with this Makefile
clean:          Clean removes any previous directories named "dataset" in present working directory
untar:          Untar the input .tar file to a predefined location
assembly:       Create an assembly (fat jar) from the scala project
run_local:      Run the fat jar after compilation and assembly LOCALLY
run_docker:     Run the fat jar after compilation and assembly via docker

TODOs:

• Create a docker-compose file for easy usage.
• Implement options to submit jar to an external spark-cluster.
• Allow configurations to be read from outside the assembly jar.

Contribution policy

Contributions via GitHub pull requests are gladly accepted from their original author. Along with any pull requests, please state that the contribution is your original work and that you license the work to the project under the project's open source license. Whether or not you state this explicitly, by submitting any copyrighted material via pull request, email, or other means you agree to license the material under the project's open source license and warrant that you have the legal authority to do so.

License

This code is open source software licensed under the Apache-2.0 license.