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These are the Jupyter notebooks for the Big Data specialization in the Data Science Program.
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.ipynb_checkpoints
ServeStreams
checkpoint_TwitterApp
datasets
examples
Preparing Data for Streaming.ipynb
README.md
RFC with Spark in Batch Mode.ipynb
Spark Streaming.ipynb
Twitter streaming challenge.ipynb
rfc_spark_batch_02_26_19.ipynb

README.md

Student resources for Thinkful's Big Data with Spark

This repo contains the notebooks, datasets, and server code that you'll need for the Big Data with Spark specialization in Thinkful's data science program.

Fork this repo to your own GitHub account, and clone a local version on your machine.

Running this repo with Docker

The notebooks in this repo use Spark. To get a Spark instance running locally, you'll need to launch these notebooks within a Thinkful-made Docker container.

Use the following command to start the container, replacing /path/to/big-data-student-resources with the local path that corresponds to this repo on your machine:

docker run -d --rm -p 8888:8888 -v /path/to/big-data-student-resources:/home/ds/notebooks thinkfulstudent/pyspark:2.2.1

Go to localhost:8888/tree in your browser to access your notebooks.

For full instructions on setting up Docker, refer back to this assignment.

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