Summary
Over the course of this chapter, we have dived deep into a few popular big data applications available in EMR, how they are set up in EMR, and what additional configuration options or features you get when you integrate with Amazon S3. Then we provided an overview of the TensorFlow and MXNet applications, which are the machine learning and deep learning libraries available in EMR. These applications are the primary building blocks when you implement a data analytics pipeline using EMR.
Finally, we covered the different notebook options you have and how you can configure and use them for your interactive development.
That concludes this chapter! Hopefully, you have got a good overview of these distributed applications and are ready to dive deep into EMR cluster creation and configuration in the next chapter.
