Jupyter Notebooks gives big data customers an easy way to leverage open-source Apache Spark in Amazon EMR for data science, interactive analytics, and prototype jobs before bringing them to production. In this tech talk, we show you how to use Amazon EMR Notebooks, an easier platform for data engineers, data scientists, and developers, which helps them increase productivity as they collaborate on different workloads and clusters.

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Using Amazon EMR Notebooks to
develop Apache Spark applications
Radhika Ravirala
Specialist solutions architect
Amazon EMR, Amazon Athena, and AWS Glue
A D B 2 0 2

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Agenda
• Amazon EMR Notebooks overview
• Why should I use it?
• How it works – Demo!
• Accessing notebooks
• Q&A

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Amazon EMR Notebooks
A managed analytics environment based on Jupyter notebooks
Amazon EMR clusters
User Amazon Simpler
Storage Service (Amazon
S3) bucket
AWS Management Console
for EMR
Amazon EMR–managed notebook
based on Jupyter notebook
Users
Customer
virtual private
cloud (VPC)
Amazon EMR
VPC

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As a data scientist or developer
• Build applications, prepare and visualize data, collaborate with peers, and run interactive analysis through
PySpark, Spark SQL, Spark R, and Scala
• Create multiple notebooks instantly from the console, attach them to a minimum 1-node EMR cluster and
immediately start experimenting with Apache Spark
• Monitor the progress of your job from within the notebook with the integrated Spark monitor
• Visualize your results in rich graphical plots using the preinstalled open-source libraries from Anaconda
• Detach your notebook from clusters and re-attach to a different cluster suitable for your workload
• Durably persist your work to Amazon S3 and share with others; easily retrieve saved work from the
console

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As an IT administrator
• Easily setup a multi-tenant cluster for your data scientists and developers and make most use of your EMR
cluster
• No need to deploy, maintain, and upgrade software or notebook instances
• Provide secure access to notebooks without providing multiuser access to the master node
• Safely terminate your cluster without fear of losing notebooks
• Set up fine-grained access control to notebooks and clusters through AWS Identity and Access
Management (IAM) policies
• Track and audit your notebook users by enforcing user impersonation

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How do I access EMR notebooks?
• Log into the AWS Management Console for Amazon EMR
• Create a IAM user policy allowing permissions to use notebooks
• Use the default service role for notebooks with an AWS managed policy or provide your custom service
role with custom policies for the notebook
• Launch or have a running cluster with Amazon EMR release 5.18.0 or later with Spark and Livy installed
• Provide an Amazon S3 path in the same region as your Amazon EMR cluster
• Click on “create notebook” button to open notebook user interface

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Thank you!
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Radhika Ravirala