This can provide an advantage over a single multi-purpose but possibly sub-optimal cluster. This type of architecture is a common strategy that many AWS customers chose is to run multiple clusters geared towards different workloads. The architecture below shows how you can have multiple types of clusters for different purposes all pointing to the same source of truth residing in S3. We will mention several of the features that are useful for SparkR throughout this post, but readers less familiar with EMR’s unique feature set may also want to review the features available in Amazon EMR. It integrates with many AWS services, allowing you to lower cost with Spot instances, easily resize your cluster, and leverage security controls using IAM roles and the AWS Key Management Service. The diagram of SparkR below is provided as a reference, but this video provides an overview of what is depicted.Ĭhoosing Amazon EMR as your platform automates much of the work associated with setting up and configuring a Spark cluster. In this blog post, we introduce you running R with the Apache SparkR project on Amazon EMR. SparkR is an R package that allows you to integrate complex statistical analysis with large datasets. This post is co-authored by Gopal Wunnava, a Senior Consultant with AWS Professional Services. Christopher Crosbie is a Healthcare and Life Science Solutions Architect with Amazon Web Services.
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