AWS Big Data Blog
Category: Amazon EMR
Build a Concurrent Data Orchestration Pipeline Using Amazon EMR and Apache Livy
In this post, we explore orchestrating a Spark data pipeline on Amazon EMR using Apache Livy and Apache Airflow, we create a simple Airflow DAG to demonstrate how to run spark jobs concurrently, and we see how Livy helps to hide the complexity to submit spark jobs via REST by using optimal EMR resources.
Exploratory data analysis of genomic datasets using ADAM and Mango with Apache Spark on Amazon EMR
In this post, we describe how to set up and run ADAM and Mango on Amazon EMR. We demonstrate how you can use these tools in an interactive notebook environment to explore the 1000 Genomes dataset, which is publicly available in Amazon S3 as a public dataset.
Encrypt data in transit using a TLS custom certificate provider with Amazon EMR
Many enterprises have highly regulated policies around cloud security. Those policies might be even more restrictive for Amazon EMR where sensitive data is processed. EMR provides security configurations that allow you to set up encryption for data at rest stored on Amazon S3 and local Amazon EBS volumes. It also allows the setup of Transport […]
Best practices for resizing and automatic scaling in Amazon EMR
In this post, I detail how EMR clusters resize, and I present some best practices for getting the maximum benefit and resulting cost savings for your own cluster through this feature.
Build a blockchain analytic solution with AWS Lambda, Amazon Kinesis, and Amazon Athena
In this post, we’ll show you how to deploy an Ethereum blockchain using the AWS Blockchain Templates, deploy a smart contract, and build a serverless analytics pipeline for that contract based around AWS Lambda, Amazon Kinesis, and Amazon Athena.
Orchestrate Apache Spark applications using AWS Step Functions and Apache Livy
In this post, I’ll show you how to use AWS Step Functions to orchestrate your Spark jobs that are running on Amazon EMR.
Analyze data in Amazon DynamoDB using Amazon SageMaker for real-time prediction
I’ll describe how to read the DynamoDB backup file format in Data Pipeline, how to convert the objects in S3 to a CSV format that Amazon ML can read, and I’ll show you how to schedule regular exports and transformations using Data Pipeline.
Getting started: Training resources for Big Data on AWS
Whether you’ve just signed up for your first AWS account or you’ve been with us for some time, there’s always something new to learn as our services evolve to meet the ever-changing needs of our customers. To help ensure you’re set up for success as you build with AWS, we put together this quick reference guide for Big Data training and resources available here on the AWS site.
How to migrate a Hue database from an existing Amazon EMR cluster
This post describes the step-by-step process for migrating the Hue database from an existing EMR cluster.
Easily manage table metadata for Presto running on Amazon EMR using the AWS Glue Data Catalog
In this post, we will explore how the AWS Glue Data Catalog addresses discoverability and manageability for table metadata for Presto on Amazon EMR.









