AWS Big Data Blog

Category: Amazon EMR

Submitting User Applications with spark-submit

Francisco Oliveira is a consultant with AWS Professional Services Customers starting their big data journey often ask for guidelines on how to submit user applications to Spark running on Amazon EMR. For example, customers ask for guidelines on how to size memory and compute resources available to their applications and the best resource allocation model […]

Turning Amazon EMR into a Massive Amazon S3 Processing Engine with Campanile

Michael Wallman is a senior consultant with AWS ProServ Have you ever had to copy a huge Amazon S3 bucket to another account or region? Or create a list based on object name or size? How about mapping a function over millions of objects? Amazon EMR to the rescue! EMR allows you to deploy large […]

Running an External Zeppelin Instance using S3 Backed Notebooks with Spark on Amazon EMR

Dominic Murphy is an Enterprise Solution Architect with Amazon Web Services Apache Zeppelin is an open source GUI which creates interactive and collaborative notebooks for data exploration using Spark. You can use Scala, Python, SQL (using Spark SQL), or HiveQL to manipulate data and quickly visualize results. Zeppelin notebooks can be shared among several users, […]

Using BlueTalon with Amazon EMR

This is a guest post by Pratik Verma, Founder and Chief Product Officer at BlueTalon. Leonid Fedotov, Senior Solution Architect at BlueTalon, also contributed to this post. Amazon Elastic MapReduce (Amazon EMR) makes it easy to quickly and cost-effectively process vast amounts of data in the cloud. EMR gets used for log, financial, fraud, and […]

Integrating Amazon Kinesis, Amazon S3 and Amazon Redshift with Cascading on Amazon EMR

This is a guest post by Ryan Desmond, Solutions Architect at Concurrent. Concurrent is an AWS Advanced Technology Partner. With Amazon Kinesis developers can quickly store, collate and access large, distributed data streams such as access logs, click streams and IoT data in real-time. The question then becomes, how can we access and leverage this […]

How Expedia Implemented Near Real-time Analysis of Interdependent Datasets

This is a guest post by Stephen Verstraete, a manager at Pariveda Solutions. Pariveda Solutions is an AWS Premier Consulting Partner. Common patterns exist for batch processing and real-time processing of Big Data. However, we haven’t seen patterns that allow us to process batches of dependent data in real-time. Expedia’s marketing group needed to analyze […]

Large-Scale Machine Learning with Spark on Amazon EMR

This is a guest post by Jeff Smith, Data Engineer at Intent Media. Intent Media, in their own words: “Intent Media operates a platform for advertising on commerce sites.  We help online travel companies optimize revenue on their websites and apps through sophisticated data science capabilities. On the data team at Intent Media, we are […]

Test drive two big data scenarios from the ‘Building a Big Data Platform on AWS’ bootcamp

Matt Yanchyshyn is a Sr. Manager for AWS Solutions Architecture AWS offers a number of events during the year such as our annual AWS re:Invent conference, the AWS Summit series, the AWS Pop-up Loft, and a variety of roadshows. All of these provide opportunities for AWS customers to attend talks focused on big data and […]