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Amazon EMR

Distribute your data and processing across a Amazon EC2 instances using Hadoop
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What is Amazon EMR?

It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.
Amazon EMR is a tool in the Big Data as a Service category of a tech stack.

Who uses Amazon EMR?

137 companies reportedly use Amazon EMR in their tech stacks, including Netflix, Amazon, and

228 developers on StackShare have stated that they use Amazon EMR.
Public Decisions about Amazon EMR

Here are some stack decisions, common use cases and reviews by companies and developers who chose Amazon EMR in their tech stack.

I have to build a data processing application with an Apache Beam stack and Apache Flink runner on an Amazon EMR cluster. I saw some instability with the process and EMR clusters that keep going down. Here, the Apache Beam application gets inputs from Kafka and sends the accumulative data streams to another Kafka topic. Any advice on how to make the process more stable?

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Shared insights
AWS GlueAWS GlueAmazon EMRAmazon EMR

I use AWS Glue because I thought it was worth all they hype Fall 2018. However, you had to use Python 2.7 with no pandas support, and cold starts lasted as long as 15 minutes. Also, setting up a dev environment for iterative development was near impossible at the time.

It was a terrible experience for me. I recommend using Amazon EMR instead. Even talking with a friend that works at Amazon, they use EMR instead of Glue for internal spark workloads. Just because a company makes something doesn't mean they use that something :/

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Amazon EMR's Features

  • Elastic- Amazon EMR enables you to quickly and easily provision as much capacity as you need and add or remove capacity at any time. Deploy multiple clusters or resize a running cluster
  • Low Cost- Amazon EMR is designed to reduce the cost of processing large amounts of data. Some of the features that make it low cost include low hourly pricing, Amazon EC2 Spot integration, Amazon EC2 Reserved Instance integration, elasticity, and Amazon S3 integration.
  • Flexible Data Stores- With Amazon EMR, you can leverage multiple data stores, including Amazon S3, the Hadoop Distributed File System (HDFS), and Amazon DynamoDB.
  • Hadoop Tools- EMR supports powerful and proven Hadoop tools such as Hive, Pig, and HBase.

Amazon EMR Alternatives & Comparisons

What are some alternatives to Amazon EMR?
Amazon EC2
It is a web service that provides resizable compute capacity in the cloud. It is designed to make web-scale computing easier for developers.
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
Amazon DynamoDB
With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
Amazon Redshift
It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
Azure HDInsight
It is a cloud-based service from Microsoft for big data analytics that helps organizations process large amounts of streaming or historical data.
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Amazon EMR's Followers
352 developers follow Amazon EMR to keep up with related blogs and decisions.
sudheer kamboji
Gustavo Leonato
akash sharma
Srilakshmi Damineni
Edmund Johnson
John Smith
Xinhui Yan
Luke Gregerson
Jay Mehta
Sanghee Park