Amazon Elastic MapReduce is an Amazon Web Services (AWS) tool for big data processing and analysis.
Amazon EMR drew inspiration from Apache Hadoop, a Java-based programming framework that supports large amounts of data in a limited computer setup. Analyzing data becomes much easier, and even business intelligence workloads get simplified and broken down with this tool. Amazon EMR is also used to transform and shift large amounts of data in and out of other AWS databases, for example, the Amazon Simple Storage Service (Amazon S3) and Amazon DynamoDB.
Benefits of EMR
- It’s easy to use: EMR takes care of difficult tasks like node provisioning, infrastructure setup, Hadoop configuration as well as cluster tuning so that the users don’t have to endure the headache of sorting these things out on their own.
- It costs less: The pricing for the EMR is simple and predictable. It is charged based on a pay per instance rate for every second used and has a one-minute minimum charge. A 10-node EMR cluster with apps such as Apache Spark and Apache Hive can be launched for as little as $0.15 per hour.
- Elastic: Provisioning hundreds or thousands of compute instances to process data becomes easier with the EMR. We can increase or decrease the number of instances as per our needs either manually or automatically using Auto Scaling, which is a feature that manages cluster sizes based on utilization.
- It’s reliable: EMR is tuned for the cloud, so it will constantly be checking in to your cluster. It has the ability to reattempt failed tasks and replace poorly performing instances. EMR will make sure to provide the latest software, which is the most stable to carry out its functions.
- Secure and Flexible: EMR can configure EC2 firewall settings that control the network access to instances and launch clusters in an Amazon Virtual Private Cloud (VPC). Even though it does all this for the user, the user will still have complete control over the cluster. They can have access to every instance and can easily install additional applications as well as customize every cluster with bootstrap actions.