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Amazon EMR (previously known as Amazon Elastic MapReduce) is an Amazon Web Services (AWS) tool for big data processing and analysis. Amazon markets EMR as an expandable, low-configuration service that provides an alternative to running on-premises cluster computing.
EMRFS is an implementation of the Hadoop file system used for reading and writing regular files from Amazon EMR directly to Amazon S3.
Amazon EMR is based on Apache Hadoop, a Java-based programming framework that supports the processing of large data sets in a distributed computing environment.
Default Amazon EBS storage for instances Amazon EMR automatically attaches an Amazon EBS General Purpose SSD (gp2) 10 GB volume as the root device for its AMIs to enhance performance. In addition, for EC2 instances with EBS-only storage, Amazon EMR allocates Amazon EBS gp2 storage volumes to instances.
Amazon EMR uses an Amazon Linux Amazon Machine Image (AMI) to initialize Amazon EC2 instances when you create and launch a cluster.
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EMR File System (EMRFS) is an implementation of HDFS that Amazon EMR clusters typically use for reading and writing regular files from Amazon EMR directly to Amazon S3. You can use EMRFS when you read the dataset one time in each run.
The EMR File System (EMRFS) is an implementation of HDFS that all Amazon EMR clusters use for reading and writing regular files from Amazon EMR directly to Amazon S3. EMRFS provides the convenience of storing persistent data in Amazon S3 for use with Hadoop while also providing features like data encryption.
Step logs These logs are generated by the Amazon EMR service and contain information about the cluster and the results of each step. The log files are stored in /mnt/var/log/hadoop/steps/ directory on the primary node.

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