Amazon EMR cluster

Amazon EMR enables rapid setup of scalable clusters for big data processing using frameworks like Spark

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Before launching an EMR cluster, you must prepare your application, input data, and storage (typically an S3 bucket in the same region)

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Data is stored in Amazon S3 using EMRFS, and bucket names must follow AWS naming conventions

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You can launch an EMR cluster via the AWS Management Console or AWS CLI, specifying Spark as the application

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Cluster configuration includes setting release version, instance type/count, permissions, and log storage location

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IAM roles (EMR_DefaultRole, EMR_EC2_DefaultRole) are required for cluster operation and can be created with the AWS CLI

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After creation, monitor cluster status as it transitions from STARTING to RUNNING to WAITING

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Security groups must be configured to allow SSH access to the master node, ideally restricted to trusted IPs

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SSH into the master node to access logs or submit jobs; avoid public SSH access for security

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Use the AWS CLI for advanced management, including cluster creation, status checks, and SSH connections

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