FUNDAMENTALS OF COMPUTER

Detailed explanation-1: -By using the EMR File System (EMRFS) on your Amazon EMR cluster, you can leverage Amazon S3 as your data layer for Hadoop. Amazon S3 is highly scalable, low cost, and designed for durability, making it a great data store for big data processing.

Detailed explanation-2: -It is a fully managed application with single sign-on, fully managed Jupyter Notebooks, automated infrastructure provisioning, and the ability to debug jobs without logging into the AWS Console or cluster.

Detailed explanation-3: -Amazon EMR (previously called Amazon Elastic MapReduce) is a managed cluster platform that simplifies running big data frameworks, such as Apache Hadoop and Apache Spark, on AWS to process and analyze vast amounts of data.

Detailed explanation-4: -Amazon EMR is a managed service that lets you process and analyze large datasets using the latest versions of big data processing frameworks such as Apache Hadoop, Spark, HBase, and Presto on fully customizable clusters.

Detailed explanation-5: -Create and configure an Amazon S3 bucket Amazon EMR uses the AWS SDK for Java with Amazon S3 to store input data, log files, and output data. Amazon S3 refers to these storage locations as buckets. Buckets have certain restrictions and limitations to conform with Amazon S3 and DNS requirements.