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Showing posts with the label YARN on HADOOP 2.0

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Step-by-Step Guide to Creating an AWS RDS Database Instance

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 Amazon Relational Database Service (AWS RDS) makes it easy to set up, operate, and scale a relational database in the cloud. Instead of managing servers, patching OS, and handling backups manually, AWS RDS takes care of the heavy lifting so you can focus on building applications and data pipelines. In this blog, we’ll walk through how to create an AWS RDS instance , key configuration choices, and best practices you should follow in real-world projects. What is AWS RDS? AWS RDS is a managed database service that supports popular relational engines such as: Amazon Aurora (MySQL / PostgreSQL compatible) MySQL PostgreSQL MariaDB Oracle SQL Server With RDS, AWS manages: Database provisioning Automated backups Software patching High availability (Multi-AZ) Monitoring and scaling Prerequisites Before creating an RDS instance, make sure you have: An active AWS account Proper IAM permissions (RDS, EC2, VPC) A basic understanding of: ...
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Apache Yarn to Manage Resources a Solution

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Apache Hadoop is one of the most popular tools for big data processing. It has been successfully deployed in production by many companies for several years.  Though Hadoop is considered a reliable, scalable, and cost-effective solution, it is constantly being improved by a large community of developers. As a result, the 2.0 version offers several revolutionary features, including Yet Another Resource Negotiator (YARN), HDFS Federation, and a highly available NameNode, which make the Hadoop cluster much more efficient, powerful, and reliable.  Apache Yarn Apache Hadoop 2.0 includes YARN, which separates the resource management and processing components. The YARN-based architecture is not constrained to MapReduce. New developmens in Hadoop 2.0 Architecture with YARN:  ResourceManager instead of a cluster manager  ApplicationMaster instead of a dedicated and short-lived JobTracker  NodeManager instead of TaskTracker  A distributed application inst...
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