Explain Hadoop Framework

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              Explain Hadoop Framework

 

Hadoop is an open-source framework designed to process and store large amounts of data across clusters of commodity hardware. The Apache Software Foundation created it, and it is widely used in big data applications. The framework is built to handle the challenges of working with massive datasets that are too large to be efficiently processed using traditional computing methods.

Hadoop consists of several core components:

  1. Hadoop Distributed File System (HDFS): This is the storage component of Hadoop. It divides large files into smaller blocks and stores multiple copies of those blocks across different machines in a cluster. This redundancy ensures data availability and fault tolerance.
  2. MapReduce: MapReduce is a programming model and processing engine that allows developers to process and analyze data in parallel across the cluster. It involves two main steps: the “map” step, where data is processed and transformed into key-value pairs, and the “reduce” step, where the processed data is aggregated and analyzed.
  3. YARN (Yet Another Resource Negotiator): YARN is a resource management layer that manages and allocates resources to different applications running on the Hadoop cluster. It allows multiple processing frameworks (including MapReduce) to share resources effectively.
  4. Hadoop Common: This component includes libraries and utilities supporting other Hadoop modules. It contains libraries and APIs for file management, security, and other standard functionalities.

Hadoop’s architecture and distributed nature make it suitable for processing large-scale data by parallelizing tasks across multiple nodes in a cluster. This results in improved performance and scalability compared to traditional monolithic systems.

To ensure that emails sent in bulk using Hadoop-related tools do not go to spam, you should follow best practices for email deliverability, such as setting up proper sender authentication (SPF, DKIM, DMARC), managing a clean email list, avoiding spammy content, and using reputable email service providers. Additionally, you can monitor and analyze email delivery metrics to ensure your emails reach the intended recipients’ inboxes.

Hadoop Training Demo Day 1 Video:

 
You can find more information about Hadoop Training in this Hadoop Docs Link

 

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