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Hands On Data and Hadoop 3

Track :

Programming

Lessons no : 6

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What will you learn in this course?
  • Master configuring Hadoop 3 for scalable big data storage and processing using HDFS and cluster management techniques
  • Implement data replication, fault tolerance, and data integrity strategies in Hadoop 3 environments for reliable big data storage
  • Optimize Hadoop 3 HDFS performance for large datasets, including block size tuning and data locality considerations
  • Develop skills to troubleshoot and resolve common Hadoop 3 HDFS issues related to data corruption, node failures, and network disruptions
  • Apply best practices for securing Hadoop 3 clusters, including data encryption, access controls, and user authentication
  • Design and implement efficient data ingestion and management workflows using Hadoop 3 for big data analytics

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Lessons | 6


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HDFS is made for handling large files by dividing them into blocks, replicating them, and storing them in the different cluster nodes. Thus, its ability to be highly fault-tolerant and reliable. HDFS is designed to store large datasets in the range of gigabytes or terabytes, or even petabytes .