Isbn: 9786208118808 - hadoop distributed file system: koneru lakshmaiah education foundation (7 resultados)

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New. In English.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 52 pp. Englisch.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -\*Hadoop Basics\* is a comprehensive guide to understanding Hadoop, a powerful framework for processing large-scale data. The book begins by introducing Hadoop's core components: the Hadoop Distributed File System (HDFS) and MapReduce, which together enable scalable and fault-tolerant data storage and processing. It explains the architecture of Hadoop, including the master-slave model where the NameNode manages metadata and DataNodes store actual data. The book covers setting up Hadoop clusters in both pseudo-distributed and fully distributed modes. It also delves into key Hadoop ecosystem tools like Apache Hive and Apache Pig for data querying and analysis. Additionally, it explores best practices for data management, including data ingestion and storage strategies. The guide provides practical examples and hands-on exercises to help readers gain experience in Hadoop operations. Overall, \*Hadoop Basics\* offers a solid foundation for anyone looking to harness the power of Hadoop for big data processing.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - \*Hadoop Basics\* is a comprehensive guide to understanding Hadoop, a powerful framework for processing large-scale data. The book begins by introducing Hadoop's core components: the Hadoop Distributed File System (HDFS) and MapReduce, which together enable scalable and fault-tolerant data storage and processing. It explains the architecture of Hadoop, including the master-slave model where the NameNode manages metadata and DataNodes store actual data. The book covers setting up Hadoop clusters in both pseudo-distributed and fully distributed modes. It also delves into key Hadoop ecosystem tools like Apache Hive and Apache Pig for data querying and analysis. Additionally, it explores best practices for data management, including data ingestion and storage strategies. The guide provides practical examples and hands-on exercises to help readers gain experience in Hadoop operations. Overall, \*Hadoop Basics\* offers a solid foundation for anyone looking to harness the power of Hadoop for big data processing.…