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This fast-paced guide helps you learn about Apache Hadoop 3 and its ecosystem. It covers setting up, configuring, and starting with Hadoop to gain insights from large datasets, as well as working with its components like MapReduce, HDFS, and YARN. The book introduces the main technical topics, beginning with an overview of big data and Hadoop, before guiding you through setting up a pseudo Hadoop development environment and a multi-node enterprise cluster. You'll explore how the parallel programming paradigm, particularly MapReduce, addresses complex data processing challenges. Key aspects of the big data software development lifecycle, including quality assurance, performance, administration, and monitoring, are also discussed. Additionally, the book delves into the Hadoop ecosystem and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Advanced topics include real-time streaming with Apache Storm and data analytics using Apache Spark. By the end, you'll be proficient in various Hadoop 3 cluster configurations. This book is ideal for aspiring Big Data professionals and existing Hadoop users looking to understand the new features of Hadoop 3, with Java programming knowledge being a plus.
Acquisto del libro
Apache Hadoop 3 Quick Start Guide, Hrishikesh Vijay Karambelkar
- Lingua
- Pubblicato
- 2018
- Rilegatura
- (In brossura),
- Condizioni del libro
- In buone condizioni
- Prezzo
- 17,99 €
Metodi di pagamento
Ancora nessuna valutazione.
- Titolo
- Apache Hadoop 3 Quick Start Guide
- Sottotitolo
- Learn About Big Data Processing And Analytics - English Edition
- Lingua
- Inglese
- Editore
- Packt Publishing
- Pubblicato
- 2018
- Formato
- In brossura
- Pagine
- 220
- ISBN10
- 1788999835
- ISBN13
- 9781788999830
- Serie
- Descrizione
- This fast-paced guide helps you learn about Apache Hadoop 3 and its ecosystem. It covers setting up, configuring, and starting with Hadoop to gain insights from large datasets, as well as working with its components like MapReduce, HDFS, and YARN. The book introduces the main technical topics, beginning with an overview of big data and Hadoop, before guiding you through setting up a pseudo Hadoop development environment and a multi-node enterprise cluster. You'll explore how the parallel programming paradigm, particularly MapReduce, addresses complex data processing challenges. Key aspects of the big data software development lifecycle, including quality assurance, performance, administration, and monitoring, are also discussed. Additionally, the book delves into the Hadoop ecosystem and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Advanced topics include real-time streaming with Apache Storm and data analytics using Apache Spark. By the end, you'll be proficient in various Hadoop 3 cluster configurations. This book is ideal for aspiring Big Data professionals and existing Hadoop users looking to understand the new features of Hadoop 3, with Java programming knowledge being a plus.