Big data analytics with Hadoop 3 : build highly effective analytics solutions to gain valuable insight into your big data
Enregistré dans:
| Auteur principal: | |
|---|---|
| Support: | E-Book |
| Langue: | Anglais |
| Publié: |
Birmingham :
Packt Publishing,
2018.
|
| Autres localisations: | Voir dans le Sudoc |
| Résumé: | Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples. Once you have taken a tour of Hadoop 3's latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases. By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly. |
| Accès en ligne: | Accès à l'E-book |
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| 100 | 1 | |a Alla, Sridhar. |4 aut. |e Auteur | |
| 245 | 1 | 0 | |a Big data analytics with Hadoop 3 : |b build highly effective analytics solutions to gain valuable insight into your big data |c Sridhar Alla. |
| 256 | |a Données textuelles. | ||
| 264 | 1 | |a Birmingham : |b Packt Publishing, |c 2018. | |
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| 500 | |a Titre provenant de la page de titre du document numérique. | ||
| 500 | |a La pagination de l'édition imprimée correspondante est de 471 p. | ||
| 506 | |a L'accès complet à la ressource est réservé aux usagers des établissements qui en ont fait l'acquisition | ||
| 516 | |a Données textuelles (1 fichier PDF) | ||
| 520 | |a Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples. Once you have taken a tour of Hadoop 3's latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases.<br>By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly. | ||
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