Książka Big Data SMACK Raul Estrada

Big Data SMACK

A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka

Język: Angielski
Oprawa: Miękka
Wydawca: APress
Dostępność: Dostępna u dostawcy
Wysyłamy za 5-8 dni
158.20
This book is about how to integrate full-stack open source big data architecture and how to choose t...

Informacje o książce

Język
Angielski
Oprawa
Książka - Miękka
Data wydania
2016
strony
264
EAN
9781484221747
ISBN
1484221745
Enbook ID
13512768
Wydawca
Waga
582
Wymiary
332 x 180 x 18

Pełny opis

This book is about how to integrate full-stack open source big data architecture and how to choose the correct technology-Scala/Spark, Mesos, Akka, Cassandra, and Kafka-in every layer. Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large datasets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses.§§Big Data SMACK explains each of the full-stack technologies and, more importantly, how to best integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples in every situation. The book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by every technology. It covers the six main concepts of big data architecture and how integrate, replace, and reinforce every layer:§§The language: Scala§§The engine: Spark (SQL, MLib, Streaming, GraphX)§§The container: Mesos, Docker§§The view: Akka§§The storage: Cassandra§§The message broker: Kafka§§What you'll learn§§How to make big data architecture without using complex Greek letter architectures.§§How to build a cheap but effective cluster infrastructure.§§How to make queries, reports, and graphs that business demands.§§How to manage and exploit unstructured and No-SQL data sources.§§How use tools to monitor the performance of your architecture.§§How to integrate all technologies and decide which replace and which reinforce.§§Who This Book Is For§§This book is for developers, data architects, and data scientists looking for how to integrate the most successful big data open stack architecture and how to choose the correct technology in every layer.§§

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