文件名称：Big Data SMACKBig Data SMACK(Apress,2016)
文件大小：11.11MB
文件格式：PDF
更新时间：2019-11-24 14:09:28
Big Data SMACKBig Data SMACK
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.