LEADER 04154nam 2200493 450 001 9910157559603321 005 20170119041210.0 035 $a(CKB)3710000000984973 035 $a(MiAaPQ)EBC4773719 035 $a(CaSebORM)9781786467201 035 $a(PPN)220202885 035 $a(EXLCZ)993710000000984973 100 $a20170301h20162016 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aFast data processing systems with SMACK stack $ecombine the incredible powers of Spark, Mesos, Akka, Cassandra, and Kafka to build data processing platforms that can take on even the hardest of your data troubles /$fRaul Estrada 205 $a1st edition 210 1$aBirmingham, England ;$aMumbai, India :$cPackt Publishing,$d2016. 210 4$dİ2016 215 $a1 online resource (370 pages) $cillustrations 300 $aIncludes index. 311 $a1-78646-720-8 311 $a1-78646-806-9 330 $aCombine the incredible powers of Spark, Mesos, Akka, Cassandra, and Kafka to build data processing platforms that can take on even the hardest of your data troubles! About This Book This highly practical guide shows you how to use the best of the big data technologies to solve your response-critical problems Learn the art of making cheap-yet-effective big data architecture without using complex Greek-letter architectures Use this easy-to-follow guide to build fast data processing systems for your organization Who This Book Is For If you are a developer, data architect, or a data scientist looking for information on how to integrate the Big Data stack architecture and how to choose the correct technology in every layer, this book is what you are looking for. What You Will Learn Design and implement a fast data Pipeline architecture Think and solve programming challenges in a functional way with Scala Learn to use Akka, the actors model implementation for the JVM Make on memory processing and data analysis with Spark to solve modern business demands Build a powerful and effective cluster infrastructure with Mesos and Docker Manage and consume unstructured and No-SQL data sources with Cassandra Consume and produce messages in a massive way with Kafka In Detail SMACK is an open source full stack for big data architecture. It is a combination of Spark, Mesos, Akka, Cassandra, and Kafka. This stack is the newest technique developers have begun to use to tackle critical real-time analytics for big data. This highly practical guide will teach you how to integrate these technologies to create a highly efficient data analysis system for fast data processing. We'll start off with an introduction to SMACK and show you when to use it. First you'll get to grips with functional thinking and problem solving using Scala. Next you'll come to understand the Akka architecture. Then you'll get to know how to improve the data structure architecture and optimize resources using Apache Spark. Moving forward, you'll learn how to perform linear scalability in databases with Apache Cassandra. You'll grasp the high throughput distributed messaging systems using Apache Kafka. We'll show you how to build a cheap but effective cluster infrastructure with Apache Mesos. Finally, you will deep dive into the different aspect of SMACK using a few case studies. By the end of the book, you will be able to integrate all the components of the SMACK stack and use them together to ach... 606 $aElectronic data processing$xDistributed processing$xManagement 606 $aData structures (Computer science) 606 $aDatabase management 606 $aBig data 615 0$aElectronic data processing$xDistributed processing$xManagement. 615 0$aData structures (Computer science) 615 0$aDatabase management. 615 0$aBig data. 676 $a004.36 700 $aEstrada$b Raul$0961533 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910157559603321 996 $aFast data processing systems with SMACK stack$92861786 997 $aUNINA