LEADER 03448nam 22005655 450 001 9910254753703321 005 20200701224238.0 010 $a1-4842-2175-3 024 7 $a10.1007/978-1-4842-2175-4 035 $a(CKB)3710000000873213 035 $a(DE-He213)978-1-4842-2175-4 035 $a(MiAaPQ)EBC4701681 035 $a(CaSebORM)9781484221754 035 $a(PPN)195514327 035 $a(EXLCZ)993710000000873213 100 $a20160929d2016 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBig Data SMACK$b[electronic resource] $eA Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka /$fby Raul Estrada, Isaac Ruiz 205 $a1st ed. 2016. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2016. 215 $a1 online resource (XXV, 264 p. 74 illus., 52 illus. in color.) 300 $aIncludes index. 311 $a1-4842-2174-5 327 $aPart 1. Introduction -- Chapter 1. Big Data, Big Problems -- Chapter 2. Big Data, Big Solutions -- Part 2. Playing SMACK -- Chapter 3. The Language: Scala -- Chapter 4. The Model: Akka -- Chapter 5. Storage. Apache Cassandra -- Chapter 6. The View -- Chapter 7. The Manager: Apache Mesos -- Chapter 8. The Broker: Apache Kafka -- Part 3. Improving SMACK -- Chapter 9. Fast Data Patterns -- Chapter 10. Big Data Pipelines -- Chapter 11. Glossary. 330 $aIntegrate full-stack open-source fast data pipeline architecture and choose the correct technology?Spark, Mesos, Akka, Cassandra, and Kafka (SMACK)?in every layer. Fast data is becoming a requirement for many enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases organizations need more than one paradigm to perform efficient analyses. Big Data SMACK explains each technology and, more importantly, how to integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples. The book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by each technology. This book covers the five main concepts of data pipeline architecture and how to integrate, replace, and reinforce every layer: The engine: Apache Spark The container: Apache Mesos The model: Akka< The storage: Apache Cassandra The broker: Apache Kafka. 606 $aBig data 606 $aDatabase management 606 $aData structures (Computer science) 606 $aBig Data$3https://scigraph.springernature.com/ontologies/product-market-codes/I29120 606 $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024 606 $aData Structures$3https://scigraph.springernature.com/ontologies/product-market-codes/I15017 615 0$aBig data. 615 0$aDatabase management. 615 0$aData structures (Computer science). 615 14$aBig Data. 615 24$aDatabase Management. 615 24$aData Structures. 676 $a005.7 700 $aEstrada$b Raul$4aut$4http://id.loc.gov/vocabulary/relators/aut$0961533 702 $aRuiz$b Isaac$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bUMI 801 1$bUMI 906 $aBOOK 912 $a9910254753703321 996 $aBig Data SMACK$92179926 997 $aUNINA