Big Data SMACK A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka /

Integrate 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 cr...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Estrada, Raul (Συγγραφέας), Ruiz, Isaac (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berkeley, CA : Apress : Imprint: Apress, 2016.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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001 978-1-4842-2175-4
003 DE-He213
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020 |a 9781484221754  |9 978-1-4842-2175-4 
024 7 |a 10.1007/978-1-4842-2175-4  |2 doi 
040 |d GrThAP 
100 1 |a Estrada, Raul.  |e author. 
245 1 0 |a Big Data SMACK  |h [electronic resource] :  |b A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka /  |c by Raul Estrada, Isaac Ruiz. 
264 1 |a Berkeley, CA :  |b Apress :  |b Imprint: Apress,  |c 2016. 
300 |a XXV, 264 p. 74 illus., 52 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
505 0 |a Part 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. 
520 |a Integrate 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. 
650 0 |a Computer science. 
650 0 |a Data structures (Computer science). 
650 0 |a Database management. 
650 1 4 |a Computer Science. 
650 2 4 |a Big Data. 
650 2 4 |a Database Management. 
650 2 4 |a Data Structures. 
700 1 |a Ruiz, Isaac.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9781484221747 
856 4 0 |u http://dx.doi.org/10.1007/978-1-4842-2175-4  |z Full Text via HEAL-Link 
912 |a ZDB-2-CWD 
950 |a Professional and Applied Computing (Springer-12059)