國立虎尾科技大學 |

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

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Big Data SMACK/ by Raul Estrada, Isaac Ruiz.
Reminder of title:	A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka /
Author:	Estrada, Raul.
other author:	Ruiz, Isaac.
Description:	XXV, 264 p. 74 illus., 52 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Big data. -
Online resource:	https://doi.org/10.1007/978-1-4842-2175-4
ISBN:	9781484221754

Big Data SMACK = A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka /
Estrada, Raul.

Big Data SMACKA Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka /[electronic resource] :by Raul Estrada, Isaac Ruiz. - 1st ed. 2016. - XXV, 264 p. 74 illus., 52 illus. in color.online resource.

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.

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.

ISBN: 9781484221754

Standard No.: 10.1007/978-1-4842-2175-4doiSubjects--Topical Terms:

981821
Big data.

LC Class. No.: QA76.9.B45

Dewey Class. No.: 005.7

Big Data SMACK = A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka /
LDR:02804nam a22003855i 4500 001 972043
003 DE-He213
005 20200701224238.0
007 cr nn 008mamaa
008 201211s2016 xxu| s |||| 0|eng d
020 $a 9781484221754 $9 978-1-4842-2175-4
024 7 $a 10.1007/978-1-4842-2175-4 $2 doi
035 $a 978-1-4842-2175-4
050 4 $a QA76.9.B45
072 7 $a UN $2 bicssc
072 7 $a COM021000 $2 bisacsh
072 7 $a UN $2 thema
082 0 4 $a 005.7 $2 23
100 1 $a Estrada, Raul. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1114131
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.
250 $a 1st ed. 2016.
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 Big data. $3 981821
650 0 $a Database management. $3 557799
650 0 $a Data structures (Computer science). $3 680370
650 1 4 $a Big Data. $3 1017136
650 2 4 $a Database Management. $3 669820
650 2 4 $a Data Structures. $3 669824
700 1 $a Ruiz, Isaac. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1114132
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9781484221747
776 0 8 $i Printed edition: $z 9781484221761
856 4 0 $u https://doi.org/10.1007/978-1-4842-2175-4
912 $a ZDB-2-CWD
912 $a ZDB-2-SXPC
950 $a Professional and Applied Computing (SpringerNature-12059)
950 $a Professional and Applied Computing (R0) (SpringerNature-43716)