國立虎尾科技大學 |

Complete Guide to Open Source Big Data Stack

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Complete Guide to Open Source Big Data Stack / by Michael Frampton.
作者:	Frampton, Michael.
面頁冊數:	XX, 365 p. 167 illus., 131 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Big data. -
電子資源:	https://doi.org/10.1007/978-1-4842-2149-5
ISBN:	9781484221495

Complete Guide to Open Source Big Data Stack
Frampton, Michael.

Complete Guide to Open Source Big Data Stack [electronic resource] /by Michael Frampton. - 1st ed. 2018. - XX, 365 p. 167 illus., 131 illus. in color.online resource.

Chapter 1: The Big Data Stack Overview -- Chapter 2: Cloud Storage -- Chapter 3: Apache Brooklyn -- Chapter 4: Apache Mesos -- Chapter 5: Stack Storage Options -- Chapter 6: Processing -- Chapter 7: Streaming -- Chapter 8: Frameworks -- Chapter 9: Visualization -- Chapter 10: The Big Data Stack -- .

See a Mesos-based big data stack created and the components used. You will use currently available Apache full and incubating systems. The components are introduced by example and you learn how they work together. In the Complete Guide to Open Source Big Data Stack, the author begins by creating a private cloud and then installs and examines Apache Brooklyn. After that, he uses each chapter to introduce one piece of the big data stack—sharing how to source the software and how to install it. You learn by simple example, step by step and chapter by chapter, as a real big data stack is created. The book concentrates on Apache-based systems and shares detailed examples of cloud storage, release management, resource management, processing, queuing, frameworks, data visualization, and more. What You’ll Learn: Install a private cloud onto the local cluster using Apache cloud stack Source, install, and configure Apache: Brooklyn, Mesos, Kafka, and Zeppelin See how Brooklyn can be used to install Mule ESB on a cluster and Cassandra in the cloud Install and use DCOS for big data processing Use Apache Spark for big data stack data processing.

ISBN: 9781484221495

Standard No.: 10.1007/978-1-4842-2149-5doiSubjects--Topical Terms:

981821
Big data.

LC Class. No.: QA76.9.B45

Dewey Class. No.: 005.7

Complete Guide to Open Source Big Data Stack
LDR:02804nam a22003975i 4500 001 998670
003 DE-He213
005 20200702093833.0
007 cr nn 008mamaa
008 201225s2018 xxu| s |||| 0|eng d
020 $a 9781484221495 $9 978-1-4842-2149-5
024 7 $a 10.1007/978-1-4842-2149-5 $2 doi
035 $a 978-1-4842-2149-5
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 Frampton, Michael. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1065439
245 1 0 $a Complete Guide to Open Source Big Data Stack $h [electronic resource] / $c by Michael Frampton.
250 $a 1st ed. 2018.
264 1 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2018.
300 $a XX, 365 p. 167 illus., 131 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 Chapter 1: The Big Data Stack Overview -- Chapter 2: Cloud Storage -- Chapter 3: Apache Brooklyn -- Chapter 4: Apache Mesos -- Chapter 5: Stack Storage Options -- Chapter 6: Processing -- Chapter 7: Streaming -- Chapter 8: Frameworks -- Chapter 9: Visualization -- Chapter 10: The Big Data Stack -- .
520 $a See a Mesos-based big data stack created and the components used. You will use currently available Apache full and incubating systems. The components are introduced by example and you learn how they work together. In the Complete Guide to Open Source Big Data Stack, the author begins by creating a private cloud and then installs and examines Apache Brooklyn. After that, he uses each chapter to introduce one piece of the big data stack—sharing how to source the software and how to install it. You learn by simple example, step by step and chapter by chapter, as a real big data stack is created. The book concentrates on Apache-based systems and shares detailed examples of cloud storage, release management, resource management, processing, queuing, frameworks, data visualization, and more. What You’ll Learn: Install a private cloud onto the local cluster using Apache cloud stack Source, install, and configure Apache: Brooklyn, Mesos, Kafka, and Zeppelin See how Brooklyn can be used to install Mule ESB on a cluster and Cassandra in the cloud Install and use DCOS for big data processing Use Apache Spark for big data stack data processing.
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
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9781484221488
776 0 8 $i Printed edition: $z 9781484221501
776 0 8 $i Printed edition: $z 9781484246689
856 4 0 $u https://doi.org/10.1007/978-1-4842-2149-5
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)