語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Large-scale graph processing using A...
~
Sakr, Sherif.
FindBook
Google Book
Amazon
博客來
Large-scale graph processing using Apache Giraph
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Large-scale graph processing using Apache Giraph/ by Sherif Sakr ... [et al.].
其他作者:
Sakr, Sherif.
出版者:
Cham :Springer International Publishing : : 2016.,
面頁冊數:
xxv, 197 p. :ill., digital ;24 cm.
內容註:
1. Introduction -- 2. Getting started with Giraph -- 3. Giraph-In-Action: Implementing Popular Graph Algorithms using Giraph -- 4. Giraph Programming Optimizations: Tips and Tricks -- 5. Similar Systems to Giraph -- 6. Conclusions.
Contained By:
Springer eBooks
標題:
Graph algorithms. -
電子資源:
http://dx.doi.org/10.1007/978-3-319-47431-1
ISBN:
9783319474311
Large-scale graph processing using Apache Giraph
Large-scale graph processing using Apache Giraph
[electronic resource] /by Sherif Sakr ... [et al.]. - Cham :Springer International Publishing :2016. - xxv, 197 p. :ill., digital ;24 cm.
1. Introduction -- 2. Getting started with Giraph -- 3. Giraph-In-Action: Implementing Popular Graph Algorithms using Giraph -- 4. Giraph Programming Optimizations: Tips and Tricks -- 5. Similar Systems to Giraph -- 6. Conclusions.
This book takes its reader on a journey through Apache Giraph, a popular distributed graph processing platform designed to bring the power of big data processing to graph data. Designed as a step-by-step self-study guide for everyone interested in large-scale graph processing, it describes the fundamental abstractions of the system, its programming models and various techniques for using the system to process graph data at scale, including the implementation of several popular and advanced graph analytics algorithms. The book is organized as follows: Chapter 1 starts by providing a general background of the big data phenomenon and a general introduction to the Apache Giraph system, its abstraction, programming model and design architecture. Next, chapter 2 focuses on Giraph as a platform and how to use it. Based on a sample job, even more advanced topics like monitoring the Giraph application lifecycle and different methods for monitoring Giraph jobs are explained. Chapter 3 then provides an introduction to Giraph programming, introduces the basic Giraph graph model and explains how to write Giraph programs. In turn, Chapter 4 discusses in detail the implementation of some popular graph algorithms including PageRank, connected components, shortest paths and triangle closing. Chapter 5 focuses on advanced Giraph programming, discussing common Giraph algorithmic optimizations, tunable Giraph configurations that determine the system's utilization of the underlying resources, and how to write a custom graph input and output format. Lastly, chapter 6 highlights two systems that have been introduced to tackle the challenge of large scale graph processing, GraphX and GraphLab, and explains the main commonalities and differences between these systems and Apache Giraph. This book serves as an essential reference guide for students, researchers and practitioners in the domain of large scale graph processing. It offers step-by-step guidance, with several code examples and the complete source code available in the related github repository. Students will find a comprehensive introduction to and hands-on practice with tackling large scale graph processing problems using the Apache Giraph system, while researchers will discover thorough coverage of the emerging and ongoing advancements in big graph processing systems.
ISBN: 9783319474311
Standard No.: 10.1007/978-3-319-47431-1doiSubjects--Topical Terms:
596326
Graph algorithms.
LC Class. No.: QA166.245
Dewey Class. No.: 511.5
Large-scale graph processing using Apache Giraph
LDR
:03535nmm a2200325 a 4500
001
2084055
003
DE-He213
005
20170106123701.0
006
m d
007
cr nn 008maaau
008
170820s2016 gw s 0 eng d
020
$a
9783319474311
$q
(electronic bk.)
020
$a
9783319474304
$q
(paper)
024
7
$a
10.1007/978-3-319-47431-1
$2
doi
035
$a
978-3-319-47431-1
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA166.245
072
7
$a
UN
$2
bicssc
072
7
$a
UMT
$2
bicssc
072
7
$a
COM021000
$2
bisacsh
082
0 4
$a
511.5
$2
23
090
$a
QA166.245
$b
.L322 2016
245
0 0
$a
Large-scale graph processing using Apache Giraph
$h
[electronic resource] /
$c
by Sherif Sakr ... [et al.].
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2016.
300
$a
xxv, 197 p. :
$b
ill., digital ;
$c
24 cm.
505
0
$a
1. Introduction -- 2. Getting started with Giraph -- 3. Giraph-In-Action: Implementing Popular Graph Algorithms using Giraph -- 4. Giraph Programming Optimizations: Tips and Tricks -- 5. Similar Systems to Giraph -- 6. Conclusions.
520
$a
This book takes its reader on a journey through Apache Giraph, a popular distributed graph processing platform designed to bring the power of big data processing to graph data. Designed as a step-by-step self-study guide for everyone interested in large-scale graph processing, it describes the fundamental abstractions of the system, its programming models and various techniques for using the system to process graph data at scale, including the implementation of several popular and advanced graph analytics algorithms. The book is organized as follows: Chapter 1 starts by providing a general background of the big data phenomenon and a general introduction to the Apache Giraph system, its abstraction, programming model and design architecture. Next, chapter 2 focuses on Giraph as a platform and how to use it. Based on a sample job, even more advanced topics like monitoring the Giraph application lifecycle and different methods for monitoring Giraph jobs are explained. Chapter 3 then provides an introduction to Giraph programming, introduces the basic Giraph graph model and explains how to write Giraph programs. In turn, Chapter 4 discusses in detail the implementation of some popular graph algorithms including PageRank, connected components, shortest paths and triangle closing. Chapter 5 focuses on advanced Giraph programming, discussing common Giraph algorithmic optimizations, tunable Giraph configurations that determine the system's utilization of the underlying resources, and how to write a custom graph input and output format. Lastly, chapter 6 highlights two systems that have been introduced to tackle the challenge of large scale graph processing, GraphX and GraphLab, and explains the main commonalities and differences between these systems and Apache Giraph. This book serves as an essential reference guide for students, researchers and practitioners in the domain of large scale graph processing. It offers step-by-step guidance, with several code examples and the complete source code available in the related github repository. Students will find a comprehensive introduction to and hands-on practice with tackling large scale graph processing problems using the Apache Giraph system, while researchers will discover thorough coverage of the emerging and ongoing advancements in big graph processing systems.
650
0
$a
Graph algorithms.
$3
596326
650
0
$a
Graph theory
$x
Data processing.
$3
655277
650
1 4
$a
Computer Science.
$3
626642
650
2 4
$a
Database Management.
$3
891010
650
2 4
$a
Big Data/Analytics.
$3
2186785
650
2 4
$a
Data Structures.
$3
891009
700
1
$a
Sakr, Sherif.
$3
2209883
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-47431-1
950
$a
Computer Science (Springer-11645)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9313304
電子資源
11.線上閱覽_V
電子書
EB QA166.245 .L322 2016
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入