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
到查詢結果
[ subject:"SPARK (Electronic resource)" ]
切換:
標籤
|
MARC模式
|
ISBD
Guide to high performance distribute...
~
Srinivasa, K.G.
FindBook
Google Book
Amazon
博客來
Guide to high performance distributed computing = case studies with Hadoop, Scalding and Spark /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Guide to high performance distributed computing/ by K.G. Srinivasa, Anil Kumar Muppalla.
其他題名:
case studies with Hadoop, Scalding and Spark /
作者:
Srinivasa, K.G.
其他作者:
Muppalla, Anil Kumar.
出版者:
Cham :Springer International Publishing : : 2015.,
面頁冊數:
xvii, 304 p. :ill., digital ;24 cm.
內容註:
Part I: Programming Fundamentals of High Performance Distributed Computing -- Introduction -- Getting Started with Hadoop -- Getting Started with Spark -- Programming Internals of Scalding and Spark -- Part II: Case studies using Hadoop, Scalding and Spark -- Case Study I: Data Clustering using Scalding and Spark -- Case Study II: Data Classification using Scalding and Spark -- Case Study III: Regression Analysis using Scalding and Spark -- Case Study IV: Recommender System using Scalding and Spark.
Contained By:
Springer eBooks
標題:
High performance computing - Congresses. -
電子資源:
http://dx.doi.org/10.1007/978-3-319-13497-0
ISBN:
9783319134970 (electronic bk.)
Guide to high performance distributed computing = case studies with Hadoop, Scalding and Spark /
Srinivasa, K.G.
Guide to high performance distributed computing
case studies with Hadoop, Scalding and Spark /[electronic resource] :by K.G. Srinivasa, Anil Kumar Muppalla. - Cham :Springer International Publishing :2015. - xvii, 304 p. :ill., digital ;24 cm. - Computer communications and networks,1617-7975. - Computer communications and networks..
Part I: Programming Fundamentals of High Performance Distributed Computing -- Introduction -- Getting Started with Hadoop -- Getting Started with Spark -- Programming Internals of Scalding and Spark -- Part II: Case studies using Hadoop, Scalding and Spark -- Case Study I: Data Clustering using Scalding and Spark -- Case Study II: Data Classification using Scalding and Spark -- Case Study III: Regression Analysis using Scalding and Spark -- Case Study IV: Recommender System using Scalding and Spark.
This timely text/reference describes the development and implementation of large-scale distributed processing systems using open source tools and technologies such as Hadoop, Scalding and Spark. Comprehensive in scope, the book presents state-of-the-art material on building high performance distributed computing systems, providing practical guidance and best practices as well as describing theoretical software frameworks. Topics and features: Describes the fundamentals of building scalable software systems for large-scale data processing in the new paradigm of high performance distributed computing Presents an overview of the Hadoop ecosystem, followed by step-by-step instruction on its installation, programming and execution Reviews the basics of Spark, including resilient distributed datasets, and examines Hadoop streaming and working with Scalding Provides detailed case studies on approaches to clustering, data classification and regression analysis Explains the process of creating a working recommender system using Scalding and Spark Supplies a complete list of supplementary source code and datasets at an associated website Fulfilling the need for both introductory material for undergraduate students of computer science and detailed discussions for software engineering professionals, this book will aid a broad audience to understand the esoteric aspects of practical high performance computing through its use of solved problems, research case studies and working source code. K.G. Srinivasa is Professor and Head of the Department of Computer Science and Engineering at M.S. Ramaiah Institute of Technology (MSRIT), Bangalore, India. His other publications include the Springer title Soft Computing for Data Mining Applications. Anil Kumar Muppalla is also a researcher at MSRIT.
ISBN: 9783319134970 (electronic bk.)
Standard No.: 10.1007/978-3-319-13497-0doiSubjects--Uniform Titles:
Apache Hadoop.
Subjects--Topical Terms:
1244541
High performance computing
--Congresses.
LC Class. No.: QA76.88
Dewey Class. No.: 004.11
Guide to high performance distributed computing = case studies with Hadoop, Scalding and Spark /
LDR
:03361nmm a2200325 a 4500
001
1995206
003
DE-He213
005
20150915141211.0
006
m d
007
cr nn 008maaau
008
151019s2015 gw s 0 eng d
020
$a
9783319134970 (electronic bk.)
020
$a
9783319134963 (paper)
024
7
$a
10.1007/978-3-319-13497-0
$2
doi
035
$a
978-3-319-13497-0
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.88
072
7
$a
UKN
$2
bicssc
072
7
$a
COM075000
$2
bisacsh
082
0 4
$a
004.11
$2
23
090
$a
QA76.88
$b
.S774 2015
100
1
$a
Srinivasa, K.G.
$3
2134520
245
1 0
$a
Guide to high performance distributed computing
$h
[electronic resource] :
$b
case studies with Hadoop, Scalding and Spark /
$c
by K.G. Srinivasa, Anil Kumar Muppalla.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2015.
300
$a
xvii, 304 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Computer communications and networks,
$x
1617-7975
505
0
$a
Part I: Programming Fundamentals of High Performance Distributed Computing -- Introduction -- Getting Started with Hadoop -- Getting Started with Spark -- Programming Internals of Scalding and Spark -- Part II: Case studies using Hadoop, Scalding and Spark -- Case Study I: Data Clustering using Scalding and Spark -- Case Study II: Data Classification using Scalding and Spark -- Case Study III: Regression Analysis using Scalding and Spark -- Case Study IV: Recommender System using Scalding and Spark.
520
$a
This timely text/reference describes the development and implementation of large-scale distributed processing systems using open source tools and technologies such as Hadoop, Scalding and Spark. Comprehensive in scope, the book presents state-of-the-art material on building high performance distributed computing systems, providing practical guidance and best practices as well as describing theoretical software frameworks. Topics and features: Describes the fundamentals of building scalable software systems for large-scale data processing in the new paradigm of high performance distributed computing Presents an overview of the Hadoop ecosystem, followed by step-by-step instruction on its installation, programming and execution Reviews the basics of Spark, including resilient distributed datasets, and examines Hadoop streaming and working with Scalding Provides detailed case studies on approaches to clustering, data classification and regression analysis Explains the process of creating a working recommender system using Scalding and Spark Supplies a complete list of supplementary source code and datasets at an associated website Fulfilling the need for both introductory material for undergraduate students of computer science and detailed discussions for software engineering professionals, this book will aid a broad audience to understand the esoteric aspects of practical high performance computing through its use of solved problems, research case studies and working source code. K.G. Srinivasa is Professor and Head of the Department of Computer Science and Engineering at M.S. Ramaiah Institute of Technology (MSRIT), Bangalore, India. His other publications include the Springer title Soft Computing for Data Mining Applications. Anil Kumar Muppalla is also a researcher at MSRIT.
630
0 0
$a
Apache Hadoop.
$3
2059708
630
0 0
$a
SPARK (Electronic resource)
$3
831456
650
0
$a
High performance computing
$v
Congresses.
$3
1244541
650
0
$a
Electronic data processing
$x
Distributed processing
$3
703843
650
1 4
$a
Computer Science.
$3
626642
650
2 4
$a
Computer Communication Networks.
$3
775497
650
2 4
$a
Programming Techniques.
$3
892496
650
2 4
$a
Data Mining and Knowledge Discovery.
$3
898250
650
2 4
$a
Artificial Intelligence (incl. Robotics)
$3
890894
650
2 4
$a
Image Processing and Computer Vision.
$3
891070
700
1
$a
Muppalla, Anil Kumar.
$3
2134521
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
830
0
$a
Computer communications and networks.
$3
1568371
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-13497-0
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
W9267908
電子資源
11.線上閱覽_V
電子書
EB QA76.88
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