語系:
繁體中文
English
說明(常見問題)
圖資館首頁
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Pro Spark streamingthe zen of real-t...
~
Nabi, Zubair.
Pro Spark streamingthe zen of real-time analytics using Apache Spark /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Pro Spark streamingby Zubair Nabi.
其他題名:
the zen of real-time analytics using Apache Spark /
作者:
Nabi, Zubair.
出版者:
Berkeley, CA :Apress :2016.
面頁冊數:
xix, 230 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
標題:
Streaming technology (Telecommunications)
電子資源:
http://dx.doi.org/10.1007/978-1-4842-1479-4
ISBN:
9781484214794$q(electronic bk.)
Pro Spark streamingthe zen of real-time analytics using Apache Spark /
Nabi, Zubair.
Pro Spark streaming
the zen of real-time analytics using Apache Spark /[electronic resource] :by Zubair Nabi. - Berkeley, CA :Apress :2016. - xix, 230 p. :ill., digital ;24 cm.
Chapter 1: The Hitchhiker's Guide to Big Data -- Chapter 2: Introduction to Spark -- Chapter 3: DStreams: Realtime RDDs -- Chapter 4: High Velocity Streams: Parallelism and Other Stories -- Chapter 5: Real-time Route 66: Linking External Data Sources -- Chapter 6: The Art of Side Effects -- Chapter 7: Getting Ready for Prime Time -- Chapter 8: Real-time ETL and Analytics Magic -- Chapter 9: Machine Learning at Scale -- Chapter 10: Of Clouds, Lambdas, and Pythons.
Learn the right cutting-edge skills and knowledge to leverage Spark Streaming to implement a wide array of real-time, streaming applications. Pro Spark Streaming walks you through end-to-end real-time application development using real-world applications, data, and code. Taking an application-first approach, each chapter introduces use cases from a specific industry and uses publicly available datasets from that domain to unravel the intricacies of production-grade design and implementation. The domains covered in the book include social media, the sharing economy, finance, online advertising, telecommunication, and IoT. In the last few years, Spark has become synonymous with big data processing. DStreams enhance the underlying Spark processing engine to support streaming analysis with a novel micro-batch processing model. Pro Spark Streaming by Zubair Nabi will enable you to become a specialist of latency sensitive applications by leveraging the key features of DStreams, micro-batch processing, and functional programming. To this end, the book includes ready-to-deploy examples and actual code. Pro Spark Streaming will act as the bible of Spark Streaming. What You'll Learn: Spark Streaming application development and best practices Low-level details of discretized streams The application and vitality of streaming analytics to a number of industries and domains Optimization of production-grade deployments of Spark Streaming via configuration recipes and instrumentation using Graphite, collectd, and Nagios Ingestion of data from disparate sources including MQTT, Flume, Kafka, Twitter, and a custom HTTP receiver Integration and coupling with HBase, Cassandra, and Redis Design patterns for side-effects and maintaining state across the Spark Streaming micro-batch model Real-time and scalable ETL using data frames, SparkSQL, Hive, and SparkR Streaming machine learning, predictive analytics, and recommendations Meshing batch processing with stream processing via the Lambda architecture Who This Book Is For: The audience includes data scientists, big data experts, BI analysts, and data architects.
ISBN: 9781484214794$q(electronic bk.)
Standard No.: 10.1007/978-1-4842-1479-4doiSubjects--Uniform Titles:
Spark (Electronic resource : Apache Software Foundation)
Subjects--Topical Terms:
219176
Streaming technology (Telecommunications)
LC Class. No.: TK5105.386
Dewey Class. No.: 006.7876
Pro Spark streamingthe zen of real-time analytics using Apache Spark /
LDR
:03629nmm a2200337 a 4500
001
490890
003
DE-He213
005
20161202141047.0
006
m d
007
cr nn 008maaau
008
170118s2016 cau s 0 eng d
020
$a
9781484214794$q(electronic bk.)
020
$a
9781484214800$q(paper)
024
7
$a
10.1007/978-1-4842-1479-4
$2
doi
035
$a
978-1-4842-1479-4
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
TK5105.386
072
7
$a
JPP
$2
bicssc
072
7
$a
UB
$2
bicssc
072
7
$a
COM018000
$2
bisacsh
072
7
$a
POL017000
$2
bisacsh
082
0 4
$a
006.7876
$2
23
090
$a
TK5105.386
$b
.N116 2016
100
1
$a
Nabi, Zubair.
$3
750545
245
1 0
$a
Pro Spark streaming
$h
[electronic resource] :
$b
the zen of real-time analytics using Apache Spark /
$c
by Zubair Nabi.
260
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2016.
300
$a
xix, 230 p. :
$b
ill., digital ;
$c
24 cm.
505
0
$a
Chapter 1: The Hitchhiker's Guide to Big Data -- Chapter 2: Introduction to Spark -- Chapter 3: DStreams: Realtime RDDs -- Chapter 4: High Velocity Streams: Parallelism and Other Stories -- Chapter 5: Real-time Route 66: Linking External Data Sources -- Chapter 6: The Art of Side Effects -- Chapter 7: Getting Ready for Prime Time -- Chapter 8: Real-time ETL and Analytics Magic -- Chapter 9: Machine Learning at Scale -- Chapter 10: Of Clouds, Lambdas, and Pythons.
520
$a
Learn the right cutting-edge skills and knowledge to leverage Spark Streaming to implement a wide array of real-time, streaming applications. Pro Spark Streaming walks you through end-to-end real-time application development using real-world applications, data, and code. Taking an application-first approach, each chapter introduces use cases from a specific industry and uses publicly available datasets from that domain to unravel the intricacies of production-grade design and implementation. The domains covered in the book include social media, the sharing economy, finance, online advertising, telecommunication, and IoT. In the last few years, Spark has become synonymous with big data processing. DStreams enhance the underlying Spark processing engine to support streaming analysis with a novel micro-batch processing model. Pro Spark Streaming by Zubair Nabi will enable you to become a specialist of latency sensitive applications by leveraging the key features of DStreams, micro-batch processing, and functional programming. To this end, the book includes ready-to-deploy examples and actual code. Pro Spark Streaming will act as the bible of Spark Streaming. What You'll Learn: Spark Streaming application development and best practices Low-level details of discretized streams The application and vitality of streaming analytics to a number of industries and domains Optimization of production-grade deployments of Spark Streaming via configuration recipes and instrumentation using Graphite, collectd, and Nagios Ingestion of data from disparate sources including MQTT, Flume, Kafka, Twitter, and a custom HTTP receiver Integration and coupling with HBase, Cassandra, and Redis Design patterns for side-effects and maintaining state across the Spark Streaming micro-batch model Real-time and scalable ETL using data frames, SparkSQL, Hive, and SparkR Streaming machine learning, predictive analytics, and recommendations Meshing batch processing with stream processing via the Lambda architecture Who This Book Is For: The audience includes data scientists, big data experts, BI analysts, and data architects.
630
0 0
$a
Spark (Electronic resource : Apache Software Foundation)
$3
750546
650
0
$a
Streaming technology (Telecommunications)
$3
219176
650
0
$a
Big data.
$3
609582
650
1 4
$a
Computer Science.
$3
212513
650
2 4
$a
Computer Appl. in Administrative Data Processing.
$3
275283
650
2 4
$a
Data Mining and Knowledge Discovery.
$3
275288
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer eBooks
856
4 0
$u
http://dx.doi.org/10.1007/978-1-4842-1479-4
950
$a
Professional and Applied Computing (Springer-12059)
筆 0 讀者評論
全部
電子館藏
館藏
1 筆 • 頁數 1 •
1
條碼號
館藏地
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
000000128048
電子館藏
1圖書
電子書
EB TK5105.386 N116 2016
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
多媒體檔案
http://dx.doi.org/10.1007/978-1-4842-1479-4
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼
登入