語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Practical Apache Spark = Using the S...
~
SpringerLink (Online service)
Practical Apache Spark = Using the Scala API /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Practical Apache Spark/ by Subhashini Chellappan, Dharanitharan Ganesan.
其他題名:
Using the Scala API /
作者:
Chellappan, Subhashini.
其他作者:
Ganesan, Dharanitharan.
面頁冊數:
XVI, 280 p. 303 illus.online resource. :
Contained By:
Springer Nature eBook
標題:
Big data. -
電子資源:
https://doi.org/10.1007/978-1-4842-3652-9
ISBN:
9781484236529
Practical Apache Spark = Using the Scala API /
Chellappan, Subhashini.
Practical Apache Spark
Using the Scala API /[electronic resource] :by Subhashini Chellappan, Dharanitharan Ganesan. - 1st ed. 2018. - XVI, 280 p. 303 illus.online resource.
Work with Apache Spark using Scala to deploy and set up single-node, multi-node, and high-availability clusters. This book discusses various components of Spark such as Spark Core, DataFrames, Datasets and SQL, Spark Streaming, Spark MLib, and R on Spark with the help of practical code snippets for each topic. Practical Apache Spark also covers the integration of Apache Spark with Kafka with examples. You’ll follow a learn-to-do-by-yourself approach to learning – learn the concepts, practice the code snippets in Scala, and complete the assignments given to get an overall exposure. On completion, you’ll have knowledge of the functional programming aspects of Scala, and hands-on expertise in various Spark components. You’ll also become familiar with machine learning algorithms with real-time usage. You will: Discover the functional programming features of Scala Understand the complete architecture of Spark and its components Integrate Apache Spark with Hive and Kafka Use Spark SQL, DataFrames, and Datasets to process data using traditional SQL queries Work with different machine learning concepts and libraries using Spark's MLlib packages.
ISBN: 9781484236529
Standard No.: 10.1007/978-1-4842-3652-9doiSubjects--Topical Terms:
981821
Big data.
LC Class. No.: QA76.9.B45
Dewey Class. No.: 005.7
Practical Apache Spark = Using the Scala API /
LDR
:02503nam a22003855i 4500
001
989925
003
DE-He213
005
20200705092347.0
007
cr nn 008mamaa
008
201225s2018 xxu| s |||| 0|eng d
020
$a
9781484236529
$9
978-1-4842-3652-9
024
7
$a
10.1007/978-1-4842-3652-9
$2
doi
035
$a
978-1-4842-3652-9
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
Chellappan, Subhashini.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1211947
245
1 0
$a
Practical Apache Spark
$h
[electronic resource] :
$b
Using the Scala API /
$c
by Subhashini Chellappan, Dharanitharan Ganesan.
250
$a
1st ed. 2018.
264
1
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2018.
300
$a
XVI, 280 p. 303 illus.
$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
520
$a
Work with Apache Spark using Scala to deploy and set up single-node, multi-node, and high-availability clusters. This book discusses various components of Spark such as Spark Core, DataFrames, Datasets and SQL, Spark Streaming, Spark MLib, and R on Spark with the help of practical code snippets for each topic. Practical Apache Spark also covers the integration of Apache Spark with Kafka with examples. You’ll follow a learn-to-do-by-yourself approach to learning – learn the concepts, practice the code snippets in Scala, and complete the assignments given to get an overall exposure. On completion, you’ll have knowledge of the functional programming aspects of Scala, and hands-on expertise in various Spark components. You’ll also become familiar with machine learning algorithms with real-time usage. You will: Discover the functional programming features of Scala Understand the complete architecture of Spark and its components Integrate Apache Spark with Hive and Kafka Use Spark SQL, DataFrames, and Datasets to process data using traditional SQL queries Work with different machine learning concepts and libraries using Spark's MLlib packages.
650
0
$a
Big data.
$3
981821
650
0
$a
Open source software.
$3
561177
650
0
$a
Computer programming.
$3
527822
650
0
$a
Programming languages (Electronic computers).
$3
1127615
650
1 4
$a
Big Data.
$3
1017136
650
2 4
$a
Open Source.
$3
1113081
650
2 4
$a
Programming Languages, Compilers, Interpreters.
$3
669782
700
1
$a
Ganesan, Dharanitharan.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1211948
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9781484236512
776
0 8
$i
Printed edition:
$z
9781484236536
776
0 8
$i
Printed edition:
$z
9781484245866
856
4 0
$u
https://doi.org/10.1007/978-1-4842-3652-9
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)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入