Language:
English
繁體中文
Help
圖資館首頁
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Next-generation big dataa practical ...
~
Quinto, Butch.
Next-generation big dataa practical guide to Apache Kudu, Impala, and Spark /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Next-generation big databy Butch Quinto.
Reminder of title:
a practical guide to Apache Kudu, Impala, and Spark /
Author:
Quinto, Butch.
Published:
Berkeley, CA :Apress :2018.
Description:
xxiii, 557 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Big data.
Online resource:
http://dx.doi.org/10.1007/978-1-4842-3147-0
ISBN:
9781484231470$q(electronic bk.)
Next-generation big dataa practical guide to Apache Kudu, Impala, and Spark /
Quinto, Butch.
Next-generation big data
a practical guide to Apache Kudu, Impala, and Spark /[electronic resource] :by Butch Quinto. - Berkeley, CA :Apress :2018. - xxiii, 557 p. :ill., digital ;24 cm.
Chapter 1: Next-Generation Big Data -- Chapter 2: Introduction to Kudu -- Chapter 3: Introduction to Impala -- Chapter 4: High Performance Data Analysis with Impala and Kudu -- Chapter 5: Introduction to Spark -- Chapter 6: High-Performance Data Processing with Spark and Kudu -- Chapter 7: Batch and Real-Time Data Ingestion and Processing -- Chapter 8: Big Data Warehousing -- Chapter 9: Big Data Visualization and Data Wrangling -- Chapter 10: Distributed In-Memory Big Data Computing -- Chapter 11: Big Data Governance and Management -- Chapter 12: Big Data in the Cloud -- Chapter 13: Big Data Case Studies.
Utilize this practical and easy-to-follow guide to modernize traditional enterprise data warehouse and business intelligence environments with next-generation big data technologies. Next-Generation Big Data takes a holistic approach, covering the most important aspects of modern enterprise big data. The book covers not only the main technology stack but also the next-generation tools and applications used for big data warehousing, data warehouse optimization, real-time and batch data ingestion and processing, real-time data visualization, big data governance, data wrangling, big data cloud deployments, and distributed in-memory big data computing. Finally, the book has an extensive and detailed coverage of big data case studies from Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard. What You'll Learn: Install Apache Kudu, Impala, and Spark to modernize enterprise data warehouse and business intelligence environments, complete with real-world, easy-to-follow examples, and practical advice Integrate HBase, Solr, Oracle, SQL Server, MySQL, Flume, Kafka, HDFS, and Amazon S3 with Apache Kudu, Impala, and Spark Use StreamSets, Talend, Pentaho, and CDAP for real-time and batch data ingestion and processing Utilize Trifacta, Alteryx, and Datameer for data wrangling and interactive data processing Turbocharge Spark with Alluxio, a distributed in-memory storage platform Deploy big data in the cloud using Cloudera Director Perform real-time data visualization and time series analysis using Zoomdata, Apache Kudu, Impala, and Spark Understand enterprise big data topics such as big data governance, metadata management, data lineage, impact analysis, and policy enforcement, and how to use Cloudera Navigator to perform common data governance tasks Implement big data use cases such as big data warehousing, data warehouse optimization, Internet of Things, real-time data ingestion and analytics, complex event processing, and scalable predictive modeling Study real-world big data case studies from innovative companies, including Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard.
ISBN: 9781484231470$q(electronic bk.)
Standard No.: 10.1007/978-1-4842-3147-0doiSubjects--Uniform Titles:
Spark (Electronic resource : Apache Software Foundation)
Subjects--Topical Terms:
609582
Big data.
LC Class. No.: QA76.9.B45 / Q568 2018
Dewey Class. No.: 005.7
Next-generation big dataa practical guide to Apache Kudu, Impala, and Spark /
LDR
:03689nmm a2200289 a 4500
001
540911
003
DE-He213
005
20190115113937.0
006
m d
007
cr nn 008maaau
008
190308s2018 cau s 0 eng d
020
$a
9781484231470$q(electronic bk.)
020
$a
9781484231463$q(paper)
024
7
$a
10.1007/978-1-4842-3147-0
$2
doi
035
$a
978-1-4842-3147-0
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.9.B45
$b
Q568 2018
082
0 4
$a
005.7
$2
23
090
$a
QA76.9.B45
$b
Q7 2018
100
1
$a
Quinto, Butch.
$3
819449
245
1 0
$a
Next-generation big data
$h
[electronic resource] :
$b
a practical guide to Apache Kudu, Impala, and Spark /
$c
by Butch Quinto.
260
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2018.
300
$a
xxiii, 557 p. :
$b
ill., digital ;
$c
24 cm.
505
0
$a
Chapter 1: Next-Generation Big Data -- Chapter 2: Introduction to Kudu -- Chapter 3: Introduction to Impala -- Chapter 4: High Performance Data Analysis with Impala and Kudu -- Chapter 5: Introduction to Spark -- Chapter 6: High-Performance Data Processing with Spark and Kudu -- Chapter 7: Batch and Real-Time Data Ingestion and Processing -- Chapter 8: Big Data Warehousing -- Chapter 9: Big Data Visualization and Data Wrangling -- Chapter 10: Distributed In-Memory Big Data Computing -- Chapter 11: Big Data Governance and Management -- Chapter 12: Big Data in the Cloud -- Chapter 13: Big Data Case Studies.
520
$a
Utilize this practical and easy-to-follow guide to modernize traditional enterprise data warehouse and business intelligence environments with next-generation big data technologies. Next-Generation Big Data takes a holistic approach, covering the most important aspects of modern enterprise big data. The book covers not only the main technology stack but also the next-generation tools and applications used for big data warehousing, data warehouse optimization, real-time and batch data ingestion and processing, real-time data visualization, big data governance, data wrangling, big data cloud deployments, and distributed in-memory big data computing. Finally, the book has an extensive and detailed coverage of big data case studies from Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard. What You'll Learn: Install Apache Kudu, Impala, and Spark to modernize enterprise data warehouse and business intelligence environments, complete with real-world, easy-to-follow examples, and practical advice Integrate HBase, Solr, Oracle, SQL Server, MySQL, Flume, Kafka, HDFS, and Amazon S3 with Apache Kudu, Impala, and Spark Use StreamSets, Talend, Pentaho, and CDAP for real-time and batch data ingestion and processing Utilize Trifacta, Alteryx, and Datameer for data wrangling and interactive data processing Turbocharge Spark with Alluxio, a distributed in-memory storage platform Deploy big data in the cloud using Cloudera Director Perform real-time data visualization and time series analysis using Zoomdata, Apache Kudu, Impala, and Spark Understand enterprise big data topics such as big data governance, metadata management, data lineage, impact analysis, and policy enforcement, and how to use Cloudera Navigator to perform common data governance tasks Implement big data use cases such as big data warehousing, data warehouse optimization, Internet of Things, real-time data ingestion and analytics, complex event processing, and scalable predictive modeling Study real-world big data case studies from innovative companies, including Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard.
630
0 0
$a
Spark (Electronic resource : Apache Software Foundation)
$3
750546
650
0
$a
Big data.
$3
609582
650
0
$a
Data mining.
$3
184440
650
0
$a
Computer science.
$3
199325
650
1 4
$a
Computer Science.
$3
212513
650
2 4
$a
Big Data.
$3
760530
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer eBooks
856
4 0
$u
http://dx.doi.org/10.1007/978-1-4842-3147-0
950
$a
Professional and Applied Computing (Springer-12059)
based on 0 review(s)
ALL
電子館藏
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
000000160668
電子館藏
1圖書
電子書
EB QA76.9.B45 Q7 2018 2018
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Multimedia file
http://dx.doi.org/10.1007/978-1-4842-3147-0
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login