Data-intensive systems : principles and fundamentals using Hadoop and Spark /
Saved in:
Author / Creator: | Wiktorski, Tomasz, author. |
---|---|
Imprint: | Cham, Switzerland : Springer, [2019] |
Description: | 1 online resource |
Language: | English |
Series: | Advanced information and knowledge processing Advanced information and knowledge processing. |
Subject: | |
Format: | E-Resource Book |
URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/11780870 |
ISBN: | 3030046036 9783030046040 3030046044 9783030046033 9783030046026 3030046028 |
---|---|
Digital file characteristics: | text file PDF |
Notes: | Includes bibliographical references. Online resource; title from digital title page (viewed on February 14, 2019). |
Summary: | Data-intensive systems are a technological building block supporting Big Data and Data Science applications. This book familiarizes readers with core concepts that they should be aware of before continuing with independent work and the more advanced technical reference literature that dominates the current landscape. The material in the book is structured following a problem-based approach. This means that the content in the chapters is focused on developing solutions to simplified, but still realistic problems using data-intensive technologies and approaches. The reader follows one reference scenario through the whole book, that uses an open Apache dataset. The origins of this volume are in lectures from a master?s course in Data-intensive Systems, given at the University of Stavanger. Some chapters were also a base for guest lectures at Purdue University and Lodz University of Technology. |
Other form: | Print version: Wiktorski, Tomasz. Data-intensive systems. Cham, Switzerland : Springer, [2019] 3030046028 9783030046026 |
Standard no.: | 10.1007/978-3-030-04603-3 |
Similar Items
-
Practical data science with Hadoop and Spark : designing and building effective analytics at scale /
by: Mendelevitch, Ofer
Published: (2017) -
Big data analytics with Hadoop 3 : build highly effective analytics solutions to gain valuable insight into your big data /
by: Alla, Sridhar
Published: (2018) -
Advanced analytics with Spark /
by: Ryza, Sandy
Published: (2015) -
Spark cookbook : over 60 recipes on Spark, covering Spark Core, Spark SQL, Spark Streaming, MLib, and GraphX libraries /
by: Yadav, Rishi
Published: (2015) -
Apache Spark 2.x cookbook : Cloud-ready recipes to do analytics and data science on Apache Spark /
by: Yadav, Rishi
Published: (2017)