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Practical Graph Analytics with Apache Giraph helps you build data mining and machine learning applications using the Apache Foundation’s Giraph framework for graph processing. This is the same framework as used by Facebook, Google, and other social media analytics operations to derive business value from vast amounts of interconnected data points.
Graphs arise in a wealth of data scenarios and describe the connections that are naturally formed in both digital and real worlds. Examples of such connections abound in online social networks such as Facebook and Twitter, among users who rate movies from services like Netflix and Amazon Prime, and are useful even in the context of biological networks for scientific research. Whether in the context of business or science, viewing data as connected adds value by increasing the amount of information available to be drawn from that data and put to use in generating new revenue or scientific opportunities.
Apache Giraph offers a simple yet flexible programming model targeted to graph algorithms and designed to scale easily to accommodate massive amounts of data. Originally developed at Yahoo!, Giraph is now a top top-level project at the Apache Foundation, and it enlists contributors from companies such as Facebook, LinkedIn, and Twitter. Practical Graph Analytics with Apache Giraph brings the power of Apache Giraph to you, showing how to harness the power of graph processing for your own data by building sophisticated graph analytics applications using the very same framework that is relied upon by some of the largest players in the industry today.
- Sales Rank: #2196910 in Books
- Published on: 2015-10-16
- Released on: 2015-09-09
- Original language: English
- Number of items: 1
- Dimensions: 10.00" h x .77" w x 7.00" l, 1.30 pounds
- Binding: Paperback
- 315 pages
About the Author
Roman Shaposhnik is a vice-president and one of the lead developers of Apache Bigtop, a 100% open source and community-driven big data management distribution built on top of Apache Hadoop. He has been working on making Hadoop ecosystem components more accessible and easier to use, and he has contributed to a wide array of Apache projects from Avro to Zookeeper. In addition to his day job building Data Fabric APIs at Pivotal Inc., Roman currently serves as a vice-president of Apache Incubator, helping exciting and new open source projects join the Apache family.
Most helpful customer reviews
0 of 0 people found the following review helpful.
Many example problems and solutions make this a great learning tool from start to end
By Audrey
If you have used (or attempted to use) Giraph you will know that it's not the easiest system to pick up and start getting your hands dirty. However, it is an extremely powerful tool that can be used to solve many interesting problems at scale. This book does a great job of taking you from the very beginning with simple, straightforward algorithms to more complex real-world applications and finally more advanced topics (e.g., data partitioning, out-of-core algorithms, running on the cloud, etc.). With this book you can start without knowing anything about Giraph or distributed graph processing systems in general (or even about graphs!) and learn how to solve many graph problems at scale.
There are several things that I find so appealing about this book. The main things are: (1) the _numerous_ examples with step-by-step illustrations that help you understand what exactly is happening during an algorithm, (2) the fact that the example applications are motivated by real-world problems (e.g., recommendation systems, pagerank, etc.) whose solutions can then serve as a building block for your personal applications, and (3) the example code that will allow you to quickly get your hands dirty and start playing with the tool.
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