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Item #:
26218863
Graph Algorithms: Practical Examples in Apache Spark and Neo4j
82% of respondents would recommend this to a friend
Item #:
26218863
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What Stands Out
Hands-on Approach
Offers practical examples that facilitate real-world application of graph algorithms, ensuring readers can implement solutions effectively using Apache Spark and Neo4j.
Comprehensive Coverage
Covers a wide range of graph algorithms and techniques, allowing readers to understand both fundamental concepts and advanced applications in data analysis.
Dual Technology Focus
Integrates two powerful technologies, Apache Spark and Neo4j, enabling users to leverage both platforms' strengths in data processing and graph databases.
Product Details
| Publisher | O'Reilly Media |
| Publication date | May 26, 2019 |
| Edition | 1st |
| Language | English |
| Print length | 265 pages |
| ISBN-10 | 1492047686 |
| ISBN-13 | 978-1492047681 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 7 x 0.75 x 9.25 inches (17.8 x 1.9 x 23.5 cm) |
Who Should Buy?
-
Data Scientists
Ideal for data scientists looking to implement graph algorithms using Apache Spark and Neo4j for data analysis.
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Software Engineers
Beneficial for software engineers focusing on graph data structures and their implementation in real-world applications.
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University Students
A great resource for university students studying data science or software engineering, enhancing their practical knowledge.
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Beginners in Data Science
Not suitable for beginners who have no prior knowledge of graph algorithms or programming concepts.
Product Description
Graph Algorithms: Practical Examples in Apache Spark and Neo4j
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Intelligence & Semantics Editorial Review
This book provides a decent overview of the use of graph databases and the types of questions each algorithm can answer. It lacks detailed descriptions of the algorithms and applications, and the lack of a bibliography is frustrating. However, the authors are experts in the field and the book is well written and edited. Overall, it is a useful but somewhat frustrating resource for understanding graph algorithms.
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Pros
- Decent overview of graph databases and their applications
- Written by authorities in the field
- Well written and edited
- Clear introduction and explanation of key concepts
Cons
- Lacks detailed algorithm descriptions
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