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Big Data Analytics with Hadoop 3: Build highly effective analytics solutions to gain valuable insight into your big data
76% of respondents would recommend this to a friend
TJS 374
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Big Data Analytics with Hadoop 3 provides practical examples to learn Hadoop 3 for building high-performance analytics solutions seamlessly on-premise and on cloud
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What Stands Out
Информация о продукте
- Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud
- Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink
- Explore Hadoop 3 features along with HDFS, YARN, and MapReduce
- Utilize Hadoop with Apache Spark and Apache Flink for real-time data analytics and stream processing
- Set up a Hadoop cluster on AWS cloud and perform big data analytics using Elastic Map Reduce
- Targeted at individuals interested in building high-performance analytics solutions using Hadoop 3, with a basic understanding of Java programming
| Publisher | Packt Publishing |
| Publication date | May 31, 2018 |
| Language | English |
| Print length | 482 pages |
| ISBN-10 | 1788628845 |
| ISBN-13 | 978-1788628846 |
| Item Weight | 1.81 pounds (820 grams) |
| Dimensions | 7.5 x 1.09 x 9.25 inches (19.1 x 2.8 x 23.5 cm) |
Who Should Buy?
-
Data Scientists
Ideal for data scientists looking to leverage Hadoop for extensive big data analysis and insights.
-
Business Analysts
Business analysts will benefit from gaining deeper insights into data patterns and trends using Hadoop 3.
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IT Professionals
IT professionals seeking to enhance their skill set in big data technologies and Hadoop ecosystem applications.
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Beginner Users
Beginner users may find the advanced concepts and tools overwhelming without prior knowledge of big data.
ОПИСАНИЕ ТОВАРА
Big Data Analytics with Hadoop 3: Build highly effective analytics solutions to gain valuable insight into your big data
Вопросы и ответы клиентов
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вопрос:
What is required to read this book?
отвечать: A basic understanding of the Java programming language. -
вопрос:
What are the tools that can be integrated with Hadoop?
отвечать: R, Python, Apache Spark, and Apache Flink can be integrated with Hadoop. -
вопрос:
Is this book only for beginners in data analytics?
отвечать: No, it is also useful for those who want to build high-performance analytics solutions for their enterprise or business using Hadoop 3's powerful features.
Data Modeling & Design Editorial Review
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Плюсы
- Comprehensive coverage of Hadoop
- Step-by-step implementation guide
- Useful for real-world applications
- Clear explanations for beginners
- Hands-on examples and exercises
Минусы
- Some advanced topics may lack depth.
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TJS 374
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Особенности и преимущества
- Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud
- Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink
- Exploit big data using Hadoop 3 with real-world examples
- Become well-versed with the analytical capabilities of the Hadoop ecosystem
- Perform big data analytics on AWS using Elastic Map Reduce
- Ideal for those looking to build high-performance analytics solutions for their enterprise or business using Hadoop 3's powerful features
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