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Apache Hive Essentials, by Dayong Du
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Immerse yourself on a fantastic journey to discover the attributes of big data by using Hive
About This Book- Discover how Hive can coexist and work with other tools in the Hadoop ecosystem to create big data solutions
- Grasp the skills needed, learn the best practices, and avoid the pitfalls in writing efficient Hive queries to analyze the big data
- Create an environment to analyze big data using practical, example-oriented scenarios
If you are a data analyst, developer, or simply someone who wants to use Hive to explore and analyze data in Hadoop, this is the book for you. Whether you are new to big data or an expert, with this book, you will be able to master both the basic and the advanced features of Hive. Since Hive is an SQL-like language, some previous experience with the SQL language and databases is useful to have a better understanding of this book.
What You Will Learn- Create and set up the Hive environment
- Discover how to use Hive's definition language to describe data
- Discover interesting data by joining and filtering datasets in Hive
- Transform data by using Hive sorting, ordering, and functions
- Aggregate and sample data in different ways
- Boost Hive query performance and enhance data security in Hive
- Customize Hive to your needs by using user-defined functions and integrate it with other tools
In this book, we prepare you for your journey into big data by firstly introducing you to backgrounds in the big data domain along with the process of setting up and getting familiar with your Hive working environment. Next, the book guides you through discovering and transforming the values of big data with the help of examples. It also hones your skill in using the Hive language in an efficient manner. Towards the end, the book focuses on advanced topics such as performance, security, and extensions in Hive, which will guide you on exciting adventures on this worthwhile big data journey.
By the end of the book, you will be familiar with Hive and able to work efficiently to find solutions to big data problems.
- Sales Rank: #1199686 in Books
- Published on: 2015-03-27
- Released on: 2015-02-26
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x .47" w x 7.50" l, .81 pounds
- Binding: Paperback
- 145 pages
About the Author
Dayong Du
Dayong Du is a big data practitioner, leader, and developer with expertise in technology consulting, designing, and implementing enterprise big data solutions. With more than 10 years of experience in enterprise data warehouse, business intelligence, and big data and analytics, he has provided his data intelligence expertise in various industries, such as media, travel, telecommunications, and so on. He is currently working with QuickPlay Media in Toronto, Canada, to build enterprise big data intelligence reporting for online media services and content providers. He has a master's degree in computer science from Dalhousie University, and he holds the Cloudera Certified Developer for Apache Hadoop certification.
Most helpful customer reviews
2 of 2 people found the following review helpful.
Contains up-to-date, practical, wide-ranging review of Hive’s functionality. Highly recommended.
By Ian Stirk
Hi,
I have written a detailed chapter-by-chapter review of this book on www DOT i-programmer DOT info, the first and last parts of this review are given here. For my review of all chapters, search i-programmer DOT info for STIRK together with the book's title.
This book aims to introduce you to a popular platform for storing and analyzing big data on Hadoop. How does it fare?
Increasing amounts of data are being created, and there’s a need to store and process this data to gain competitive advantage. Hive is a popular platform for storing and analyzing big data on Hadoop. Hive tends to be popular because it uses a SQL-like syntax, familiar to many people. With plenty of built-in functionality, big data analysis can be done in Hive without advanced coded skills.
The book is aimed at both the beginner and the more advanced audience (data analysts, developers, and users). Some previous experience of SQL and databases is advantageous.
Chapter 1 Overview of Big Data and Hive
The chapter opens with a brief overview of the history of data processing, covering: batch, online, relational databases, and the internet. The latter has led to a massive rise in the amount of data being created, requiring new approaches to processing. This big data can be described in terms of various attributes including: volume, velocity and variety.
Big data tends to be processed on relatively cheap commodity hardware, using a distributed processing. Hadoop is a popular platform for big data processing. The chapter discusses the major components of Hadoop:
*Hadoop Distributed File System (HDFS) – storage system
*MapReduce – computing system (distributes processing and aggregates results)
*Associated components (e.g. HBase, Sqoop, Flume, Impala etc)
Having described how we arrived at big data and Hadoop, the chapter proceeds with an overview of Hive. Hive allows you to issue queries against petabytes of data, using its Hive Query Language (HQL) which is similar to SQL. Hive gives a table structure to data held in HDFS. Using Hive allows simpler data processing, compared with similar code written in Java.
This chapter provides a helpful background on how we arrived at today’s big data and Hadoop platform. An overview of Hadoop and its components is given, together with a very helpful diagram of the Hadoop ecosystem (e.g. HDFS, HBase, Sqoop, Impala, etc). A useful overview of Hive is provided, highlighting its purpose and advantages.
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Conclusion
This book provides up-to-date detail on Hive, a very popular platform for storing and analyzing big data on Hadoop.
Most topics are explained in a very readable manner, a few sections could do with more detail (e.g. transactions). Throughout, there are helpful explanations, screenshots, practical code examples, and inter-chapter references. Some links to websites are provided for further information.
This book is especially suitable for developers and data analysts starting out with Hive. Additionally, since it also contains advanced and up-to-date material, it is also suitable for more advanced developers/analysts. If you have a background in SQL the book is even easier to understand.
There are very few books dedicated to Hive, and these tend to be out of date now (especially since Hive changes regularly). If you want an up-to-date, practical, wide-ranging review of Hive’s functionality, I highly recommend this book.
0 of 0 people found the following review helpful.
a book with quite many well-designed examples
By Ryan
Given the hyped data science and big data framework buzzwords, the topic this book covers is definitely relevant and important to big data practitioners. The author appears to have a long and solid experience in the industry which gave him much practical knowledge on the subject. Having quickly skimmed through the book, my first impression is the book has a broad coverage of Apache Hive, ranging from the basic setup to security, data manipulation and the detailed explanation on the grammar, complemented with relatively straightforward examples.
My current feeling is, as a thin book of 200 pages, it did quite a good job.
0 of 0 people found the following review helpful.
this is really a good book to start reading
By xulubo
This is by far the most up to date book about Hive. It's been such a long time I've been waiting for a book to cover most stable and widely used Hive version. It is well written. All topics in each chapter are carefully picked and clearly presented for the all level of readers. You really do not need much programming or big data backgrounds to learn it. By reading the book, I strongly agree to the author that Hive will be the most important and popular tools of big data ecosystem for now and future. And most people can and should start the journey of big data from learning Hive. Of course, this is really a good book to start reading.
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