Du - Apache Hive essentials: essential techniques to help you process, and get unique insights from, big data

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First published: February 2015
Second edition: June 2018

Production reference: 1290618

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ISBN 978-1-78899-509-2

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Dayong Du is a big data practitioner, author, and coach with over 10 years' experience in technology consulting, designing, and implementing enterprise big data architecture and analytics in various industries, including finance, media, travel, and telecoms. He has a master's degree in computer science from Dalhousie University and is a Cloudera certified Hadoop developer. He is a cofounder of Toronto Big Data Professional Association and the founder of DataFiber website.

Deepak Kumar Sahu is a big data technology-driven professional with extensive experience in data gathering, modeling, analysis, validation, and architecture design to build next-generation analytics platforms. He has a strong analytical and technical background with good problem-solving skills to develop effective, complex business solutions. He enjoys developing high-quality software and designing secure and scalable data systems. He has written blogs on machine learning, data science, big data management, and Blockchain. He can be reached at linkedin deepakkumarsahu .

Shuguang Li is a big data professional with extensive experience in designing and implementing complete end-to-end Hadoop infrastructure using MapReduce, Spark, Hive, Atlas, Kafka, Sqoop, HBase. The whole lifecycle covers data ingestion, data streaming, data analyzing and data mining. He also has hands on experience in blockchain technology, including fabric and sawtooth. Shuguang has more than 20 years' experience in financial industry, like banks, stock exchange and mutual fund companies. He can be reach at linkedin michael-li-12016915.

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With an increasing interest in big data analysis, Hive over Hadoop becomes a cutting-edge data solution for storing, computing, and analyzing big data. The SQL-like syntax makes Hive easier to learn and is popularly accepted as a standard for interactive SQL queries over big data. The variety of features available within Hive provides us with the capability of doing complex big data analysis without advanced coding skills. The maturity of Hive lets it gradually merge and share its valuable architecture and functionalities across different computing frameworks beyond Hadoop.

Apache Hive Essentials, Second Edition prepares your journey to big data by covering the introduction of backgrounds and concepts in the big data domain, along with the process of setting up and getting familiar with your Hive working environment in the first two chapters. In the next four chapters, the book guides you through discovering and transforming the value behind big data using examples and skills of Hive query languages. In the last four chapters, the book highlights the well-selected and advanced topics, such as performance, security, and extensions, as exciting adventures for this worthwhile big data journey.

If you are a data analyst, developer, or user who wants to use Hive for exploring and analyzing data in Hadoop, this is the right book for you. Whether you are new to big data or already an experienced user, you will be able to master both basic and advanced functions of Hive. Since HQL is quite similar to SQL, some previous experience with SQL and databases will help with getting a better understanding of this book.