
Practical Hive
Description
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Persons
Andreas Francois Vermeulen is Consulting Manager of Business Intelligence, Big Data, Data Science, and Computational Analytics at Sopra-Steria, doctoral researcher at University of Dundee and St Andrews on future concepts in massive distributed computing, mechatronics, big data, business intelligence, and deep learning. He owns and incubates the "Rapid Information Factory" data processing framework. Active in developing next-generation processing frameworks and mechatronics engineering with over thirty-five years of international experience in data processing, software development and system architecture. Andre is a data scientist, doctoral trainer, corporate consultant, principal systems architect, and speaker/author/columnist on data science, distributed computing, big data, business intelligence, and deep learning. Andre took his bachelor's at the North West University at Potchefstroom, his Master of Business Administration at the University of Manchester, Master of Business Intelligence and Data Science at University of Dundee, and Doctor of Philosophy at the University of Dundee and St Andrews.
Ankur Gupta is a Senior Solutions Engineer at Hortonworks. He has over fourteen years of experience in data management, working as a Data Architect and Oracle DBA. Before joining the world of big data, he was working as an Oracle Consultant for Investment Banks in the UK. He is a regular speaker on big data concepts, Hive, Hadoop, Oracle in various events and is an author of Oracle Goldengate 11g Complete Cookbook. Ankur has a Masters' degree in Computer Science & International Business. He is a Hadoop Certified Administrator & Oracle Certified Professional and lives in London with his wife.
David Kjerrumgaard is a systems architect at Hortonworks. He has 20 years of experience in software development and is a Certified Developer for Apache Hadoop (CCDH). Kjerrumgaard is the author of Data Governance with Apache Falcon and Cloudera Developer Training for Apache Hadoop. He took his BS and MS in Computer Science from Kent State University.
Content
Chapter 1: Setting the Stage for Hive: Hadoop.- Chapter 2: Introducing Hive.- Chapter 3: Hive Architecture.- Chapter 4: Hive Tables DDL.- Chapter 5: Data Manipulation Language (DML).- Chapter 6: Loading Data into Hive.- Chapter 7: Querying Semi-Structured Data.- Chapter 8: Hive Analytics.- Chapter 9: Performance Tuning: Hive.- Chapter 10: Hive Security.- Chapter 11: Future of Hive.- Chapter 12: Appendix A. Building a Big Data Team.- Chapter 13: Appendix B. Hive Functions.
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