Practical Hive is your go-to resource for moving traditional relational databases into Hive, a Hadoop-based data warehousing product.Author Scott Shaw, an eminent big data expert, takes you through learning HiveQL, the SQL-like language specific to Hive, to analyze, export, and massage the data stored across your Hadoop environment. From deploying Hive on your hardware or virtual machine and setting up its initial configuration to learning how Hive interacts with Hadoop, MapReduce, and other big data technologies, Practical Hive gives you a detailed treatment of the software. In addition, the latter portion of the book includes detailed, real-world case studies grounded in everyday Hive deployments that will show you how others have coaxed the most out of their Hive data warehouses. What you'll learn Inside the book, author Scott Shaw provides: instructions for installation and configuration of Hive for new and existing datasetsa step-by-step walkthrough of how to perform DDL Operationsguidance on efficiently executing DML OperationsDetailed descriptions of uses for and instruction on tables, particians, buckets, user-defined functionsa comprehensive study of QL and SQL operations with Hivecase studies of successful Hive implementations Who this book is for Practical Hive is intended for developers, companies and professionals who deal with large amounts of data and could use software that can efficiently manage large volumes of input. It showcases how to effectively use Hive, so that it will be practical even to readers with high levels of experience using the software. It is assumed that readers have the ability to work with SQL. "
Chapter 1. The Frame for Hive Chapter 2. Introduction to Hive Chapter 3. The Structure of Hive Chapter 4. Hive Tables DDL Chapter 5. Hive DML Chapter 6. Hive Files and Storage Chapter 7. Querying Semi-Structured Data Chapter 8. Administering Hive Chapter 9. Hive in the Cloud Chapter 10. Hive Best Practice Chapter 11. The Future of Hive Appendix A. Building a Big Data Team Appendix B. Using ODBC connectors