Easy, hands-on recipes to help you understand Hive and its integration with frameworks that are used widely in today's big data world
About This Book
- Grasp a complete reference of different Hive topics.
- Get to know the latest recipes in development in Hive including CRUD operations
- Understand Hive internals and integration of Hive with different frameworks used in today's world.
Who This Book Is For
The book is intended for those who want to start in Hive or who have basic understanding of Hive framework. Prior knowledge of basic SQL command is also required
What You Will Learn
- Learn different features and offering on the latest Hive
- Understand the working and structure of the Hive internals
- Get an insight on the latest development in Hive framework
- Grasp the concepts of Hive Data Model
- Master the key concepts like Partition, Buckets and Statistics
- Know how to integrate Hive with other frameworks such as Spark, Accumulo, etc
In Detail
Hive was developed by Facebook and later open sourced in Apache community. Hive provides SQL like interface to run queries on Big Data frameworks. Hive provides SQL like syntax also called as HiveQL that includes all SQL capabilities like analytical functions which are the need of the hour in today's Big Data world.
This book provides you easy installation steps with different types of metastores supported by Hive. This book has simple and easy to learn recipes for configuring Hive clients and services. You would also learn different Hive optimizations including Partitions and Bucketing. The book also covers the source code explanation of latest Hive version.
Hive Query Language is being used by other frameworks including spark. Towards the end you will cover integration of Hive with these frameworks.
Style and approach
Starting with the basics and covering the core concepts with the practical usage, this book is a complete guide to learn and explore Hive offerings.
Hanish Bansal
Hanish Bansal is a software engineer with over 4 years of experience in developing big data applications. He loves to study emerging solutions and applications mainly related to big data processing, NoSQL, natural language processing, and neural networks. He has worked on various technologies such as Spring Framework, Hibernate, Hadoop, Hive, Flume, Kafka, Storm, and NoSQL databases, which include HBase, Cassandra, MongoDB, and search engines such as Elasticsearch. In 2012, he completed his graduation in Information Technology stream from Jaipur Engineering College and Research Center, Jaipur, India. He was also the technical reviewer of the book Apache Zookeeper Essentials. In his spare time, he loves to travel and listen to music. You can read his blog at http://hanishblogger.blogspot.in/ and follow him on Twitter at https://twitter.com/hanishbansal786.
Saurabh Chauhan
Saurabh Chauhan is a module lead with close to 8 years of experience in data warehousing and big data applications. He has worked on multiple Extract, Transform and Load tools, such as Oracle Data Integrator and Informatica as well as on big data technologies such as Hadoop, Hive, Pig, Sqoop, and Flume. He completed his bachelor of technology in 2007 from Vishveshwarya Institute of Engineering and Technology. In his spare time, he loves to travel and discover new places. He also has a keen interest in sports.
Shrey Mehrotra
Shrey Mehrotra has 6 years of IT experience and, since the past 4 years, in designing and architecting cloud and big data solutions for the governmental and financial domains. Having worked with big data R&D Labs and Global Data and Analytical Capabilities, he has gained insights into Hadoop, focusing on HDFS, MapReduce, and YARN. His technical strengths also include Hive, Pig, Spark, Elasticsearch, Sqoop, Flume, Kafka, and Java. He likes spending time performing R&D on different big data technologies. He is the coauthor of the book Learning YARN, a certified Hadoop developer, and has also written various technical papers. In his free time, he listens to music, watches movies, and spending time with friends.
