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Apache Hive Cookbook

Apache Hive Cookbook

By : Hanish Bansal, Saurabh Chauhan, Shrey Mehrotra
3 (4)
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Apache Hive Cookbook

Apache Hive Cookbook

3 (4)
By: Hanish Bansal, Saurabh Chauhan, Shrey Mehrotra

Overview of this book

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.
Table of Contents (14 chapters)
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13
Index

What this book covers

Chapter 1, Developing Hive, helps you out in configuring Hive on a Hadoop platform. This chapter explains a different mode of Hive installations. It also provides pointers for debugging Hive and brief information about compiling Hive source code and different modules in the Hive source code.

Chapter 2, Services in Hive, gives a detailed description about the configurations and usage of different services provided by Hive such as HiveServer2. This chapter also explains about different clients of Hive, including Hive CLI and Beeline.

Chapter 3, Understanding the Hive Data Model, takes you through the details of different data types provided by Hive in order to be helpful in data modeling.

Chapter 4, Hive Data Definition Language, helps you understand the syntax and semantics of creating, altering, and dropping different objects in Hive, including databases, tables, functions, views, indexes, and roles.

Chapter 5, Hive Data Manipulation Language, gives you complete understanding of Hive interfaces for data manipulation. This chapter also includes some of the latest features in Hive related to CRUD operations in Hive. It explains insert, update, and delete at the row level in Hive available in Hive 0.14 and later versions.

Chapter 6, Hive Extensibility Features, covers a majority of advance concepts in Hive. This chapter explain some concepts such as SerDes, Partitions, Bucketing, Windowing and Analytics, and File Formats in Hive with the detailed examples.

Chapter 7, Joins and Join Optimization, gives you a detailed explanation of types of Join supported by Hive. It also provides detailed information about different types of Join optimizations available in Hive.

Chapter 8, Statistics in Hive, allows you to capture and analyze tables, partitions, and column-level statistics. This chapter covers the configurations and commands use to capture these statistics.

Chapter 9, Functions in Hive, gives you the detailed overview of the extensive set of inbuilt functions supported by Hive, which can be used directly in queries. This chapter also covers how to create a custom User-Defined Function and register in Hive.

Chapter 10, Hive Tuning, helps you out in optimizing the complex queries to reduce the throughput time. It covers different optimization techniques using predicate pushdown, by reducing number of maps, and by sampling.

Chapter 11, Hive Security, covers concepts to secure the data from any unauthorized access. It explains the different mechanisms of authentication and authorization that can be implement in Hive for security purposes. In case of critical or sensitive data, security is the first thing that needs to be considered.

Chapter 12, Hive Integration with Other Frameworks, takes you through the integration mechanism of Hive with some other popular frameworks such as Spark, HBase, Accumulo, and Google Drill.

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