You're reading from Apache Hive Cookbook

Product type Paperback

Published in Apr 2016

Publisher Packt

ISBN-13 9781782161080

Length 268 pages

Edition 1st Edition

Languages

Java

Tools

Hadoop

Concepts

Data Processing

Table of Contents (14) Chapters

Preface

What this book covers
What you need for this book
Who this book is for
Sections
Conventions
Reader feedback
Customer support

1. Developing Hive

Introduction
Deploying Hive on a Hadoop cluster
Deploying Hive Metastore
Installing Hive
Configuring HCatalog
Understanding different components of Hive
Compiling Hive from source
Hive packages
Debugging Hive
Running Hive
Changing configurations at runtime

2. Services in Hive FREE CHAPTER

Introducing HiveServer2
Understanding HiveServer2 properties
Configuring HiveServer2 high availability
Using HiveServer2 clients
Introducing the Hive metastore service
Configuring high availability of metastore service
Introducing Hue

3. Understanding the Hive Data Model

Introduction
Using numeric data types
Using string data types
Using Date/Time data types
Using miscellaneous data types
Using complex data types
Using operators
Partitioning
Partitioning a managed table
Partitioning an external table
Bucketing

4. Hive Data Definition Language

Introduction
Creating a database schema
Dropping a database schema
Altering a database schema
Using a database schema
Showing database schemas
Describing a database schema
Creating tables
Dropping tables
Truncating tables
Renaming tables
Altering table properties
Creating views
Dropping views
Altering the view properties
Altering the view as select
Showing tables
Showing partitions
Show the table properties
Showing create table
HCatalog
WebHCat

5. Hive Data Manipulation Language

Introduction
Loading files into tables
Inserting data into Hive tables from queries
Inserting data into dynamic partitions
Writing data into files from queries
Enabling transactions in Hive
Inserting values into tables from SQL
Updating data
Deleting data

6. Hive Extensibility Features

Introduction
Serialization and deserialization formats and data types
Exploring views
Exploring indexes
Hive partitioning
Creating buckets in Hive
Analytics functions in Hive
Windowing in Hive
File formats

7. Joins and Join Optimization

Understanding the joins concept
Using a left/right/full outer join
Using a left semi join
Using a cross join
Using a map-side join
Using a bucket map join
Using a bucket sort merge map join
Using a skew join

8. Statistics in Hive

Bringing statistics in to Hive
Table and partition statistics in Hive
Column statistics in Hive
Top K statistics in Hive

9. Functions in Hive

Using built-in functions
Using the built-in User-defined Aggregation Function (UDAF)
Using the built-in User Defined Table Function (UDTF)
Creating custom User-Defined Functions (UDF)

10. Hive Tuning

Enabling predicate pushdown optimizations in Hive
Optimizations to reduce the number of map
Sampling

11. Hive Security

Securing Hadoop
Authorizing Hive
Configuring the SQL standards-based authorization
Authenticating Hive

12. Hive Integration with Other Frameworks

Working with Apache Spark
Working with Accumulo
Working with HBase
Working with Google Drill

Index

Chapter 8. Statistics in Hive

In previous chapters, you learned different types of joins in Hive and optimizations available in Hive joins.

In this chapter, we will cover the following recipes in detail:

Bringing statistics in to Hive
Table and partition statistics in Hive
Column statistics in Hive
Top K statistics in Hive

The rest of the chapter is locked

You're reading from Apache Hive Cookbook

Table of Contents (14) Chapters

Chapter 8. Statistics in Hive

Unlock this book and the full library FREE for 7 days

Personalised recommendations for you