Browse Library
Sign In Start Free Trial
Close icon Search icon
Account
Browse Library Sign In Start Free Trial

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Apache Hive Essentials
  • Table Of Contents Toc
Apache Hive Essentials

Apache Hive Essentials

By : Dayong Du
4.5 (4)
Buy this Book
close
close
Apache Hive Essentials

Apache Hive Essentials

4.5 (4)
By: Dayong Du
Buy this Book

Overview of this book

If you are a data analyst, developer, or simply someone who wants to use Hive to explore and analyze data in Hadoop, this is the book for you. Whether you are new to big data or an expert, with this book, you will be able to master both the basic and the advanced features of Hive. Since Hive is an SQL-like language, some previous experience with the SQL language and databases is useful to have a better understanding of this book.
Table of Contents (12 chapters)
close
close
close
Preface
Icon
Preface
Icon
What this book covers
Icon
What you need for this book
Icon
Who this book is for
Icon
Conventions
Icon
Reader feedback
Icon
Customer support
Lock Free Chapter
1
1. Overview of Big Data and Hive
Icon
1. Overview of Big Data and Hive
Icon
A short history
Icon
Introducing big data
Icon
Relational and NoSQL database versus Hadoop
Icon
Batch, real-time, and stream processing
Icon
Overview of the Hadoop ecosystem
Icon
Hive overview
Icon
Summary
2
2. Setting Up the Hive Environment
Icon
2. Setting Up the Hive Environment
Icon
Installing Hive from Apache
Icon
Installing Hive from vendor packages
Icon
Starting Hive in the cloud
Icon
Using the Hive command line and Beeline
Icon
The Hive-integrated development environment
Icon
Summary
3
3. Data Definition and Description
Icon
3. Data Definition and Description
Icon
Understanding Hive data types
Icon
Data type conversions
Icon
Hive Data Definition Language
Icon
Hive database
Icon
Hive internal and external tables
Icon
Hive partitions
Icon
Hive buckets
Icon
Hive views
Icon
Summary
4
4. Data Selection and Scope
Icon
4. Data Selection and Scope
Icon
The SELECT statement
Icon
The INNER JOIN statement
Icon
The OUTER JOIN and CROSS JOIN statements
Icon
Special JOIN – MAPJOIN
Icon
Set operation – UNION ALL
Icon
Summary
5
5. Data Manipulation
Icon
5. Data Manipulation
Icon
Data exchange – LOAD
Icon
Data exchange – INSERT
Icon
Data exchange – EXPORT and IMPORT
Icon
ORDER and SORT
Icon
Operators and functions
Icon
Transactions
Icon
Summary
6
6. Data Aggregation and Sampling
Icon
6. Data Aggregation and Sampling
Icon
Basic aggregation – GROUP BY
Icon
Advanced aggregation – GROUPING SETS
Icon
Advanced aggregation – ROLLUP and CUBE
Icon
Aggregation condition – HAVING
Icon
Analytic functions
Icon
Sampling
Icon
Summary
7
7. Performance Considerations
chevron up
Icon
7. Performance Considerations
Icon
Performance utilities
Icon
Design optimization
Icon
Data file optimization
Icon
Job and query optimization
Icon
Summary
8
8. Extensibility Considerations
Icon
8. Extensibility Considerations
Icon
User-defined functions
Icon
Streaming
Icon
SerDe
Icon
Summary
9
9. Security Considerations
Icon
9. Security Considerations
Icon
Authentication
Icon
Authorization
Icon
Encryption
Icon
Summary
10
10. Working with Other Tools
Icon
10. Working with Other Tools
Icon
JDBC / ODBC connector
Icon
HBase
Icon
Hue
Icon
HCatalog
Icon
ZooKeeper
Icon
Oozie
Icon
Hive roadmap
Icon
Summary
11
Index
Icon
Index

Chapter 7. Performance Considerations

Although Hive is built to deal with big data, we still cannot ignore the importance of performance. Most of the time, a better Hive query can rely on the smart query optimizer to find the best execution strategy as well as the default setting best practice from vendor packages. However, as experienced users, we should learn more about the theory and practice of performance tuning in Hive, especially when working in a performance-based project or environment. In this chapter, we will start from utilities available in Hive to find potential issues causing poor performance. Then, we introduce the best practices of performance considerations in the areas of design, file format, compression, storage, query, and job.

In this chapter, we will cover the following topics:

  • Performance utilities
  • Design optimization
  • Data file optimization
  • Job and query optimization
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Apache Hive Essentials
End of Section 7
Next Section
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options
font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected
Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful
Order Page Read Now

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon