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MySQL 8 for Big Data

You're reading from   MySQL 8 for Big Data Effective data processing with MySQL 8, Hadoop, NoSQL APIs, and other Big Data tools

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781788397186
Length 296 pages
Edition 1st Edition
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Authors (4):
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Chintan Mehta Chintan Mehta
Author Profile Icon Chintan Mehta
Chintan Mehta
Shabbir Challawala Shabbir Challawala
Author Profile Icon Shabbir Challawala
Shabbir Challawala
Jaydip Lakhatariya Jaydip Lakhatariya
Author Profile Icon Jaydip Lakhatariya
Jaydip Lakhatariya
Kandarp Patel Kandarp Patel
Author Profile Icon Kandarp Patel
Kandarp Patel
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Toc

Table of Contents (11) Chapters Close

Preface 1. Introduction to Big Data and MySQL 8 FREE CHAPTER 2. Data Query Techniques in MySQL 8 3. Indexing your data for High-Performing Queries 4. Using Memcached with MySQL 8 5. Partitioning High Volume Data 6. Replication for building highly available solutions 7. MySQL 8 Best Practices 8. NoSQL API for Integrating with Big Data Solutions 9. Case study: Part I - Apache Sqoop for exchanging data between MySQL and Hadoop 10. Case study: Part II - Real time event processing using MySQL applier

Database storage engines and types


Let's have a look at different storage engine of MySQL database. This is an important section to understand before we jump into data query techniques, as storage engines play an important role in data query techniques. MySQL stores data in the database as a subdirectory. In each database, data is stored as tables and each table definition information is being stored in a file with extension as .frm with the same name as the table name. Suppose if we create a new table as admin_user then it will store all table definition related information in admin_user.frm file.

We can see information related to a table with the use of SHOWTABLE STATUS command. Let's try to execute this command for admin_user table and pull the information.

mysql> SHOW TABLE STATUS LIKE 'admin_user' \G;
*************************** 1. row ***************************
 Name: admin_user
 Engine: InnoDB
 Version: 10
 Row_format: Dynamic
 Rows: 2
 Avg_row_length: 8192
 Data_length: 16384
...
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