Book Image

MySQL 8 Administrator???s Guide

By : Chintan Mehta, Ankit K Bhavsar, Hetal Oza, Subhash Shah
Book Image

MySQL 8 Administrator???s Guide

By: Chintan Mehta, Ankit K Bhavsar, Hetal Oza, Subhash Shah

Overview of this book

MySQL is one of the most popular and widely used relational databases in the world today. The recently released version 8.0 brings along some major advancements in the way your MySQL solution can be administered. This handbook will be your companion to understand the newly introduced features in MySQL and show you how you can leverage them to design a high-performance MySQL solution for your organization. This book starts with a brief introduction to the new features in MySQL 8, and then quickly jumping onto the crucial administration topics that you will find useful in your day-to-day work. Topics such as migrating to MySQL 8, MySQL benchmarking, achieving high performance by implementing the indexing techniques, and optimizing your queries are covered in this book. You will also learn how to perform replication, scale your MySQL solution and implement effective security techniques. There is also a special section on the common and not so common troubleshooting techniques for effective MySQL administration is also covered in this book. By the end of this highly practical book, you will have all the knowledge you need to tackle any problem you might encounter while administering your MySQL solution.
Table of Contents (17 chapters)

B-Tree index

The main purpose of the B-Tree index is to reduce the number of physical read operations. A B-Tree index is created by sorting the data on the search key and maintaining a hierarchical search data structure, which helps to search for the correct page of data entries. InnoDB and MyISAM storage engines, by default, use the B-Tree index. B-Tree manages to keep an equal distance from all the leaf nodes to the root node. This index speeds up data access because there is no need to scan the whole data to get the desired output. Instead, it starts with the root node. The root node holds a pointer of child nodes, and the storage engine follows these pointers to find the next path. It finds the right path by considering values in the node page. The node page defines the upper and lower bounds of values in the child nodes. At the end of the search process, the storage engine...