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MySQL 8 for Big Data

MySQL 8 for Big Data

By : Challawala, Jaydip Lakhatariya, Mehta, Patel
5 (1)
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MySQL 8 for Big Data

MySQL 8 for Big Data

5 (1)
By: Challawala, Jaydip Lakhatariya, Mehta, Patel

Overview of this book

With organizations handling large amounts of data on a regular basis, MySQL has become a popular solution to handle this structured Big Data. In this book, you will see how DBAs can use MySQL 8 to handle billions of records, and load and retrieve data with performance comparable or superior to commercial DB solutions with higher costs. Many organizations today depend on MySQL for their websites and a Big Data solution for their data archiving, storage, and analysis needs. However, integrating them can be challenging. This book will show you how to implement a successful Big Data strategy with Apache Hadoop and MySQL 8. It will cover real-time use case scenario to explain integration and achieve Big Data solutions using technologies such as Apache Hadoop, Apache Sqoop, and MySQL Applier. Also, the book includes case studies on Apache Sqoop and real-time event processing. By the end of this book, you will know how to efficiently use MySQL 8 to manage data for your Big Data applications.
Table of Contents (11 chapters)
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Best practices for MySQL queries


It would be difficult to write the best queries for reference and reuse. It will always vary based on the nature of your application, architecture, design, table structure, and so on. However, precautions can be taken while writing MySQL queries for better performance, scalability, and integrity.

Let's go through a few of the best practices that we should keep in mind while designing or writing MySQL queries.

Data types

A database table would consist multiple columns having data types such as numeric or string. MySQL 8 provides various data types than just limiting to numeric or string.

  • Small is good. As MySQL loads data in memory, a large data size would adversely impact performance. Smaller sets can accommodate more data in memory and reduce overheads of resource utilization.
  • Fix your length. If you don't fix the data type length, it would have to go and fetch the required information each time it needs. So, wherever it's possible, you can limit data length...
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