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MySQL 8 for Big Data

MySQL 8 for Big Data

By : Challawala, Jaydip Lakhatariya, Mehta, Patel
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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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Pruning partitions in MySQL


Pruning is the selective extraction of data. As we have multiple partitions of big data, it will go through each partition during retrieval, which is time consuming and impacts performance. Some of the partitions will also be included in search while the requested data is not available inside that partition, which is an overhead process. Pruning helps here to search for only those partitions that have the relevant data, which will avoid the unnecessary inclusion of those partitions during retrieval.

This optimization that avoids the scanning of partitions where there can be no matching values is known as the pruning of partitions. In partition pruning, the optimizer analyzes FROM and WHERE clauses in SQL statements to eliminate unneeded partitions, and scans those database partitions that are relevant to the SQL statement. Let's see an example.

Suppose that we have a table with the following structure:

 CREATE TABLE student (
 rollNo INT NOT NULL,
 name VARCHAR(50...

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