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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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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

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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