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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

Indexing your data for High-Performing Queries

In the previous chapter, you learned to apply queries on your data stored in the MySQL database. You learned the different syntax of the select query, how to join tables, and how to apply aggregate functions on the table.

In this chapter, you will learn below topics on what is indexing and different types of indexes:

  • MySQL indexing
  • MySQL index types
  • Indexing JSON data

Let's assume that we have a database table that has more then 50 lakh records of email addresses and you want to fetch one record out of this table. Now, if you write a query to fetch an email address, MySQL will have to check in each and every row for the values matching your queried email address. If MySQL takes one microsecond to scan one record, then it will take around five seconds to load just one record and, as the number of records increases in a table...

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