Identify and fix causes of poor performance. You will learn Query Store, adaptive execution plans, and automated tuning on the Microsoft Azure SQL Database platform. Anyone responsible for writing or creating T-SQL queries will find valuable the insight into bottlenecks, including how to recognize them and eliminate them.
Learn to use the Java Persistence API (JPA) and other related APIs as found in the Java EE 8 platform from the perspective of one of the specification creators. A one-of-a-kind resource, this in-depth book provides both theoretical and practical coverage of JPA usage for experienced Java developers.
Move data back and forth between database and application. The must-have knowledge in this book helps programmers learn how to use the official driver, MySQL Connector/Python, by which Python programs communicate with the MySQL database.
This book takes you from the initial installation of the connector through...
Deal with data, build up financial formulas in code from scratch, and evaluate and think about money in your day-to-day life. This book is about Python and personal finance and how you can effectively mix the two together.
In Personal Finance with Python you will learn Python and finance at...
Gain all the essentials you need to create scalable microservices, which will help you solve real challenges when deploying services into production. This book will take you through creating a scalable data layer with polygot persistence. You’ll cover data access and query patterns in Spring and JPA in high-performance...
Use ASP.NET Core 2 to create durable and cross-platform web APIs through a series of applied, practical scenarios. Examples in this book help you build APIs that are fast and scalable. You’ll progress from the basics of the framework through to solving the complex problems encountered in implementing secure RESTful services....
The database space has been greatly dominated by relational database
management systems (or RDBMSs) such as Microsoft® SQL Server or
Oracle. This dominance was made possible in part by the wide range of
solutions that can be built on top of those systems but also because of
the powerful products that are available. There is,...
Build GPU-accelerated high performing applications with Python 2.7, CUDA 9, and open source libraries such as PyCUDA and scikit-cuda. We recommend the use of Python 2.7 as this version has stable support across all libraries used in this book.
