An approachable guide to programming in SQL (Structured Query Language) that will teach even beginning programmers how to build powerful databases and analyze data to find meaningful information.Practical SQL is an approachable and fast-paced guide to SQL (Structured Query Language) written by longtime professional journalist Anthony DeBarros. SQL is the primary tool that programmers, web developers, researchers, journalists, and others use to explore data in a database. DeBarros focuses on using SQL to find the story in data, with the aid of the popular open-source database PostgreSQL and the pgAdmin interface.This thoroughly revised second edition includes a new chapter describing how to set up PostgreSQL and more extensive discussion of pgAdmin's best features. The author has also added a chapter on the JSON data format that shows readers how to store and query JSON data. DeBarros has also updated the data in the book throughout, added coverage of additional topics, and perfected the book's examples.Readers love DeBarros's use of exercises and real-world examples that demonstrate how to:- Create databases and related tables using your own data - Correctly define data typesAggregate, sort, and filter data to find patterns - Clean their data and transfer data as text files - Create advanced queries and automate tasksThis book uses PostgreSQL, but the SQL syntax is applicable to many database applications, including Microsoft SQL Server and MySQL.

    This open source systems programming language is now used for everything from game engines and operating systems to browser components and virtual reality simulation engines. But Rust is also an incredibly complex language with a notoriously difficult learning curve.Rather than focusing on the language as a whole, this guide teaches Rust using a single small, complete, focused program in each chapter. Author Ken Youens-Clark shows you how to start, write, and test each of these programs to create a finished product. You'll learn how to handle errors in Rust, read and write files, and use regular expressions, Rust types, structs, and more.

    Reactive systems ensure applications are responsive, resilient, and elastic no matter what failures, latency, or other errors may be occurring, while event-driven architecture offers a flexible and composable option for distributed systems. This practical resource helps you bring these approaches together using Quarkus, a Java framework that greatly simplifies the work developers must undertake for cloud deployments. This book covers how Quarkus 2.0 reactive features allow the smooth development of reactive systems.Clement Escoffier and Ken Finnigan from Red Hat show you how to take advantage of event-driven and reactive principles to build more robust distributed systems, reducing latency and increasing throughput, particularly in your microservices and serverless applications. Java developers will also get a foundation in Quarkus, enabling you to create truly Kubernetes-native applications for the cloud.Understand the fundamentals of reactive systems and event-driven architectureLearn how to use Quarkus to build reactive applicationsCombine Quarkus with Apache Kafka or AMQP to build reactive systemsDevelop microservices that utilize messages with Quarkus for use in event-driven architectures

    It can also be very slow compared to lower-level languages. Python Concurrency with asyncio teaches you how to boost Python's performance by applying a variety of concurrency techniques. You'll learn how the complex-but-powerful asyncio library can achieve concurrency with just a single thread and use asyncio's APIs to run multiple web requests and database queries simultaneously. The book covers using asyncio with the entire Python concurrency landscape, including multiprocessing and multithreading. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology It’s easy to overload standard Python and watch your programs slow to a crawl. Th e asyncio library was built to solve these problems by making it easy to divide and schedule tasks. It seamlessly handles multiple operations concurrently, leading to apps that are lightning fast and scalable. About the book Python Concurrency with asyncio introduces asynchronous, parallel, and concurrent programming through hands-on Python examples. Hard-to-grok concurrency topics are broken down into simple flowcharts that make it easy to see how your tasks are running. You’ll learn how to overcome the limitations of Python using asyncio to speed up slow web servers and microservices. You’ll even combine asyncio with traditional multiprocessing techniques for huge improvements to performance. What's inside     Build web APIs and make concurrency web requests with aiohttp     Run thousands of SQL queries concurrently     Create a map-reduce job that can process gigabytes of data concurrently     Use threading with asyncio to mix blocking code with asyncio code About the reader For intermediate Python programmers. No previous experience of concurrency required. About the author Matthew Fowler has over 15 years of software engineering experience in roles from architect to engineering director. Table of Contents 1 Getting to know asyncio 2 asyncio basics 3 A first asyncio application 4 Concurrent web requests 5 Non-blocking database drivers 6 Handling CPU-bound work 7 Handling blocking work with threads 8 Streams 9 Web applications 10 Microservices 11 Synchronization 12 Asynchronous queues 13 Managing subprocesses 14 Advanced asyncio