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The amount of data being generated today is staggering and growing. Apache Spark has emerged as the de facto tool to analyze big data and is now a critical part of the data science toolbox. Updated for Spark 3.0, this practical guide brings together Spark, statistical methods, and real-world datasets to teach you how to approach analytics problems using PySpark, Spark's Python API, and other best practices in Spark programming.Data scientists Akash Tandon, Sandy Ryza, Uri Laserson, Sean Owen, and Josh Wills offer an introduction to the Spark ecosystem, then dive into patterns that apply common techniques-including classification, clustering, collaborative filtering, and anomaly detection, to fields such as genomics, security, and finance. This updated edition also covers NLP and image processing.If you have a basic understanding of machine learning and statistics and you program in Python, this book will get you started with large-scale data analysis.Familiarize yourself with Spark's programming model and ecosystemLearn general approaches in data scienceExamine complete implementations that analyze large public datasetsDiscover which machine learning tools make sense for particular problemsExplore code that can be adapted to many uses

Move into iOS development by getting a firm grasp of its fundamentals, including the Xcode 13 IDE, Cocoa Touch, and Swift 5.5, the latest version of Apple's acclaimed programming language. With this thoroughly updated guide, you'll learn the Swift language, understand Apple's Xcode development tools, and discover the Cocoa framework.

You'll find several books on basic or advanced MySQL performance, but nothing in between. That's because explaining MySQL performance without addressing its complexity is difficult. This practical book bridges the gap by teaching software engineers mid-level MySQL knowledge beyond the fundamentals, but well shy of deep-level internals required by database administrators (DBAs).Daniel Nichter shows you how to apply the best practices and techniques that directly affect MySQL performance. You'll learn how to improve performance by analyzing query execution, indexing for common SQL clauses and table joins, optimizing data access, and understanding the most important MySQL metrics. You'll also discover how replication, transactions, row locking, and the cloud influenceMySQL performance.Understand why query response time is the North Star of MySQL performanceLearn query metrics in detail, including aggregation, reporting, and analysisSee how to index effectively for common SQL clauses and table joinsExplore the most important server metrics and what they reveal about performanceDive into transactions and row locking to gain deep, actionable insightAchieve remarkable MySQL performance at any scale

Get the lowdown on CockroachDB, the elastic SQL database built to handle the demands of today's data-driven world. With this practical guide, software developers, architects, and DevOps teams will discover the advantages of building on a distributed SQL database. You'll learn how to create applications that scale elastically and provide seamless delivery for end users while remaining exceptionally resilient and indestructible.Written from scratch for the cloud and architected to scale elastically to handle the demands of cloud native and open source, CockroachDB makes it easier to build and scale modern applications. If you're familiar with distributed systems, you'll quickly discover the benefits of strong data correctness and consistency guarantees as well as optimizations for delivering ultralow latencies to globally distributed end users.With this thorough guide, you'll learn how to:Plan and build applications for distributed infrastructure, including data modeling and schema designMigrate data into CockroachDBRead and write data and run ACID transactions across distributed infrastructureOptimize queries for performance across geographically distributed replicasPlan a CockroachDB deployment for resiliency across single-region and multiregion clustersSecure, monitor, and optimize your CockroachDB deployment

Zero to Genetic Engineering Hero is made to provide you with a first glimpse of the inner-workings of a cell. It further focuses on skill-building for genetic engineering and the Biology-as-a-Technology mindset (BAAT).

The cloud is becoming the de facto home for companies ranging from enterprises to startups. Moving to the cloud means moving your applications from monolith to microservices. But once you do, running and maintaining these services brings its own level of complexity. The answer? Modularity, deployability, observability, and self-healing capacity through cloud native development.With this practical book, Nishant Singh and Michael Kehoe show you how to build a true cloud native infrastructure using Microsoft Azure or another cloud computing solution by following guidelines from the Cloud Native Computing Foundation (CNCF). DevOps and site reliability engineers will learn how adapting applications to cloud native early in the design phase helps you fully utilize the elasticity and distributed nature of the cloud.This book helps you explore:Why go cloud native?How to use infrastructure as codeWhat it takes to containerize an applicationWhy and how Kubernetes is the "e;grand orchestrator"e;How to create a Kubernetes cluster on AzureHow observability complements monitoringHow to use service discovery and a service mesh to find new territoriesHow networking and policy management serve as gatekeepersHow distributed databases and storage work

The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations.Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data.Use Python 3.8+ to read, write, and transform data from a variety of sourcesUnderstand and use programming basics in Python to wrangle data at scaleOrganize, document, and structure your code using best practicesCollect data from structured data files, web pages, and APIsPerform basic statistical analyses to make meaning from datasetsVisualize and present data in clear and compelling ways

Documents various SQL commands according to ANSI standard, and details how those commands are implemented in Microsoft SQL Server 2008, Oracle 11g, and the MySQL 5.1 and PostgreSQL 8.3 open source database products. This book presents fundamental concepts that are necessary for understanding relational databases and SQL commands.

Securing, observing, and troubleshooting containerized workloads on Kubernetes can be daunting. It requires a range of considerations, from infrastructure choices and cluster configuration to deployment controls and runtime and network security. With this practical book, you'll learn how to adopt a holistic security and observability strategy for building and securing cloud native applications running on Kubernetes.Whether you're already working on cloud native applications or are in the process of migrating to its architecture, this guide introduces key security and observability concepts and best practices to help you unleash the power of cloud native applications. Authors Brendan Creane and Amit Gupta from Tigera take you through the full breadth of new cloud native approaches for establishing security and observability for applications running on Kubernetes.Learn why you need a security and observability strategy for cloud native applications and determine your scope of coverageUnderstand key concepts behind the book's security and observability approachExplore the technology choices available to support this strategyDiscover how to share security responsibilities across multiple teams or rolesLearn how to architect Kubernetes security and observability for multicloud and hybrid environments

Observability is critical for building, changing, and understanding the software that powers complex modern systems. Teams that adopt observability are much better equipped to ship code swiftly and confidently, identify outliers and aberrant behaviors, and understand the experience of each and every user. This practical book explains the value of observable systems and shows you how to practice observability-driven development.Authors Charity Majors, Liz Fong-Jones, and George Miranda from Honeycomb explain what constitutes good observability, show you how to improve upon what you??re doing today, and provide practical dos and don'ts for migrating from legacy tooling, such as metrics monitoring and log management. You??ll also learn the impact observability has on organizational culture (and vice versa).You'll explore:How the concept of observability applies to managing software systemsThe value of practicing observability when delivering and managing complex cloud native applications and systemsThe impact observability has across the entire software development lifecycleHow and why different functional teams use observability with service-level objectives (SLOs)How to instrument your code to help future engineers understand the code you wrote todayHow to produce quality code for context-aware system debugging and maintenanceHow data-rich analytics can help you debug elusive issues quickly

How can you realize MySQL's full power? With High Performance MySQL, you'll learn advanced techniques for everything from setting service-level objectives to designing schemas, indexes, and queries to tuning your server, operating system, and hardware to achieve your platform's full potential. This guide also teaches database administrators safe and practical ways to scale applications through replication, load balancing, high availability, and failover.Updated to reflect recent advances in cloud- and self-hosted MySQL, InnoDB performance, and new features and tools, this revised edition helps you design a relational data platform that will scale with your business. You'll learn best practices for database security along with hard-earned lessons in both performance and database stability.Dive into MySQL's architecture, including key facts about its storage enginesLearn how server configuration works with your hardware and deployment choicesMake query performance part of your software delivery processExamine enhancements to MySQL's replication and high availabilityCompare different MySQL offerings in managed cloud environmentsExplore MySQL's full stack optimization from application-side configuration to server tuningTurn traditional database management tasks into automated processes

Data is a fantastic raw resource for powering change in an organization, but all too often the people working in those organizations don't have the necessary skills to communicate with data effectively. With this practical book, subject matter experts will learn ways to develop strong, persuasive points when presenting data to different groups in their organizations.Author Carl Allchin shows anyone how to find data sources and develop data analytics, and teaches those with more data expertise how to visualize data to convey findings to key business leaders more effectively. Once both your business and data experts possess the skills to work with data and interpret its significance, you can deal with questions and challenges in departments across your organization.Learn the fundamental data skills required to work with dataUse data visualization to influence change in your organizationLearn how to apply data techniques to effectively work with data end to endUnderstand how to communicate data points clearly and persuasivelyAppreciate why different stakeholders often have divergent needs and viewsCreate a playbook for using data with different departments

Get quick hands-on experience with Google Cloud. This cookbook provides a variety of self-contained recipes that show you how to use Google Cloud services for your enterprise application. Whether you're looking for practical ways to apply microservices, AI, analytics, security, or networking solutions, these recipes take you step-by-step through the process and provide discussions that explain how and why the recipes work.Ideal for system engineers and administrators, developers, network and database administrators, and data analysts, this cookbook helps you get started with Google Cloud regardless of your level of experience. Google veterans Rui Costa and Drew Hodun also cover advanced-level Google Cloud services for those who have appreciable experience with the platform.Learn how to get started with Google CloudUnderstand the depth of services Google Cloud providesGain hands-on experience using practical examples and labsExplore topics that include BigQuery, Cloud Run, and KubernetesBuild and run mobile and web applications on Google CloudExamine ways to build your cloud applications for scaleBuild a minimum viable product (MVP) app to use in productionLearn data platform and pipeline skills

With this unique hands-on guide, you'll learn valuable ways to use Git in many different situations. Raju Gandhi peels back the layers to reveal the simple yet powerful engine that powers Git, with activities that help you truly understand this crucial tool as you get it up and running.

This practical guide provides over 70 self-contained recipes to help you creatively solve common AWS challenges you'll encounter on your cloud journey. If you're comfortable with rudimentary scripting and general cloud concepts, this cookbook provides what you need to address foundational tasks and create high-level capabilities.Authors John Culkin and Mike Zazon share real-world examples that incorporate best practices. Each recipe includes a diagram to visualize the components. Code is provided so that you can safely execute in an AWS account to ensure solutions work as described. From there, you can customize the code to help construct an application or fix an existing problem. Each recipe also includes a discussion to provide context, explain the approach, and challenge you to explore the possibilities further.Go beyond theory and learn the details you need to successfully build on AWS. The recipes help you:Redact personal identifiable information (PII) from text using Amazon ComprehendAutomate password rotation for Amazon RDS databasesUse VPC Reachability Analyzer to verify and troubleshoot network pathsLock down Amazon Simple Storage Service (S3) bucketsAnalyze AWS Identity and Access Management policiesAutoscale a containerized service

Reactive systems and event-driven architecture are becoming indispensable to application design, and companies are taking note. Reactive systems ensure that applications are responsive, resilient, and elastic no matter what failures or errors may be occurring, while event-driven architecture offers a flexible and composable option for distributed systems. This practical book helps Java developers bring these approaches together using Quarkus 2.x, the Kubernetes-native Java framework.Clement Escoffier and Ken Finnigan show you how to take advantage of event-driven and reactive principles to build robust distributed systems, reducing latency and increasing throughput, particularly in microservices and serverless applications. You'll also get a foundation in Quarkus to help you create true 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 architecturesLearn how to integrate external messaging systems, such as Apache Kafka, with QuarkusBuild applications with Quarkus using reactive systems and reactive programming concepts

Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Python-based machine learning and deep learning models for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to replace traditional financial risk models with ML models.Author Abdullah Karasan helps you explore the theory behind financial risk modeling before diving into practical ways of employing ML models in modeling financial risk using Python. With this book, you will:Review classical time series applications and compare them with deep learning modelsExplore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learningImprove market risk models (VaR and ES) using ML techniques and including liquidity dimensionDevelop a credit risk analysis using clustering and Bayesian approachesCapture different aspects of liquidity risk with a Gaussian mixture model and Copula modelUse machine learning models for fraud detectionPredict stock price crash and identify its determinants using machine learning models

Every enterprise application creates data, including log messages, metrics, user activity, and outgoing messages. Learning how to move these items is almost as important as the data itself. If you're an application architect, developer, or production engineer new to Apache Pulsar, this practical guide shows you how to use this open source event streaming platform to handle real-time data feeds.Jowanza Joseph, staff software engineer at Finicity, explains how to deploy production Pulsar clusters, write reliable event streaming applications, and build scalable real-time data pipelines with this platform. Through detailed examples, you'll learn Pulsar's design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the load manager, and the storage layer.This book helps you:Understand how event streaming fits in the big data ecosystemExplore Pulsar producers, consumers, and readers for writing and reading eventsBuild scalable data pipelines by connecting Pulsar with external systemsSimplify event-streaming application building with Pulsar FunctionsManage Pulsar to perform monitoring, tuning, and maintenance tasksUse Pulsar's operational measurements to secure a production clusterProcess event streams using Flink and query event streams using Presto

Apache Spark's speed, ease of use, sophisticated analytics, and multilanguage support makes practical knowledge of this cluster-computing framework a required skill for data engineers and data scientists. With this hands-on guide, anyone looking for an introduction to Spark will learn practical algorithms and examples using PySpark.In each chapter, author Mahmoud Parsian shows you how to solve a data problem with a set of Spark transformations and algorithms. You'll learn how to tackle problems involving ETL, design patterns, machine learning algorithms, data partitioning, and genomics analysis. Each detailed recipe includes PySpark algorithms using the PySpark driver and shell script.With this book, you will:Learn how to select Spark transformations for optimized solutionsExplore powerful transformations and reductions including reduceByKey(), combineByKey(), and mapPartitions()Understand data partitioning for optimized queriesBuild and apply a model using PySpark design patternsApply motif-finding algorithms to graph dataAnalyze graph data by using the GraphFrames APIApply PySpark algorithms to clinical and genomics dataLearn how to use and apply feature engineering in ML algorithmsUnderstand and use practical and pragmatic data design patterns

Ready to learn Java? This book combines puzzles, strong visuals, mysteries, and soul-searching interviews with famous Java objects to engage you in many different ways. It's fast, it's fun, and it's effective. And despite its playful appearance, Head First Java is serious stuff: a complete introduction to object-oriented programming and Java.

Author Gaurav Raje shows cloud solution architects and software developers with AWS experience how to build highly secure systems on AWS without increasing overhead.

AI is nothing without somewhere to run it. Now that mobile devices have become the primary computing device for most people, it's essential that mobile developers add AI to their toolbox. This insightful book is your guide to creating and running models on popular mobile platforms such as iOS and Android.Laurence Moroney, lead AI advocate at Google, offers an introduction to machine learning techniques and tools, then walks you through writing Android and iOS apps powered by common ML models like computer vision and text recognition, using tools such as ML Kit, TensorFlow Lite, and Core ML. If you're a mobile developer, this book will help you take advantage of the ML revolution today.Explore the options for implementing ML and AI on mobile devicesCreate ML models for iOS and AndroidWrite ML Kit and TensorFlow Lite apps for iOS and Android, and Core ML/Create ML apps for iOSChoose the best techniques and tools for your use case, such as cloud-based versus on-device inference and high-level versus low-level APIsLearn privacy and ethics best practices for ML on devices

Popularly known as "the Llama," Learning Perl is the book most programmers rely on to get started with this versatile language. The bestselling Perl tutorial since it was first published in 1993, this sixth edition includes recent changes to the language up to Perl 5.24.

Your code is a testament to your skills as a developer. No matter what language you use, code should be clean, elegant, and uncluttered. By using test-driven development (TDD), you'll write code that's easy to understand, retains its elegance, and works for months, even years, to come. With this indispensable guide, you'll learn how to use TDD with three different languages: Go, JavaScript, and Python.Author Saleem Siddiqui shows you how to tackle domain complexity using a unit test-driven approach. TDD partitions requirements into small, implementable features, enabling you to solve problems irrespective of the languages and frameworks you use. With Learning Test-Driven Development at your side, you'll learn how to incorporate TDD into your regular coding practice.This book helps you:Use TDD's divide-and-conquer approach to tame domain complexityUnderstand how TDD works across languages, testing frameworks, and domain conceptsLearn how TDD enables continuous integrationSupport refactoring and redesign with TDDLearn how to write a simple and effective unit test harness in JavaScriptSet up a continuous integration environment with the unit tests produced during TDDWrite clean, uncluttered code using TDD in Go, JavaScript, and Python

When it comes to writing efficient code, every software professional needs to have an effective working knowledge of algorithms. In this practical book, author George Heineman (Algorithms in a Nutshell) provides concise and informative descriptions of key algorithms that improve coding in multiple languages. Software developers, testers, and maintainers will discover how algorithms solve computational problems creatively.Each chapter builds on earlier chapters through eye-catching visuals and a steady rollout of essential concepts, including an algorithm analysis to classify the performance of every algorithm presented in the book. At the end of each chapter, you??ll get to apply what you??ve learned to a novel challenge problem??simulating the experience you might find in a technical code interview.With this book, you will:Examine fundamental algorithms central to computer science and software engineeringLearn common strategies for efficient problem solving??such as divide and conquer, dynamic programming, and greedy approachesAnalyze code to evaluate time complexity using big O notationUse existing Python libraries and data structures to solve problems using algorithmsUnderstand the main steps of important algorithms

Get the definitive guide on Gatsby, the JavaScript framework for building blazing fast websites and applications. Used by Nike, Costa Coffee, and other companies worldwide, Gatsby is emerging as one of the key technologies in the Jamstack (JavaScript, APIs, and markup) ecosystem. With this comprehensive guide, you'll learn how to architect, build, and deploy Gatsby sites independently or with CMSs, commerce systems, and other data sources.Author Preston So begins by showing you how to set up a Gatsby site from scratch. From there, you??ll learn ways to use Gatsby??s declarative rendering and GraphQL API, build complex offline-enabled sites, and continuously deploy Gatsby sites on a variety of platforms, including Gatsby Cloud.Discover how Gatsby integrates with many data sources and plug-insSet up, configure, and architect Gatsby sites using Gatsby's CLI, React, JSX, and GraphQL with high performance out of the boxBuild an independent Gatsby site based on Markdown and data- and content-driven Gatsby sites that integrate with CMSs and commerce platformsDeploy Gatsby sites with full CI/CD and test coverage on a variety of platforms, including Netlify, Vercel, and Gatsby Cloud

Want to run your Kubernetes workloads safely and securely? This practical book provides a threat-based guide to Kubernetes security. Each chapter examines a particular component's architecture and potential default settings and then reviews existing high-profile attacks and historical Common Vulnerabilities and Exposures (CVEs). Authors Andrew Martin and Michael Hausenblas share best-practice configuration to help you harden clusters from possible angles of attack.This book begins with a vanilla Kubernetes installation with built-in defaults. You'll examine an abstract threat model of a distributed system running arbitrary workloads, and then progress to a detailed assessment of each component of a secure Kubernetes system.Understand where your Kubernetes system is vulnerable with threat modelling techniquesFocus on pods, from configurations to attacks and defensesSecure your cluster and workload trafficDefine and enforce policy with RBAC, OPA, and KyvernoDive deep into sandboxing and isolation techniquesLearn how to detect and mitigate supply chain attacksExplore filesystems, volumes, and sensitive information at restDiscover what can go wrong when running multitenant workloads in a clusterLearn what you can do if someone breaks in despite you having controls in place

Traditionally, JavaScript has been a single-threaded language. Nearly all online forum posts, books, online documentation, and libraries refer to the language as single threaded. Thanks to recent advancements in the language--such as the Atomics and SharedArrayBuffers objects and Web Workers in the browser--JavaScript is now a multi-threaded language. These features will go down as being the biggest paradigm shift for the world's most popular programming language.Multithreaded JavaScript explores the various features that JavaScript runtimes have at their disposal for implementing multithreaded programming, providing both practical real-world examples, as well as reference material.Learn what multithreaded programming is and how you can benefit from itUnderstand the differences between a web worker, a service worker, and a worker threadKnow when and when not to use threads in an applicationOrchestrate communication between threads by leveraging the Atomics objectBuild high-performance applications using the knowledge you gain from this bookBenchmark performance to learn if you'll benefit from multithreading

A lot of work is required to release an API, but the effort doesnt always pay off. Overplanning before an API matures is a wasted investment, while underplanning can lead to disaster. This practical guide provides maturity models for individual APIs and multi-API landscapes to help you invest the right human and company resources for the right maturity level at the right time.How do you balance the desire for agility and speed with the need for robust and scalable operations? Four experts from the API Academy show software architects, program directors, and product owners how to maximize the value of their APIs by managing them as products through a continuous life cycle.Learn which API decisions you need to govern and how and where to do soDesign, deploy, and manage APIs using an API-as-a-product (AaaP) approachExamine ten pillars that form the foundation of API product workLearn how the continuous improvement model governs changes throughout an APIs lifetimeExplore the five stages of a complete API product life cycleDelve into team roles needed to design, build, and maintain your APIsLearn how to manage your API landscapethe set of APIs published by your organization

While containers, microservices, and distributed systems dominate discussions in the tech world, the majority of applications in use today still run monolithic architectures that follow traditional development processes. This practical book helps developers examine long-established Java-based models and demonstrates how to bring these monolithic applications successfully into the future.Relying on their years of experience modernizing applications, authors Markus Eisele and Natale Vinto walk you through the steps necessary to update your organization's Java applications. You'll discover how to dismantle your monolithic application and move to an up-to-date software stack that works across cloud and on-premises installations.Learn cloud native application basics to understand what parts of your organization's Java-based applications and platforms need to migrate and modernizeUnderstand how enterprise Java specifications can help you transition projects and teamsBuild a cloud native platform that supports effective development without falling into buzzword trapsFind a starting point for your migration projects by identifying candidates and staging them through modernization stepsDiscover how to complement a traditional enterprise Java application with components on top of containers and Kubernetes