Download or read book Scalable Data Architecture with Java written by Sinchan Banerjee and published by Packt Publishing Ltd. This book was released on 2022-09-30 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Orchestrate data architecting solutions using Java and related technologies to evaluate, recommend and present the most suitable solution to leadership and clients Key FeaturesLearn how to adapt to the ever-evolving data architecture technology landscapeUnderstand how to choose the best suited technology, platform, and architecture to realize effective business valueImplement effective data security and governance principlesBook Description Java architectural patterns and tools help architects to build reliable, scalable, and secure data engineering solutions that collect, manipulate, and publish data. This book will help you make the most of the architecting data solutions available with clear and actionable advice from an expert. You'll start with an overview of data architecture, exploring responsibilities of a Java data architect, and learning about various data formats, data storage, databases, and data application platforms as well as how to choose them. Next, you'll understand how to architect a batch and real-time data processing pipeline. You'll also get to grips with the various Java data processing patterns, before progressing to data security and governance. The later chapters will show you how to publish Data as a Service and how you can architect it. Finally, you'll focus on how to evaluate and recommend an architecture by developing performance benchmarks, estimations, and various decision metrics. By the end of this book, you'll be able to successfully orchestrate data architecture solutions using Java and related technologies as well as to evaluate and present the most suitable solution to your clients. What you will learnAnalyze and use the best data architecture patterns for problemsUnderstand when and how to choose Java tools for a data architectureBuild batch and real-time data engineering solutions using JavaDiscover how to apply security and governance to a solutionMeasure performance, publish benchmarks, and optimize solutionsEvaluate, choose, and present the best architectural alternativesUnderstand how to publish Data as a Service using GraphQL and a REST APIWho this book is for Data architects, aspiring data architects, Java developers and anyone who wants to develop or optimize scalable data architecture solutions using Java will find this book useful. A basic understanding of data architecture and Java programming is required to get the best from this book.

Download or read book Building Scalable and High performance Java Web Applications Using J2EE Technology written by Greg Barish and published by Addison-Wesley Professional. This book was released on 2002 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scaling Java enterprise applications beyond just programming techniques--this is the next level. This volume covers all the technologies Java developers need to build scalable, high-performance Web applications. The book also covers servlet-based session management, EJB application logic, database design and integration, and more.

Download or read book Scalable Big Data Architecture written by Bahaaldine Azarmi and published by Apress. This book was released on 2015-12-31 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance. Scalable Big Data Architecture covers real-world, concrete industry use cases that leverage complex distributed applications , which involve web applications, RESTful API, and high throughput of large amount of data stored in highly scalable No-SQL data stores such as Couchbase and Elasticsearch. This book demonstrates how data processing can be done at scale from the usage of NoSQL datastores to the combination of Big Data distribution. When the data processing is too complex and involves different processing topology like long running jobs, stream processing, multiple data sources correlation, and machine learning, it’s often necessary to delegate the load to Hadoop or Spark and use the No-SQL to serve processed data in real time. This book shows you how to choose a relevant combination of big data technologies available within the Hadoop ecosystem. It focuses on processing long jobs, architecture, stream data patterns, log analysis, and real time analytics. Every pattern is illustrated with practical examples, which use the different open sourceprojects such as Logstash, Spark, Kafka, and so on. Traditional data infrastructures are built for digesting and rendering data synthesis and analytics from large amount of data. This book helps you to understand why you should consider using machine learning algorithms early on in the project, before being overwhelmed by constraints imposed by dealing with the high throughput of Big data. Scalable Big Data Architecture is for developers, data architects, and data scientists looking for a better understanding of how to choose the most relevant pattern for a Big Data project and which tools to integrate into that pattern.

Download or read book Big Data written by James Warren and published by Simon and Schuster. This book was released on 2015-04-29 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth

Download or read book Salesforce Data Architect Certification Guide written by Aaron Allport and published by Packt Publishing Ltd. This book was released on 2022-11-18 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn data architecture essentials and prepare for the Salesforce Certified Data Architect exam with the help of tips and mock test questions Key FeaturesLeverage data modelling, Salesforce database design, and techniques for effective data designLearn master data management, Salesforce data management, and how to include considerationsGet to grips with large data volumes, performance tuning, and poor performance mitigation techniquesBook Description The Salesforce Data Architect is a prerequisite exam for the Application Architect half of the Salesforce Certified Technical Architect credential. This book offers complete, up-to-date coverage of the Salesforce Data Architect exam so you can take it with confidence. The book is written in a clear, succinct way with self-assessment and practice exam questions, covering all the topics necessary to help you pass the exam with ease. You'll understand the theory around Salesforce data modeling, database design, master data management (MDM), Salesforce data management (SDM), and data governance. Additionally, performance considerations associated with large data volumes will be covered. You'll also get to grips with data migration and understand the supporting theory needed to achieve Salesforce Data Architect certification. By the end of this Salesforce book, you'll have covered everything you need to know to pass the Salesforce Data Architect certification exam and have a handy, on-the-job desktop reference guide to re-visit the concepts. What you will learnUnderstand the topics relevant to passing the Salesforce Data Architect examExplore specialist areas, such as large data volumesTest your knowledge with the help of exam-like questionsPick up useful tips and tricks that can be referred to time and againUnderstand the reasons underlying the way Salesforce data management worksDiscover the techniques that are available for loading massive amounts of dataWho this book is for This book is for both aspiring Salesforce data architects and those already familiar with Salesforce data architecture who want to pass the exam and have a reference guide to revisit the material as part of their day-to-day job. Working knowledge of the Salesforce platform is assumed, alongside a clear understanding of Salesforce architectural concepts.

Download or read book Designing Data Intensive Applications written by Martin Kleppmann and published by "O'Reilly Media, Inc.". This book was released on 2017-03-16 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

Download or read book Enhancing Java EE Applications Strategies for Performance and Scalability written by Peter Jones and published by Walzone Press. This book was released on 2024-10-21 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the full potential of your Java EE applications with "Enhancing Java EE Applications: Strategies for Performance and Scalability." This essential guide provides comprehensive coverage of techniques and strategies to boost the performance and scalability of your Java EE applications. From architectural insights to advanced coding practices, each chapter brims with expert advice and practical solutions to help you overcome performance and scalability challenges. Learn how to profile and monitor applications to pinpoint bottlenecks, optimize Java EE servers, effectively interact with databases, and implement robust concurrency and multithreading. Explore caching strategies, fine-tune application code, and master network communications within a Java EE context. Additionally, discover how to manage memory efficiently and deploy resources wisely to ensure maximum stability and performance. Whether you're a software developer, IT architect, or system administrator, this book empowers you to make performance-driven decisions that can significantly impact the success of your enterprise applications. Dive into "Enhancing Java EE Applications: Strategies for Performance and Scalability" and elevate your Java EE skills, ensuring your applications are efficient, scalable, and poised to meet the demands of your business.

Download or read book Java Database Best Practices written by George Reese and published by "O'Reilly Media, Inc.". This book was released on 2003-05-14 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: When creating complex Java enterprise applications, do you spend a lot of time thumbing through a myriad of books and other resources searching for what you hope will be the API that's right for the project at hand?Java Database Best Practices rescues you from having to wade through books on each of the various APIs before figuring out which method to use! This comprehensive guide introduces each of the dominant APIs (Enterprise JavaBeans, Java Data Objects, the Java Database Connectivity API (JDBC) as well as other, lesser-known options), explores the methodology and design components that use those APIs, and then offers practices most appropriate for different types and makes of databases, as well as different types of applications.Java Database Practices also examines database design, from table and database architecture to normalization, and offers a number of best practices for handling these tasks as well. Learn how to move through the various forms of normalization, understand when to denormalize, and even get detailed instructions on optimizing your SQL queries to make the best use of your database structure. Through it all, this book focuses on practical application of these techniques, giving you information that can immediately be applied to your own enterprise projects.Enterprise applications in today's world are about data-- whether it be information about a product to buy, a user's credit card information, or the color that a customer prefers for their auto purchases. And just as data has grown in importance, the task of accessing that data has grown in complexity. Until now, you have been left on your own to determine which model best suits your application, and how best to use your chosen API. Java Database Practices is the one stop reference book to help you determine what's appropriate for your specific project at hand. Whether it's choosing between an alphabet soup of APIs and technologies--EJB, JDO, JDBC, SQL, RDBMS, OODBMS, and more on the horizon, this book is an indispensable resource you can't do without.

Download or read book Software Development written by Marc Hamilton and published by Prentice Hall Professional. This book was released on 1999 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: 80% of software projects fail--here's why the other 20% succeed! Software Development is the most thorough, realistic guide to "what works" in software development--and how to make it happen in your organization. Leading consultant Marc Hamilton tackles all three key components of successful development: people, processes, and technology. From streamlining infrastructures to retraining programmers, choosing tools to implementing service-level agreements, Hamilton unifies all of today's best practices--in management, architecture, and software engineering. There's never been a more comprehensive blueprint for software success. Discover "The Ten Commandments of Software Development" Build a winning software development team, organize it for success - and retain your best talent Create a software architecture that maps to business goals and serves as a foundation for successful development Define processes that streamline component and Web-based development projects Leverage the advantages of object-oriented techniques throughout the entire lifecycle Make the most of Java, JavaBeans, and Jini technology Learn the best ways to measure software quality and productivity--and improve them Software Development is ruthlessly realistic and remarkably accessible--for managers and technical professionals alike. Best of all, its techniques can be applied to any project or organization, large or small. Ready to build software that meets all its goals? This book will get you there.

Download or read book Essential PySpark for Scalable Data Analytics written by Sreeram Nudurupati and published by Packt Publishing Ltd. This book was released on 2021-10-29 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started with distributed computing using PySpark, a single unified framework to solve end-to-end data analytics at scale Key FeaturesDiscover how to convert huge amounts of raw data into meaningful and actionable insightsUse Spark's unified analytics engine for end-to-end analytics, from data preparation to predictive analyticsPerform data ingestion, cleansing, and integration for ML, data analytics, and data visualizationBook Description Apache Spark is a unified data analytics engine designed to process huge volumes of data quickly and efficiently. PySpark is Apache Spark's Python language API, which offers Python developers an easy-to-use scalable data analytics framework. Essential PySpark for Scalable Data Analytics starts by exploring the distributed computing paradigm and provides a high-level overview of Apache Spark. You'll begin your analytics journey with the data engineering process, learning how to perform data ingestion, cleansing, and integration at scale. This book helps you build real-time analytics pipelines that help you gain insights faster. You'll then discover methods for building cloud-based data lakes, and explore Delta Lake, which brings reliability to data lakes. The book also covers Data Lakehouse, an emerging paradigm, which combines the structure and performance of a data warehouse with the scalability of cloud-based data lakes. Later, you'll perform scalable data science and machine learning tasks using PySpark, such as data preparation, feature engineering, and model training and productionization. Finally, you'll learn ways to scale out standard Python ML libraries along with a new pandas API on top of PySpark called Koalas. By the end of this PySpark book, you'll be able to harness the power of PySpark to solve business problems. What you will learnUnderstand the role of distributed computing in the world of big dataGain an appreciation for Apache Spark as the de facto go-to for big data processingScale out your data analytics process using Apache SparkBuild data pipelines using data lakes, and perform data visualization with PySpark and Spark SQLLeverage the cloud to build truly scalable and real-time data analytics applicationsExplore the applications of data science and scalable machine learning with PySparkIntegrate your clean and curated data with BI and SQL analysis toolsWho this book is for This book is for practicing data engineers, data scientists, data analysts, and data enthusiasts who are already using data analytics to explore distributed and scalable data analytics. Basic to intermediate knowledge of the disciplines of data engineering, data science, and SQL analytics is expected. General proficiency in using any programming language, especially Python, and working knowledge of performing data analytics using frameworks such as pandas and SQL will help you to get the most out of this book.

Download or read book Data Driven Customer Engagement written by Ralf Strauss and published by Springer Nature. This book was released on with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Java Performance and Scalability written by Dr Henry H Liu and published by Perfmath. This book was released on 2012-07-01 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written in Henry Liu's clear, concise style, Java Application Performance and Scalability gets right to the point. With clearly explained concepts, most pertinent theories, precise step-by-step procedures, and large volume of illustrative charts and tables with highly reliable data supporting behind, you gain quickly the necessary knowledge and skills for being able to cope with Java application performance and scalability issues without having to resort to more experienced professionals or expensive external consultants. Specifically, it helps you learn the following knowledge and skills that are essential for you to become more effective in contributing to the success of your organization:* What you need to know at minimum about the architecture of modern hardware so that you can make smart decisions on when you should pour your time on your application and when you can just throw in more advanced hardware to get by.* What you need to know about garbage collection theories in general and how they are implemented with widely used Java Virtual Machines like HotSpot JVMs.* Precise methodologies, procedures, and programs that you can start to use immediately to help you profile and tune your Java applications.* How you can design and build performance and scalability into your product proactively without having to face tough retrofitting decisions or even torrents of customer escalations later on.In addition, the book contains interesting data for your reference, associated with oops compression, CMS garbage collection tuning, DoEscapeAnalysis, G1 versus CMS comparison, etc., all based on full scale, rigorous performance and scalability tests with real products.

Download or read book The Art of Scalability written by Martin L. Abbott and published by Addison-Wesley Professional. This book was released on 2015-05-23 with total page 1148 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Comprehensive, Proven Approach to IT Scalability–Updated with New Strategies, Technologies, and Case Studies In The Art of Scalability, Second Edition, leading scalability consultants Martin L. Abbott and Michael T. Fisher cover everything you need to know to smoothly scale products and services for any requirement. This extensively revised edition reflects new technologies, strategies, and lessons, as well as new case studies from the authors’ pioneering consulting practice, AKF Partners. Writing for technical and nontechnical decision-makers, Abbott and Fisher cover everything that impacts scalability, including architecture, process, people, organization, and technology. Their insights and recommendations reflect more than thirty years of experience at companies ranging from eBay to Visa, and Salesforce.com to Apple. You’ll find updated strategies for structuring organizations to maximize agility and scalability, as well as new insights into the cloud (IaaS/PaaS) transition, NoSQL, DevOps, business metrics, and more. Using this guide’s tools and advice, you can systematically clear away obstacles to scalability–and achieve unprecedented IT and business performance. Coverage includes • Why scalability problems start with organizations and people, not technology, and what to do about it • Actionable lessons from real successes and failures • Staffing, structuring, and leading the agile, scalable organization • Scaling processes for hyper-growth environments • Architecting scalability: proprietary models for clarifying needs and making choices–including 15 key success principles • Emerging technologies and challenges: data cost, datacenter planning, cloud evolution, and customer-aligned monitoring • Measuring availability, capacity, load, and performance

Download or read book Implementing Domain driven Design written by Vaughn Vernon and published by Pearson Education. This book was released on 2013 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vaughn Vernon presents concrete and realistic domain-driven design (DDD) techniques through examples from familiar domains, such as a Scrum-based project management application that integrates with a collaboration suite and security provider. Each principle is backed up by realistic Java examples, and all content is tied together by a single case study of a company charged with delivering a set of advanced software systems with DDD.

Download or read book Production Ready Microservices written by Susan J. Fowler and published by "O'Reilly Media, Inc.". This book was released on 2016-11-30 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the biggest challenges for organizations that have adopted microservice architecture is the lack of architectural, operational, and organizational standardization. After splitting a monolithic application or building a microservice ecosystem from scratch, many engineers are left wondering what’s next. In this practical book, author Susan Fowler presents a set of microservice standards in depth, drawing from her experience standardizing over a thousand microservices at Uber. You’ll learn how to design microservices that are stable, reliable, scalable, fault tolerant, performant, monitored, documented, and prepared for any catastrophe. Explore production-readiness standards, including: Stability and Reliability: develop, deploy, introduce, and deprecate microservices; protect against dependency failures Scalability and Performance: learn essential components for achieving greater microservice efficiency Fault Tolerance and Catastrophe Preparedness: ensure availability by actively pushing microservices to fail in real time Monitoring: learn how to monitor, log, and display key metrics; establish alerting and on-call procedures Documentation and Understanding: mitigate tradeoffs that come with microservice adoption, including organizational sprawl and technical debt

Download or read book Expert Oracle Database Architecture written by Thomas Kyte and published by Apress. This book was released on 2014-11-10 with total page 811 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its third edition, this best-selling book continues to bring you some of the best thinking on how to apply Oracle Database to produce scalable applications that perform well and deliver correct results. Tom Kyte and Darl Kuhn share a simple philosophy: "you can treat Oracle as a black box and just stick data into it, or you can understand how it works and exploit it as a powerful computing environment." If you choose the latter, then you’ll find that there are few information management problems that you cannot solve quickly and elegantly. This fully revised third edition covers the developments up to Oracle Database 12c. Significant new content is included surrounding Oracle's new cloud feature set, and especially the use of pluggable databases. Each feature is taught in a proof-by-example manner, not only discussing what it is, but also how it works, how to implement software using it, and the common pitfalls associated with it. Don’t treat Oracle Database as a black-box. Get this book. Get under the hood. Turbo-charge your career. Revised to cover Oracle Database 12c Proof-by-example approach: Let the evidence be your guide Dives deeply into Oracle Database’s most powerful features

Download or read book Modern Data Architecture on AWS written by Behram Irani and published by Packt Publishing Ltd. This book was released on 2023-08-31 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover all the essential design and architectural patterns in one place to help you rapidly build and deploy your modern data platform using AWS services Key Features Learn to build modern data platforms on AWS using data lakes and purpose-built data services Uncover methods of applying security and governance across your data platform built on AWS Find out how to operationalize and optimize your data platform on AWS Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMany IT leaders and professionals are adept at extracting data from a particular type of database and deriving value from it. However, designing and implementing an enterprise-wide holistic data platform with purpose-built data services, all seamlessly working in tandem with the least amount of manual intervention, still poses a challenge. This book will help you explore end-to-end solutions to common data, analytics, and AI/ML use cases by leveraging AWS services. The chapters systematically take you through all the building blocks of a modern data platform, including data lakes, data warehouses, data ingestion patterns, data consumption patterns, data governance, and AI/ML patterns. Using real-world use cases, each chapter highlights the features and functionalities of numerous AWS services to enable you to create a scalable, flexible, performant, and cost-effective modern data platform. By the end of this book, you’ll be equipped with all the necessary architectural patterns and be able to apply this knowledge to efficiently build a modern data platform for your organization using AWS services.What you will learn Familiarize yourself with the building blocks of modern data architecture on AWS Discover how to create an end-to-end data platform on AWS Design data architectures for your own use cases using AWS services Ingest data from disparate sources into target data stores on AWS Build data pipelines, data sharing mechanisms, and data consumption patterns using AWS services Find out how to implement data governance using AWS services Who this book is for This book is for data architects, data engineers, and professionals creating data platforms. The book's use case–driven approach helps you conceptualize possible solutions to specific use cases, while also providing you with design patterns to build data platforms for any organization. It's beneficial for technical leaders and decision makers to understand their organization's data architecture and how each platform component serves business needs. A basic understanding of data & analytics architectures and systems is desirable along with beginner’s level understanding of AWS Cloud.