Download Free Lucene 4 Cookbook Book in PDF and EPUB Free Download. You can read online Lucene 4 Cookbook and write the review.

Lucene 4 Cookbook is a practical guide that shows you how to build a scalable search engine for your application, from an internal documentation search to a wide-scale web implementation with millions of records. Starting with helping you to successfully install Apache Lucene, it will guide you through creating your first search application. Furthermore, the book walks you through analyzing your text and indexing your data to leverage the performance of your search application. As you progress through the chapters, you will learn to effectively search your indexes and successfully employ real-time searching. The chapters start off with simple concepts and build up to complex solutions that should help you on your way to becoming a search engine expert.
This book is for experienced Java developers with NLP needs, whether academics, industrialists, or hobbyists. A basic knowledge of NLP terminology will be beneficial.
When Lucene first hit the scene five years ago, it was nothing short ofamazing. By using this open-source, highly scalable, super-fast search engine,developers could integrate search into applications quickly and efficiently.A lot has changed since then-search has grown from a "nice-to-have" featureinto an indispensable part of most enterprise applications. Lucene now powerssearch in diverse companies including Akamai, Netflix, LinkedIn,Technorati, HotJobs, Epiphany, FedEx, Mayo Clinic, MIT, New ScientistMagazine, and many others. Some things remain the same, though. Lucene still delivers high-performancesearch features in a disarmingly easy-to-use API. Due to its vibrant and diverseopen-source community of developers and users, Lucene is relentlessly improving,with evolutions to APIs, significant new features such as payloads, and ahuge increase (as much as 8x) in indexing speed with Lucene 2.3. And with clear writing, reusable examples, and unmatched advice on bestpractices, Lucene in Action, Second Edition is still the definitive guide todeveloping with Lucene. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.
If you are a .NET developer who is looking for a simpler way to build services, this is the book for you. It will show you how to write fast, maintainable APIs that are a pleasure to use and maintain starting from the database to the client and everything in-between.
This book is for intermediate Solr Developers who are willing to learn and implement Pro-level practices, techniques, and solutions. This edition will specifically appeal to developers who wish to quickly get to grips with the changes and new features of Apache Solr 5.
Over 100 practical recipes to make Apache Solr faster, more reliable and return better results.
Over 90 incredible and powerful recipes to help you efficiently use NHibernate in your application About This Book Master the full range of NHibernate features through detailed example recipes that you can quickly apply to your own applications Reduce hours of application development time and get a better application architecture and improved performance Create, maintain, and update your database structure automatically with the help of NHibernate Who This Book Is For This book is written for .NET developers who want to use NHibernate and those who want to deepen their knowledge of the platform. Examples are written in C# and XML. Some basic knowledge of SQL is assumed. If you build .NET applications that use relational databases, this book is for you. What You Will Learn Create a persistent object model to move data in and out of your database Build the database from your model automatically Configure NHibernate for use with WebForms, MVC, WPF, and WinForms applications Create database queries using a variety of methods Improve the performance of your applications using a variety of techniques Build an infrastructure for fast, easy, test-driven development of your data access layer Implement entity validation, auditing, full-text search, horizontal partitioning (sharding), and spatial queries using NHibernate Contrib projects In Detail NHibernate is a mature, flexible, scalable, and feature-complete open source project for data access. Although it sounds like an easy task to build and maintain database applications, it can be challenging to get beyond the basics and develop applications that meet your needs perfectly. NHibernate allows you to use plain SQL and stored procedures less and keep focus on your application logic instead. Learning the best practices for a NHibernate-based application will help you avoid problems and ensure that your project is a success. The book will take you from the absolute basics of NHibernate through to its most advanced features, showing you how to take full advantage of each concept to quickly create amazing database applications. You will learn several techniques for each of the four core NHibernate tasks—configuration, mapping, session and transaction management, and querying—and which techniques fit best with various types of applications. In short, you will be able to build an application using NHibernate by the end of the book. You will also learn how to best implement enterprise application architecture patterns using NHibernate, leading to clean, easy-to-understand code and increased productivity. In addition to new features, you will learn creative ways to extend the NHibernate core, as well as gaining techniques to work with the NHibernate search, shards, spatial, envers, and validation projects. Style and approach This book contains recipes with examples organized in functional areas, each containing step-by-step instructions on everything necessary to execute a particular task. The book is designed so you can read it from start to end or just open up any chapter and start following the recipes.
This book is for intermediate Solr Developers who are willing to learn and implement Pro-level practices, techniques, and solutions. This edition will specifically appeal to developers who wish to quickly get to grips with the changes and new features of Apache Solr 5.
Simplify machine learning model implementations with Spark About This Book Solve the day-to-day problems of data science with Spark This unique cookbook consists of exciting and intuitive numerical recipes Optimize your work by acquiring, cleaning, analyzing, predicting, and visualizing your data Who This Book Is For This book is for Scala developers with a fairly good exposure to and understanding of machine learning techniques, but lack practical implementations with Spark. A solid knowledge of machine learning algorithms is assumed, as well as hands-on experience of implementing ML algorithms with Scala. However, you do not need to be acquainted with the Spark ML libraries and ecosystem. What You Will Learn Get to know how Scala and Spark go hand-in-hand for developers when developing ML systems with Spark Build a recommendation engine that scales with Spark Find out how to build unsupervised clustering systems to classify data in Spark Build machine learning systems with the Decision Tree and Ensemble models in Spark Deal with the curse of high-dimensionality in big data using Spark Implement Text analytics for Search Engines in Spark Streaming Machine Learning System implementation using Spark In Detail Machine learning aims to extract knowledge from data, relying on fundamental concepts in computer science, statistics, probability, and optimization. Learning about algorithms enables a wide range of applications, from everyday tasks such as product recommendations and spam filtering to cutting edge applications such as self-driving cars and personalized medicine. You will gain hands-on experience of applying these principles using Apache Spark, a resilient cluster computing system well suited for large-scale machine learning tasks. This book begins with a quick overview of setting up the necessary IDEs to facilitate the execution of code examples that will be covered in various chapters. It also highlights some key issues developers face while working with machine learning algorithms on the Spark platform. We progress by uncovering the various Spark APIs and the implementation of ML algorithms with developing classification systems, recommendation engines, text analytics, clustering, and learning systems. Toward the final chapters, we'll focus on building high-end applications and explain various unsupervised methodologies and challenges to tackle when implementing with big data ML systems. Style and approach This book is packed with intuitive recipes supported with line-by-line explanations to help you understand how to optimize your work flow and resolve problems when working with complex data modeling tasks and predictive algorithms. This is a valuable resource for data scientists and those working on large scale data projects.
Recipes to help you overcome your data science hurdles using Java About This Book This book provides modern recipes in small steps to help an apprentice cook become a master chef in data science Use these recipes to obtain, clean, analyze, and learn from your data Learn how to get your data science applications to production and enterprise environments effortlessly Who This Book Is For This book is for Java developers who are familiar with the fundamentals of data science and want to improve their skills to become a pro. What You Will Learn Find out how to clean and make datasets ready so you can acquire actual insights by removing noise and outliers Develop the skills to use modern machine learning techniques to retrieve information and transform data to knowledge. retrieve information from large amount of data in text format. Familiarize yourself with cutting-edge techniques to store and search large volumes of data and retrieve information from large amounts of data in text format Develop basic skills to apply big data and deep learning technologies on large volumes of data Evolve your data visualization skills and gain valuable insights from your data Get to know a step-by-step formula to develop an industry-standard, large-scale, real-life data product Gain the skills to visualize data and interact with users through data insights In Detail If you are looking to build data science models that are good for production, Java has come to the rescue. With the aid of strong libraries such as MLlib, Weka, DL4j, and more, you can efficiently perform all the data science tasks you need to. This unique book provides modern recipes to solve your common and not-so-common data science-related problems. We start with recipes to help you obtain, clean, index, and search data. Then you will learn a variety of techniques to analyze, learn from, and retrieve information from data. You will also understand how to handle big data, learn deeply from data, and visualize data. Finally, you will work through unique recipes that solve your problems while taking data science to production, writing distributed data science applications, and much more—things that will come in handy at work. Style and approach This book contains short yet very effective recipes to solve most common problems. Some recipes cater to very specific, rare pain points. The recipes cover different data sets and work very closely to real production environments