Mastering Apache Solr

Accelerate your enterprise search engine and bring relevancy in your search analytics Key Features A practical guide in building expertise with Indexing, Faceting, Clustering and Pagination Master the management and administration of Enterprise Search Applications and services seamlessly Handle multiple data inputs such as JSON, xml, pdf, doc, xls,ppt, csv and much more. Book Description Apache Solr is the only standalone enterprise search server with a REST-like application interface. providing highly scalable, distributed search and index replication for many of the world's largest internet sites. To begin with, you would be introduced to how you perform full text search, multiple filter search, perform dynamic clustering and so on helping you to brush up the basics of Apache Solr. You will also explore the new features and advanced options released in Apache Solr 7.x which will get you numerous performance aspects and making data investigation simpler, easier and powerful. You will learn to build complex queries, extensive filters and how are they compiled in your system to bring relevance in your search tools. You will learn to carry out Solr scoring, elements affecting the document score and how you can optimize or tune the score for the application at hand. You will learn to extract features of documents, writing complex queries in re-ranking the documents. You will also learn advanced options helping you to know what content is indexed and how the extracted content is indexed. Throughout the book, you would go through complex problems with solutions along with varied approaches to tackle your business needs. By the end of this book, you will gain advanced proficiency to build out-of-box smart search solutions for your enterprise demands. What you will learn Design schema using schema API to access data in the database Advance querying and fine-tuning techniques for better performance Get to grips with indexing using Client API Set up a fault tolerant and highly available server with newer distributed capabilities, SolrCloud Explore Apache Tika to upload data with Solr Cell Understand different data operations that can be done while indexing Master advanced querying through Velocity Search UI, faceting and Query Re-ranking, pagination and spatial search Learn to use JavaScript, Python, SolrJ and Ruby for interacting with Solr Who this book is for The book would rightly appeal to developers, software engineers, data engineers and database architects who are building or seeking to build enterprise-wide effective search engines for business intelligence. Prior experience of Apache Solr or Java programming is must to take the best of this book.

Topic: In the open source, full-text search community, a leader emerges – Apache Solr. Apache Solr enables you to index and access documents orders of magnitude faster than classical databases and thereby provides a first-class search experience to your end users. Brief Description: Mastering Apache Solr is a practical, hands-on guide containing crisp, relevant, systematically arranged, and progressive chapters. These chapters contain a wealth of information presented in a direct and easy-to-understand manner. This book covers key technical concepts, highlighting Solr's supremacy over classical databases in full-text search, which will help you accelerate your progress in the Solr world. Detailed Description: Mastering Apache Solr starts with an introduction to Apache Solr, its underlying technologies, the main differences between the classical database engines, and gradually moves to more advance topics like boosting performance. In this book, we will look under the hood of a large number of topics and discuss answers to pertinent questions like why denormalize data, how to import classical databases' data inside Apache Solr, how to serve Solr through five different web servers, how to optimize them to serve Solr even faster. An important and major topic covered in this book is Solr's querying mechanism, which will prove to be a strong ally in our journey through this book. We then look at boosting performance and deploying Solr using several servlet servers. Finally, we cover how to communicate with Solr using different programming languages, before deploying it in a cloud-based environment. Who this book is for: Mastering Apache Solr has been written for developers, programmers, and data specialists who want to take a leap towards the future of full-text storage and search and offer a world-class experience to their users. The reader is expected to have a working knowledge of traditional databases, Linux-based operating systems, and XML configuration files. Style and Approach: Mastering Apache Solr is written lucidly and has a dynamically simple approach. From the first page to the last, the book remains practical and focuses on the most important topics used in the world of Apache Solr without neglecting important theoretical fundamentals that help you build a strong foundation. Conclusion: Mastering Apache Solr will empower you to provide a world-class search experience to your end users through the discovery of the powerful mechanisms presented in this book.

Topic: In the open source, full-text search community, a leader emerges – Apache Solr. Apache Solr enables you to index and access documents orders of magnitude faster than classical databases and thereby provides a first-class search experience to your end users. Brief Description: Mastering Apache Solr is a practical, hands-on guide containing crisp, relevant, systematically arranged, and progressive chapters. These chapters contain a wealth of information presented in a direct and easy-to-understand manner. This book covers key technical concepts, highlighting Solr's supremacy over classical databases in full-text search, which will help you accelerate your progress in the Solr world. Detailed Description: Mastering Apache Solr starts with an introduction to Apache Solr, its underlying technologies, the main differences between the classical database engines, and gradually moves to more advance topics like boosting performance. In this book, we will look under the hood of a large number of topics and discuss answers to pertinent questions like why denormalize data, how to import classical databases' data inside Apache Solr, how to serve Solr through five different web servers, how to optimize them to serve Solr even faster. An important and major topic covered in this book is Solr's querying mechanism, which will prove to be a strong ally in our journey through this book. We then look at boosting performance and deploying Solr using several servlet servers. Finally, we cover how to communicate with Solr using different programming languages, before deploying it in a cloud-based environment. Who this book is for: Mastering Apache Solr has been written for developers, programmers, and data specialists who want to take a leap towards the future of full-text storage and search and offer a world-class experience to their users. The reader is expected to have a working knowledge of traditional databases, Linux-based operating systems, and XML configuration files. Style and Approach: Mastering Apache Solr is written lucidly and has a dynamically simple approach. From the first page to the last, the book remains practical and focuses on the most important topics used in the world of Apache Solr without neglecting important theoretical fundamentals that help you build a strong foundation. Conclusion: Mastering Apache Solr will empower you to provide a world-class search experience to your end users through the discovery of the powerful mechanisms presented in this book.

Summary Solr in Action is a comprehensive guide to implementing scalable search using Apache Solr. This clearly written book walks you through well-documented examples ranging from basic keyword searching to scaling a system for billions of documents and queries. It will give you a deep understanding of how to implement core Solr capabilities. About the Book Whether you're handling big (or small) data, managing documents, or building a website, it is important to be able to quickly search through your content and discover meaning in it. Apache Solr is your tool: a ready-to-deploy, Lucene-based, open source, full-text search engine. Solr can scale across many servers to enable real-time queries and data analytics across billions of documents. Solr in Action teaches you to implement scalable search using Apache Solr. This easy-to-read guide balances conceptual discussions with practical examples to show you how to implement all of Solr's core capabilities. You'll master topics like text analysis, faceted search, hit highlighting, result grouping, query suggestions, multilingual search, advanced geospatial and data operations, and relevancy tuning. This book assumes basic knowledge of Java and standard database technology. No prior knowledge of Solr or Lucene is required. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. What's Inside How to scale Solr for big data Rich real-world examples Solr as a NoSQL data store Advanced multilingual, data, and relevancy tricks Coverage of versions through Solr 4.7 About the Authors Trey Grainger is a director of engineering at CareerBuilder. Timothy Potter is a senior member of the engineering team at LucidWorks. The authors work on the scalability and reliability of Solr, as well as on recommendation engine and big data analytics technologies. Table of Contents PART 1 MEET SOLR Introduction to Solr Getting to know Solr Key Solr concepts Configuring Solr Indexing Text analysis PART 2 CORE SOLR CAPABILITIES Performing queries and handling results Faceted search Hit highlighting Query suggestions Result grouping/field collapsing Taking Solr to production PART 3 TAKING SOLR TO THE NEXT LEVEL SolrCloud Multilingual search Complex query operations Mastering relevancy

This book is for Elasticsearch users who want to extend their knowledge and develop new skills. Prior knowledge of the Query DSL and data indexing is expected.

ElasticSearch is an open source search server built on Apache Lucene. It was built to provide a scalable search solution with built-in support for near real-time search and multi-tenancy.Jumping into the world of ElasticSearch by setting up your own custom cluster, this book will show you how to create a fast, scalable, and flexible search solution. By learning the ins-and-outs of data indexing and analysis, "ElasticSearch Server" will start you on your journey to mastering the powerful capabilities of ElasticSearch. With practical chapters covering how to search data, extend your search, and go deep into cluster administration and search analysis, this book is perfect for those new and experienced with search servers.In "ElasticSearch Server" you will learn how to revolutionize your website or application with faster, more accurate, and flexible search functionality. Starting with chapters on setting up your own ElasticSearch cluster and searching and extending your search parameters you will quickly be able to create a fast, scalable, and completely custom search solution.Building on your knowledge further you will learn about ElasticSearch's query API and become confident using powerful filtering and faceting capabilities. You will develop practical knowledge on how to make use of ElasticSearch's near real-time capabilities and support for multi-tenancy.Your journey then concludes with chapters that help you monitor and tune your ElasticSearch cluster as well as advanced topics such as shard allocation, gateway configuration, and the discovery module.

If you’re like most R users, you have deep knowledge and love for statistics. But as your organization continues to collect huge amounts of data, adding tools such as Apache Spark makes a lot of sense. With this practical book, data scientists and professionals working with large-scale data applications will learn how to use Spark from R to tackle big data and big compute problems. Authors Javier Luraschi, Kevin Kuo, and Edgar Ruiz show you how to use R with Spark to solve different data analysis problems. This book covers relevant data science topics, cluster computing, and issues that should interest even the most advanced users. Analyze, explore, transform, and visualize data in Apache Spark with R Create statistical models to extract information and predict outcomes; automate the process in production-ready workflows Perform analysis and modeling across many machines using distributed computing techniques Use large-scale data from multiple sources and different formats with ease from within Spark Learn about alternative modeling frameworks for graph processing, geospatial analysis, and genomics at scale Dive into advanced topics including custom transformations, real-time data processing, and creating custom Spark extensions

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.