Scaling Apache Solr

This book is a step-by-step guide for readers who would like to learn how to build complete enterprise search solutions, with ample real-world examples and case studies. If you are a developer, designer, or architect who would like to build enterprise search solutions for your customers or organization, but have no prior knowledge of Apache Solr/Lucene technologies, this is the book for you.

This book is aimed at developers, designers, and architects who would like to build big data enterprise search solutions for their customers or organizations. No prior knowledge of Apache Hadoop and Apache Solr/Lucene technologies is required.

As data grows exponentially day-by-day, extracting information becomes a tedious activity in itself. Technologies like Hadoop are trying to address some of the concerns, while Solr provides high-speed faceted search. Bringing these two technologies together is helping organizations resolve the problem of information extraction from Big Data by providing excellent distributed faceted search capabilities.Scaling Big Data with Hadoop and Solr is a step-by-step guide that helps you build high performance enterprise search engines while scaling data. Starting with the basics of Apache Hadoop and Solr, this book then dives into advanced topics of optimizing search with some interesting real-world use cases and sample Java code.Scaling Big Data with Hadoop and Solr starts by teaching you the basics of Big Data technologies including Hadoop and its ecosystem and Apache Solr. It explains the different approaches of scaling Big Data with Hadoop and Solr, with discussion regarding the applicability, benefits, and drawbacks of each approach. It then walks readers through how sharding and indexing can be performed on Big Data followed by the performance optimization of Big Data search. Finally, it covers some real-world use cases for Big Data scaling.With this book, you will learn everything you need to know to build a distributed enterprise search platform as well as how to optimize this search to a greater extent resulting in maximum utilization of available resources.

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 developers who already know how to use Solr and are looking at procuring advanced strategies for improving their search using Solr. This book is also for people who work with analytics to generate graphs and reports using Solr. Moreover, if you are a search architect who is looking forward to scale your search using Solr, this is a must have book for you. It would be helpful if you are familiar with the Java programming language.

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.

Build an enterprise search engine using Apache Solr: index and search documents; ingest data from varied sources; apply various text processing techniques; utilize different search capabilities; and customize Solr to retrieve the desired results. Apache Solr: A Practical Approach to Enterprise Search explains each essential concept-backed by practical and industry examples--to help you attain expert-level knowledge. The book, which assumes a basic knowledge of Java, starts with an introduction to Solr, followed by steps to setting it up, indexing your first set of documents, and searching them. It then introduces you to information retrieval and its implementation in Apache Solr; this will help you understand your search problem, decide the approach to build an effective solution, and use various metrics to evaluate the results. The book next covers the schema design and techniques to build a text analysis chain for cleansing, normalizing and enriching your documents and addressing different types of search queries. It describes various popular matching techniques which are generally applied to improve the precision and recall of searches. You will learn the end-to-end process of data ingestion from varied sources, metadata extraction, pre-processing and transformation of content, various search components, query parsers and other advanced search capabilities. After covering out-of-the-box features, Solr expert Dikshant Shahi dives into ways you can customize Solr for your business and its specific requirements, along with ways to plug in your own components. Most important, you will learn about implementations for Solr scoring, factors affecting the document score, and tuning the score for the application at hand. The book explains why textual scoring is not sufficient for practical ranking of documents and ways to integrate real-world factors for contributing to the document ranking. You'll see how to influence user experience by providing suggestions and recommendations. You'll also see integration of Solr with important related technologies such as OpenNLP and Tika. Additionally, you will learn about scaling Solr using SolrCloud. This book concludes with coverage of semantic search capabilities, which is crucial for taking the search experience to the next level. By the end of Apache Solr, you will be proficient in designing and developing your search engine. .

Build an enterprise search engine using Apache Solr: index and search documents; ingest data from varied sources; apply various text processing techniques; utilize different search capabilities; and customize Solr to retrieve the desired results. Apache Solr: A Practical Approach to Enterprise Search explains each essential concept-backed by practical and industry examples--to help you attain expert-level knowledge. The book, which assumes a basic knowledge of Java, starts with an introduction to Solr, followed by steps to setting it up, indexing your first set of documents, and searching them. It then introduces you to information retrieval and its implementation in Apache Solr; this will help you understand your search problem, decide the approach to build an effective solution, and use various metrics to evaluate the results. The book next covers the schema design and techniques to build a text analysis chain for cleansing, normalizing and enriching your documents and addressing different types of search queries. It describes various popular matching techniques which are generally applied to improve the precision and recall of searches. You will learn the end-to-end process of data ingestion from varied sources, metadata extraction, pre-processing and transformation of content, various search components, query parsers and other advanced search capabilities. After covering out-of-the-box features, Solr expert Dikshant Shahi dives into ways you can customize Solr for your business and its specific requirements, along with ways to plug in your own components. Most important, you will learn about implementations for Solr scoring, factors affecting the document score, and tuning the score for the application at hand. The book explains why textual scoring is not sufficient for practical ranking of documents and ways to integrate real-world factors for contributing to the document ranking. You'll see how to influence user experience by providing suggestions and recommendations. You'll also see integration of Solr with important related technologies such as OpenNLP and Tika. Additionally, you will learn about scaling Solr using SolrCloud. This book concludes with coverage of semantic search capabilities, which is crucial for taking the search experience to the next level. By the end of Apache Solr, you will be proficient in designing and developing your search engine.