Practical Apache Lucene 8

Atri Sharma

ISBN 10: 1484263448 / ISBN 13: 9781484263440

Published by Apress, Apress Nov 2020, 2020

About this Item

Neuware -Gain a thorough knowledge of Lucene's capabilities and use it to develop your own search applications. This book explores the Java-based, high-performance text search engine library used to build search capabilities in your applications. Starting with the basics of Lucene and searching, you will learn about the types of queries used in it and also take a look at scoring models. Applying this basic knowledge, you will develop a hello world app using basic Lucene queries and explore functions like scoring and document level boosting.Along the way you will also uncover the concepts of partial searching and matching in Lucene and then learn how to integrate geographical information (geospatial data) in Lucene using spatial queries and n-dimensional indexing. This will prepare you to build a location-aware search engine with a representative data set that allows location constraints to be specified during a search. Yoüll also develop atext classifier using Lucene and Apache Mahout, a popular machine learning framework.After a detailed review of performance bench-marking and common issues associated with it, yoüll learn some of the best practices of tuning the performance of your application. By the end of the book yoüll be able to build your first Lucene patch, where you will not only write your patch, but also test it and ensure it adheres to community coding standards.What Yoüll LearnMaster the basics of Apache LuceneUtilize different query types in Apache LuceneExplore scoring and document level boostingIntegrate geospatial data into your applicationWho This Book Is ForDevelopers wanting to learn the finer details of Apache Lucene by developing a series of projects with it.

Seller Inventory # 9781484263440

Bibliographic Details

• Title: Practical Apache Lucene 8
• Publisher: Apress, Apress Nov 2020
• Publication Date: 2020
• Language: English
• ISBN 10: 1484263448
• ISBN 13: 9781484263440
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 8D millimeters 235 millimeters width by 155 millimeters height by 8 millimeters depth
• Weight: 201 grams

About this title

Synopsis

Gain a thorough knowledge of Lucene's capabilities and use it to develop your own search applications. This book explores the Java-based, high-performance text search engine library used to build search capabilities in your applications.  

Starting with the basics of Lucene and searching, you will learn about the types of queries used in it and also take a look at scoring models. Applying this basic knowledge, you will develop a hello world app using basic Lucene queries and explore functions like scoring and document level boosting.

Along the way you will also uncover the concepts of partial searching and matching in Lucene and then learn how to integrate geographical information (geospatial data) in Lucene using spatial queries and n-dimensional indexing. This will prepare you to build a location-aware search engine with a representative data set that allows location constraints to be specified during a search. You’ll also develop atext classifier using Lucene and Apache Mahout, a popular machine learning framework.

After a detailed review of performance bench-marking and common issues associated with it, you’ll learn some of the best practices of tuning the performance of your application. By the end of the book you’ll be able to build your first Lucene patch, where you will not only write your patch, but also test it and ensure it adheres to community coding standards.

What You’ll Learn

• Master the basics of Apache Lucene
• Utilize different query types in Apache Lucene
• Explore scoring and document level boosting
• Integrate geospatial data into your application

Who This Book Is For

Developers wanting to learn the finer details of Apache Lucene by developing a series of projects with it. 

About the Author

Atri is a distributed systems engineer with expertise in building and scaling large data oriented systems, and an Apache Lucene/Solr committer. He has worked for Microsoft, where he was responsible for scaling the storage and query engines for Azure CosmosDB. He is also a long time PostgreSQL contributor and an Apache committer and PMC member for HAWQ, MADLib, and Apex.