Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Scaling Apache Solr

You're reading from   Scaling Apache Solr Optimize your searches using high-performance enterprise search repositories with Apache Solr

Arrow left icon
Product type Paperback
Published in Jul 2014
Publisher
ISBN-13 9781783981748
Length 298 pages
Edition 1st Edition
Languages
Tools
Concepts
Arrow right icon
Author (1):
Arrow left icon
Hrishikesh Vijay Karambelkar Hrishikesh Vijay Karambelkar
Author Profile Icon Hrishikesh Vijay Karambelkar
Hrishikesh Vijay Karambelkar
Arrow right icon
View More author details
Toc

Table of Contents (13) Chapters Close

Preface 1. Understanding Apache Solr FREE CHAPTER 2. Getting Started with Apache Solr 3. Analyzing Data with Apache Solr 4. Designing Enterprise Search 5. Integrating Apache Solr 6. Distributed Search Using Apache Solr 7. Scaling Solr through Sharding, Fault Tolerance, and Integration 8. Scaling Solr through High Performance 9. Solr and Cloud Computing 10. Scaling Solr Capabilities with Big Data A. Sample Configuration for Apache Solr Index

What this book covers

Chapter 1, Understanding Apache Solr, introduces readers to Apache Solr as a search server. It discusses problems addressed by Apache Solr, its architecture, features, and, finally, covers different use cases for Solr.

Chapter 2, Getting Started with Apache Solr, focuses on setting up the first Apache Solr instance. It provides a detailed step-by-step guide for installing and configuring Apache Solr. It also covers connecting to Solr through SolrJ libraries.

Chapter 3, Analyzing Data with Apache Solr, covers some of the common enterprise search problems of bringing information from disparate sources and different information flow patterns to Apache Solr with minimal losses. It also covers advanced topics for Apache Solr such as deduplication, and searching through images.

Chapter 4, Designing Enterprise Search, introduces its readers to the various aspects of designing a search for enterprises. It covers topics pertaining to different data processing patterns of enterprises, integration patterns, and a case study of designing a knowledge repository for the software IT industry.

Chapter 5, Integrating Apache Solr, focuses on the integration aspects of Apache Solr with different applications that are commonly used in any enterprise. It also covers different ways in which Apache Solr can be introduced by the enterprise to its users.

Chapter 6, Distributed Search Using Apache Solr, starts with the need for distributed search for an enterprise, and it provides a deep dive to building distributed search using Apache SolrCloud. Finally, the chapter covers common problems and a case study of distributed search using Apache Solr for the software industry.

Chapter 7, Scaling Solr through Sharding, Fault Tolerance, and Integration, discusses various aspects of enabling enterprise Solr search server to scaling by means of sharding and search result clustering. It covers integration aspects of Solr with other tools such as MongoDB, Carrot2, and Storm to achieve the scalable search solution for an enterprise.

Chapter 8, Scaling Solr through High Performance, provides insights of how Apache Solr can be transformed into a high-performance search engine for an enterprise. It starts with monitoring for performance, and how the Solr application server can be tuned for performing better with maximum utilization of the available sources.

Chapter 9, Solr and Cloud Computing, focuses on enabling Solr on cloud-based infrastructure for scalability. It covers different Solr strategies for cloud, their applications, and deep dive into using Solr in different types of cloud environment.

Chapter 10, Scaling Solr Capabilities with Big Data, covers aspects of working with a very high volume of data (Big Data), and how Solr can be used to work with Big Data. It discusses how Apache Hadoop and its ecosystem can be used to build and run efficient Big Data enterprise search solutions.

Appendix, Sample Configuration for Apache Solr, provides a reference configuration for different Solr configuration files with detailed explanations.

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image