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  • Book Overview & Buying Apache Solr Search Patterns
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Apache Solr Search Patterns

Apache Solr Search Patterns

By : Jayant Kumar
4.5 (2)
Buy this Book
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Apache Solr Search Patterns

Apache Solr Search Patterns

4.5 (2)
By: Jayant Kumar
Buy this Book

Overview of this book

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.
Table of Contents (12 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Solr Indexing Internals
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1. Solr Indexing Internals
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The job site problem statement – Solr indexing fundamentals
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Working of analyzers, tokenizers, and filters
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Handling a multilingual search
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Measuring the quality of search results
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The e-commerce problem statement
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The job site problem statement
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Challenges of large-scale indexing
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The SolrCloud solution
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Summary
2
2. Customizing the Solr Scoring Algorithm
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2. Customizing the Solr Scoring Algorithm
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Relevance calculation
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Building a custom scorer
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Drawbacks of the TF-IDF model
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The information gain model
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Implementing the information gain model
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Options to TF-IDF similarity
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Summary
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3. Solr Internals and Custom Queries
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3. Solr Internals and Custom Queries
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Working of a scorer on an inverted index
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Working of OR and AND clauses
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The eDisMax query parser
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Using BRS queries instead of DisMax
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Building a custom query parser
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Summary
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4. Solr for Big Data
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4. Solr for Big Data
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Introduction to big data
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Getting data points using facets
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Radius faceting for location-based data
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Data analysis using pivot faceting
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Graphs for analytics
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Summary
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5. Solr in E-commerce
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5. Solr in E-commerce
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Designing an e-commerce search
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Handling unclean data
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Handling variations in the product
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Sorting
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Problems and solutions of flash sale searches
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Faceting with the option of multi-select
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Faceting with hierarchical taxonomy
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Faceting with size
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Implementing semantic search
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Optimizations
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Summary
6
6. Solr for Spatial Search
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6. Solr for Spatial Search
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Features of spatial search
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Lucene 4 spatial module
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Indexing for spatial search
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Searching and filtering on a spatial index
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Distance sort and relevancy boost
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Advanced concepts
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Summary
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7. Using Solr in an Advertising System
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7. Using Solr in an Advertising System
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Ad system functionalities
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Architecture of an ad distribution system
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Requirements of an ad distribution system
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Performance improvements
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Merging Solr with Redis
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Summary
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8. AJAX Solr
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8. AJAX Solr
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The purpose of AJAX Solr
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The AJAX Solr architecture
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Working with AJAX Solr
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Performance tuning
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Summary
9
9. SolrCloud
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9. SolrCloud
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The SolrCloud architecture
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Centralized configuration
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Setting up SolrCloud
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Distributed indexing and search
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Routing documents to a particular shard
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Adding more nodes to the SolrCloud
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Fault tolerance and high availability in SolrCloud
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Advanced sharding with SolrCloud
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Asynchronous calls
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Migrating documents to another collection
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Sizing and monitoring of SolrCloud
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Using SolrCloud as a NoSQL database
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Summary
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10. Text Tagging with Lucene FST
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10. Text Tagging with Lucene FST
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An overview of FST and text tagging
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Implementation of FST in Lucene
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Text tagging algorithms
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Using Solr for text tagging
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Implementing a text tagger using Solr
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Summary
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Index
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Index

Summary

In this chapter, we went through most of the aspects of SolrCloud. We understood the architecture of SolrCloud, constructed a setup for SolrCloud using ZooKeeper servers, and created our collections on the cloud. We saw the advantages of routing and how to implement it. We saw how SolrCloud addresses the horizontal scalability, high availability, and distributed indexing and search requirements for a large-scale Solr deployment. We saw how to manage the shards in SolrCloud and monitor SolrCloud. We can use the monitoring information to size the cores in SolrCloud and scale it further. We also saw that SolrCloud can be used as a NoSQL database.

In the next chapter, we will explore text tagging using the Lucene Finite State Transducer (FST). We will delve into FSTs and how they can be implemented using Lucene and SolrCloud?

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Tech Concepts
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Programming languages
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