Apache Solr Beginner's Guide

Apache Solr Beginner's Guide

By : Alfredo Serafini

Buy this Book

Apache Solr Beginner's Guide

By: Alfredo Serafini

Buy this Book

Overview of this book

With over 40 billion web pages, the importance of optimizing a search engine's performance is essential. Solr is an open source enterprise search platform from the Apache Lucene project. Full-text search, faceted search, hit highlighting, dynamic clustering, database integration, and rich document handling are just some of its many features. Solr is highly scalable thanks to its distributed search and index replication. Solr is written in Java and runs as a standalone full-text search server within a servlet container such as Apache Tomcat or Jetty. Solr uses the Lucene Java search library at its core for full-text indexing and search, and has REST-like HTTP/XML and JSON APIs that make it usable with most popular programming languages. Solr's powerful external configuration allows it to be tailored to many types of application without Java coding, and it has a plugin architecture to support more advanced customization. With Apache Solr Beginner's Guide you will learn how to configure your own search engine experience. Using real data as an example, you will have the chance to start writing step-by-step, simple, real-world configurations and understand when and where to adopt this technology. Apache Solr Beginner's Guide will start by letting you explore a simple search over real data. You will then go through a step-by-step description that gives you the chance to explore several practical features. At the end of the book you will see how Solr is used in different real-world contexts. Using data from public domains like DBpedia, you will define several different configurations, exploring some of the most interesting Solr features, such as faceted search and navigation, auto-suggestion, and rich document indexing. You will see how to configure different analysers for handling different data types, without programming. You will learn the basics of Solr, focusing on real-world examples and practical configurations.

Apache Solr Beginner's Guide

Credits

About the Author

Acknowledgments

About the Reviewers

www.PacktPub.com

Preface

Free Chapter

Getting Ready with the Essentials

Understanding Solr

Learning the powerful aspects of Solr

Working with Java installation

Installing and testing Solr

Time for action – starting Solr for the first time

Time for action – posting some example data

Time for action – testing Solr with cURL

Who uses Solr?

Resources on Solr

How will we use Solr?

Summary

Indexing with Local PDF Files

Understanding and using an index

Posting example documents to the first Solr core

Time for action – configuring Solr Home and Solr core discovery

Time for action – writing a simple solrconfig.xml file

Time for action – writing a simple schema.xml file

Time for action – starting the new core

Time for action – defining an example document

Time for action – indexing an example document with cURL

Time for action – updating an existing document

Time for action – cleaning an index

Creating an index prototype from PDF files

Time for action – defining the schema.xml file with only dynamic fields and tokenization

Time for action – writing a simple solrconfig.xml file with an update handler

Time for action – using Tika and cURL to extract text from PDFs

Time for action – finding copies of the same files with deduplication

Time for action – looking inside an index with SimpleTextCodec

Understanding the structure of an inverted index

Writing the full configuration for our PDF index example

Summarizing some easy recipes for the maintenance of an index

Summary

Indexing Example Data from DBpedia – Paintings

Harvesting paintings' data from DBpedia

Analyzing the entities that we want to index

Writing Solr core configurations for the first tests

Time for action – defining the basic solrconfig.xml file

Time for action – defining the simple schema.xml file

Time for action – listing all the fields with the CSV output

Defining a new Solr core for our Painting entity

Time for action – refactoring the schema.xml file for the paintings core by introducing tokenization and stop words

Collecting the paintings data from DBpedia

Testing our paintings core

Time for action - looking at a field using the Schema browser in the web interface

Time for action – searching the new data in the paintings core

Summary

Searching the Example Data

Looking at Solr's standard query parameters

Time for action – searching for all documents with pagination

Time for action – projecting fields with fl

Time for action – adding a custom DocTransformer to hide empty fields in the results

Time for action – searching for terms with a Boolean query

Time for action – using q.op for the default Boolean operator

Time for action – selecting documents with the filter query

Time for action – searching for incomplete terms with the wildcard query

Time for action – using the Boost options

Time for action – searching for similar terms with fuzzy search

Time for action – writing a simple phrase query example

Time for action – playing with range queries

Time for action – sorting documents with the sort parameter

Time for action – adding a default parameter to a handler

Time for action – enabling XSLT Response Writer with Luke

Summary

Extending Search

Looking at different search parsers – Lucene, Dismax, and Edismax

Time for action – inspecting results using the stats and debug components

Time for action – debugging a query with the Lucene parser

Time for action – debugging a query with the Dismax parser

Time for action – executing a nested Edismax query

A short list of search components

Time for action – executing a simple pseudo-join query

Time for action – generating highlighted snippets over a term

Some idea about geolocalization with Solr

Time for action – creating a repository of cities

Time for action – expanding the original data with coordinates during the update process

Performing editorial correction on boosting

Introducing the spellcheck component

Time for action – playing with spellchecks

Summary

Using Faceted Search – from Searching to Finding

Exploring documents suggestion and matching with faceted search

Time for action – prototyping an auto-suggester with facets

Time for action – creating wordclouds on facets to view and analyze data

Thinking about faceted search and findability

Time for action – defining facets over enumerated fields

Performing data normalization for the keyword field during the update phase

Time for action – finding interesting topics using faceting on tokenized fields with a filter query

Using filter queries for caching filters

Time for action – finding interesting subjects using a facet query

Time for action – using range queries and facet range queries

Time for action – using a hierarchical facet (pivot)

Introducing group and field collapsing

Time for action – grouping results

Playing with terms

Time for action – playing with a term suggester

Time for action – having a look at the term vectors

Introducing the More Like This component and recommendations

Time for action – obtaining similar documents by More Like This

Summary

Working with Multiple Entities, Multicores, and Distributed Search

Working with multiple entities

Time for action – searching for cities using multiple core joins

Using sharding for distributed search

Time for action – playing with sharding (distributed search)

Time for action – finding a document from any shard

Collecting some ideas on schemaless versus normalization

Time for action – testing SolrCloud and Zookeeper locally

Summary

Indexing External Data sources

Stepping further into the real world

Time for action – indexing data from a database (for example, a blog or an e-commerce website)

Time for action – handling sub-entities (for example, joins on complex data)

Time for action – indexing incrementally using delta imports

Time for action – indexing CSV (for example, open data)

Time for action – importing Solr XML document files

Time for action – indexing rich documents (for example, PDF)

Adding more consideration about tuning

Time for action – indexing artist data from Tate Gallery and DBpedia

Summary

Introducing Customizations

Looking at the Solr customizations

Playing with specific languages

Time for action – detecting language with Tika and LangDetect

Introducing stemming for query expansion

Time for action – adopting a stemmer

Following an example plugin lifecycle

Time for action – writing a new ResponseWriter plugin with the Thymeleaf library

Using Maven for development

Time for action – integrating Stanford NER for Named Entity extraction

Summary

Solr Clients and Integrations

Introducing SolrJ – an embedded or remote Solr client using the Java (JVM) API

Time for action – playing with an embedded Solr instance

Choosing between an embedded or remote Solr instance

Time for action – playing with an external HttpSolrServer

Time for action – using Bean Scripting Framework and JavaScript

Writing Solr clients and integrations outside JVM

Summary

Pop Quiz Answers

Chapter 1, Getting Ready with the Essentials

Chapter 2, Indexing with Local PDF Files

Chapter 3, Indexing Example Data from DBpedia – Paintings

Chapter 4, Searching the Example Data

Chapter 5, Extending Search

Chapter 6, Using Faceted Search – from Searching to Finding

Chapter 7, Working with Multiple Entities, Multicores, and Distributed Search

Chapter 8, Indexing External Data sources

Chapter 9, Introducing Customizations

Appendix, Solr Clients and Integrations

Index

Customer Reviews

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Time for action – expanding the original data with coordinates during the update process

Defining an external and specific dedicated index is not unusual in a real context, when sometimes you would like to index and search for specific kind of entities. Thus, you will be able to recognize them and annotate them in your own data in a way similar to what we already did for highlighting, but in a more controlled way and with more semantics. A good experiment at this time, involving just a bit of scripting, could be expanding the information we have about our city at the time of posting them to be indexed.

Suppose we have already collected information about cities, and we want to use it to expand the information about every new document when it contains a known city. I have defined a new paintings_geo core that extends the usual painting with updating capabilities, as in the following snippet of solrconfig.xml:
```
<updateHandler class="solr.DirectUpdateHandler2">
 <updateLog>
 &lt...
```

Apache Solr Beginner's Guide

By : Alfredo Serafini

Apache Solr Beginner's Guide

By: Alfredo Serafini

Overview of this book

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Apache Solr Beginner's Guide

Time for action – expanding the original data with coordinates during the update process