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  • Book Overview & Buying Scaling Apache Solr
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Scaling Apache Solr

Scaling Apache Solr

By : Vijay Karambelkar
4.7 (3)
Buy this Book
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Scaling Apache Solr

Scaling Apache Solr

4.7 (3)
By: Vijay Karambelkar
Buy this Book

Overview of this book

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.
Table of Contents (13 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. Understanding Apache Solr
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1. Understanding Apache Solr
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Challenges in enterprise search
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Apache Solr – an overview
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Features of Apache Solr
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Apache Solr architecture
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Practical use cases for Apache Solr
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Summary
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2. Getting Started with Apache Solr
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2. Getting Started with Apache Solr
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Setting up Apache Solr
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Understanding the Solr structure
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Configuring the Apache Solr for enterprise
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Understanding SolrJ
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Summary
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3. Analyzing Data with Apache Solr
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3. Analyzing Data with Apache Solr
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Understanding enterprise data
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Loading data using native handlers
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Working with rich documents
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Importing structured data from the database
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Advanced topics with Solr
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Summary
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4. Designing Enterprise Search
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4. Designing Enterprise Search
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Designing aspects for enterprise search
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Enterprise search data-processing patterns
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Data integrating pattern for search
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Case study – designing an enterprise knowledge repository search for software IT services
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Summary
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5. Integrating Apache Solr
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5. Integrating Apache Solr
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Empowering the Java Enterprise application with Solr search
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Integration with client technologies
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Case study – Apache Solr and Drupal
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Summary
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6. Distributed Search Using Apache Solr
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6. Distributed Search Using Apache Solr
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Need for distributed search
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Understanding SolrCloud
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Building enterprise distributed search using SolrCloud
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Common problems and resolutions
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Case study – distributed enterprise search server for the software industry
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Summary
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7. Scaling Solr through Sharding, Fault Tolerance, and Integration
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7. Scaling Solr through Sharding, Fault Tolerance, and Integration
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Enabling search result clustering with Carrot2
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Sharding and fault tolerance
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Searching Solr documents in near real time
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Solr with MongoDB
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Scaling Solr through Storm
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Summary
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8. Scaling Solr through High Performance
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8. Scaling Solr through High Performance
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Monitoring performance of Apache Solr
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Tuning Solr JVM and container
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Optimizing Solr schema and indexing
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Speeding Solr through Solr caching
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Improving runtime search for Solr
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Optimizing SolrCloud
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Summary
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9. Solr and Cloud Computing
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9. Solr and Cloud Computing
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Enterprise search on Cloud
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Solr on Cloud strategies
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Running Solr on Cloud (IaaS and PaaS)
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Running Solr on Cloud (SaaS) and enterprise search as a service
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Summary
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10. Scaling Solr Capabilities with Big Data
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10. Scaling Solr Capabilities with Big Data
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Apache Solr and HDFS
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Big Data search on Katta
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Using the Solr 1045 patch – map-side indexing
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Using the Solr 1301 patch – reduce-side indexing
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Apache Solr and Cassandra
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Advanced analytics with Solr
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Summary
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A. Sample Configuration for Apache Solr
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A. Sample Configuration for Apache Solr
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schema.xml
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solrconfig.xml
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spellings.txt
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synonyms.txt
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protwords.txt
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stopwords.txt
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Index
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Index

Chapter 3. Analyzing Data with Apache Solr

Many organizations suffer when dealing with huge amounts of data generated in different formats, due to incremental IT enablement of their business processes. Dealing with vast varieties of data becomes a challenge for any enterprise search engine. This data may reside in a database, or would be streamed over HTTP protocol. To address these problems, many companies provided tools to bring in data from various sources into one form. These were Extract Transfer Load (ETL) tools mainly used for business intelligence (BI) and analytics solutions. Luckily, Apache Solr provides different ways of dealing with different data types, when it comes down to information collection. We have already read about indexing in Chapter 1, Understanding Apache Solr. In this chapter, we are going to look at analyzing different types of data and how to deal with them. We will focus on the following topics:

  • Configuring handlers
  • Apache Tika integration
  • Importing...
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Programming languages
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