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Scaling Apache Solr

By : Hrishikesh Vijay Karambelkar
Book Image

Scaling Apache Solr

By: Hrishikesh Vijay Karambelkar

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Scaling Apache Solr
Hrishikesh Vijay Karambelkar
Jul, 2014 | 298 pages
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Table of Contents (18 chapters)
Scaling Apache Solr
Scaling Apache Solr
Credits
Credits
About the Author
About the Author
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Understanding Apache Solr
Understanding Apache Solr
Challenges in enterprise search
Apache Solr – an overview
Features of Apache Solr
Apache Solr architecture
Practical use cases for Apache Solr
Summary
2
Getting Started with Apache Solr
Getting Started with Apache Solr
Setting up Apache Solr
Understanding the Solr structure
Configuring the Apache Solr for enterprise
Understanding SolrJ
Summary
3
Analyzing Data with Apache Solr
Analyzing Data with Apache Solr
Understanding enterprise data
Loading data using native handlers
Working with rich documents
Importing structured data from the database
Advanced topics with Solr
Summary
4
Designing Enterprise Search
Designing Enterprise Search
Designing aspects for enterprise search
Enterprise search data-processing patterns
Data integrating pattern for search
Case study – designing an enterprise knowledge repository search for software IT services
Summary
5
Integrating Apache Solr
Integrating Apache Solr
Empowering the Java Enterprise application with Solr search
Integration with client technologies
Case study – Apache Solr and Drupal
Summary
6
Distributed Search Using Apache Solr
Distributed Search Using Apache Solr
Need for distributed search
Understanding SolrCloud
Building enterprise distributed search using SolrCloud
Common problems and resolutions
Case study – distributed enterprise search server for the software industry
Summary
7
Scaling Solr through Sharding, Fault Tolerance, and Integration
Scaling Solr through Sharding, Fault Tolerance, and Integration
Enabling search result clustering with Carrot2
Sharding and fault tolerance
Searching Solr documents in near real time
Solr with MongoDB
Scaling Solr through Storm
Summary
8
Scaling Solr through High Performance
Scaling Solr through High Performance
Monitoring performance of Apache Solr
Tuning Solr JVM and container
Optimizing Solr schema and indexing
Speeding Solr through Solr caching
Improving runtime search for Solr
Optimizing SolrCloud
Summary
9
Solr and Cloud Computing
Solr and Cloud Computing
Enterprise search on Cloud
Solr on Cloud strategies
Running Solr on Cloud (IaaS and PaaS)
Running Solr on Cloud (SaaS) and enterprise search as a service
Summary
10
Scaling Solr Capabilities with Big Data
Scaling Solr Capabilities with Big Data
Apache Solr and HDFS
Big Data search on Katta
Using the Solr 1045 patch – map-side indexing
Using the Solr 1301 patch – reduce-side indexing
Apache Solr and Cassandra
Advanced analytics with Solr
Summary
Sample Configuration for Apache Solr
Sample Configuration for Apache Solr
schema.xml
solrconfig.xml
spellings.txt
synonyms.txt
protwords.txt
stopwords.txt
Index
Index

Summary

In this chapter, we focused mainly on working with big databases that work on large datasets for processing and how Apache Solr can add value to them. We also looked at some of the implementations to integrate Apache Solr with MongoDB, Apache Cassandra, and Apache Storm. We also looked at some of the advanced topics such as clustering the outcomes/results from Apache Solr using Carrot2. In the next chapter, we will be focusing on optimizing Apache Solr for high performance.

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