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Solr for Developers

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Solr for Developers

Overview:

This course introduces students to the Solr platform. Through a combination of lecture, discussion, and labs students will gain hands-on experience configuring effective search and indexing.

What You Will Learn:

  • Solr installation and configuration
  • Solr architecture and design
  • Faceting, indexing, and search
  • Advanced topics including spell checking, suggestions, Multicore, and SolrCloud.

Duration:

Two days, optional third day for developers

Audience:

Developers, business users, administrators

Prerequisites:

All attendees should be experienced technical staff with a background in web application operations and, preferably, development.

Lab environment:

Amazon EC2 servers will be provided students for installation, administration and lab work. Students would need an SSH client and a browser to access the cluster.

Zero Install : There is no need to install Solr software on students’ machines! (although it is possible)

Detailed Outline

Overall Goal

Provide experienced web developers and technical staff with a comprehensive introduction to the Solr search platform. Teach software developer deep skills creating search solutions.

I. Fundamentals

  • Solr Overview
  • Installing and running Solr
  • Adding content to Solr
  • Reading a Solr XML response
  • Changing parameters in the URL
  • Using the browse interface
  • Labs: install Solr, run queries

II. Searching

  • Sorting results
  • Query parsers
  • More queries
  • Hardwiring request parameters
  • Adding fields to default search
  • Faceting
  • Result grouping
  • Labs: advanced queries, experiment with faceted search

III. Indexing

  • Adding your own content to Solr
  • Deleting data from Solr
  • Building a bookstore search
  • Adding book data
  • Exploring the book data
  • Dedupe update processor
  • Labs: indexing various document collections

IV. Schema Updating

  • Adding fields to the schema
  • Analyzing text
  • Labs: customize Solr schema

V. Relevance

  • Field weighting
  • Phrase queries
  • Function queries
  • Fuzzier search
  • Sounds-like
  • Labs: implementing queries for ¬†relevance

VI. Extended features

  • More-like-this
  • Geospatial
  • Spell checking
  • Suggestions
  • Highlighting
  • Pseudo-fields
  • Pseudo-joins
  • Multilanguage
  • Labs: implementing spell checking and suggestions

VII. Multicore

  • Adding more kinds of data
  • Labs: creating and administering cores

VIII. SolrCloud

  • Introduction
  • How SolrCloud works
  • Commit strategies
  • ZooKeeper
  • Managing Solr config files
  • Labs: administer SolrCloud

Developer sessions:

IX. Developing with Solr API

  • Talking to Solr through REST
  • Configuration
  • Indexing and searching
  • Solr and Spring
  • Labs: code to read and write Solr index, exercise in Spring with Solr

X. Developing with Lucene API

  • Building a Lucene index
  • Searching, viewing, debugging
  • Extracting text with Tika
  • Scaling Lucene indices on clusters
  • Lucene performance tuning
  • Labs: coding with Lucene

XI. Conclusion

  • Other approaches to search
    • ElasticSearch
    • DataStax Enterprise: Solr+Cassandra
    • Cloudera Solr integration
    • Blur
  • Future directions