Solr for Developers

Enable participants to install, configure, and optimize Solr search applications—including faceting, indexing pipelines, and SolrCloud—for high‑relevance, scalable search solutions.

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Audience: Developers, business users, administrators

Duration: Two days, optional third day for developers

Format: Lectures and hands‑on labs (50% lecture, 50% lab)

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.

Objective

Enable participants to install, configure, and optimize Solr search applications—including faceting, indexing pipelines, and SolrCloud—for high‑relevance, scalable search solutions.

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.

Course Details

Audience: Developers, business users, administrators

Duration: Two days, optional third day for developers

Format: Lectures and hands‑on labs (50% lecture, 50% lab)

Prerequisites:

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

Setup: Amazon EC2 servers will be provided for installation, administration, and lab work • SSH client • Browser • Zero Install

Detailed Outline

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

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

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

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

Field weighting
Phrase queries
Function queries
Fuzzier search
Sounds‑like
Labs: implementing queries for relevance

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

Adding more kinds of data
Labs: creating and administering cores

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

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

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

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