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.
Get Course Info
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)
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
Ready to Get Started?
Contact us to learn more about this course and schedule your training.