Chapter 3. Key Solr concepts


This chapter covers

  • What differentiates Solr from traditional database technologies
  • The basic structure of Solr’s internal index
  • How Solr performs complex queries using terms, phrases, and fuzzy matching
  • How Solr calculates scores for matching queries to the most relevant documents
  • How to balance returning relevant results versus returning all possible results
  • How to model your content into denormalized documents
  • How Solr scales across servers to handle billions of documents and queries

Now that we have Solr up and running, it’s important to gain a basic understanding of how a search engine operates and why you’d choose to use Solr to store and retrieve your content. Our main goal for this chapter is to provide the theoretical underpinnings so you can understand and maximize your use of Solr.

If you have a solid background in search and information retrieval, then you may wish to skip some or all of this chapter, but if not, it will help you understand more advanced topics later in this book and maximize the quality of your users’ search experience.

3.1. Searching, matching, and finding content

3.2. Relevancy

3.3. Precision and Recall

3.4. Searching at scale

3.5. Summary