concept pivot faceting in category solr

This is an excerpt from Manning's book Solr in Action. Login to get full access to this book.

Although Solr serves as a powerful text search engine, finding and returning documents based upon keywords is far from its only common use. You have seen many of Solr’s core document search capabilities—such as rich text analysis, hit highlighting, and results grouping—that enhance the relevancy and usefulness of the list of results returned for a query. Although presenting the specific documents that best match a query is important for many search applications, another common use case for Solr is reporting aggregate results for data analytics capabilities. Pivot faceting, Solr’s ability to return multiple levels of hierarchical facet results, enables the computation of an arbitrary number of aggregate breakdowns in a single Solr request, making Solr efficient for use in data analytics reporting.

In chapter 8, you learned all about faceting in Solr, and how it can be used to power interesting data analytics and subsequent data visualizations. All of the examples demonstrated in chapter 8—field faceting, range faceting, and query faceting—were based upon the idea of returning aggregate counts for values based upon a single field or query. In many cases, however, it can be useful to provide nested facets: facets which return aggregate calculations that can pivot on values from multiple fields (functioning similarly to pivot tables in modern spreadsheet applications). Solr supports an advanced form of faceting called pivot faceting (or sometimes decision-tree faceting) that can provide contingent facet counts based upon values from multiple fields.