When a query is passed to Solr, it is converted to an appropriate query string that is then executed by Solr. For each document in the result, Solr calculates the relevance score according to which the document is sorted. By default higher scoring documents are given priority in the result.
The Solr relevancy algorithm is known as the tf-idf model where tf stands for term frequency and idf stands for inverse document frequency. The meaning of the parameters used in relevance calculation so we can interpret the output of debug query are explained as follows:
tf: The term frequency is the frequency with which a term appears in a document. Higher term frequency results in a high document score.
idf: The inverse document frequency is the inverse of the number of documents in which the term appears. It indicates the rarity of the term across all documents in the index. Documents having a rare term are scored higher.
