What is the principle of sorting in Elasticsearch?

The sorting principle of Elasticsearch is based on inverted index and scoring algorithm. Inverted index is a data structure used to quickly locate documents by associating each word with the documents containing that word. With the help of inverted index, Elasticsearch can quickly find documents containing specific terms.

When searching, Elasticsearch first matches documents based on the query statement, and calculates a relevance score for each matching document. This score is calculated based on various factors including term frequency, document length, and query term position. Elasticsearch uses algorithms such as TF-IDF (term frequency-inverse document frequency) and BM25 to calculate the relevance score of documents.

Once the scores for all documents are calculated, Elasticsearch sorts the documents based on the scores to return the most relevant documents as search results. By default, Elasticsearch sorts by relevance score, but it can also be sorted by other fields such as date, price, etc.

Furthermore, Elasticsearch also supports sorting multiple fields and custom sorting rules. Custom sorting rules can be defined based on different business needs to ensure that search results are more tailored to requirements.