Full-Text Search Queries in Neo4j
Introduction
Full-text search allows for searching text fields in a database using natural language queries. In Neo4j, full-text search capabilities help to retrieve nodes and relationships based on specific text patterns rather than just exact matches.
What is Full-Text Search?
Full-text search is a feature that enables you to search for words or phrases within large volumes of text. It utilizes tokenization, stemming, and ranking to provide relevant results.
Indexing in Neo4j
To enable full-text search in Neo4j, you must create a full-text index. This index will allow you to perform searches efficiently.
Creating a Full-Text Index
CALL db.index.fulltext.createNodeIndex("PersonIndex", ["Person"], ["name", "bio"])
This command creates a full-text index named PersonIndex for nodes labeled Person on properties name and bio.
Querying with Full-Text Search
Once the index is created, you can perform full-text searches using the following syntax:
Executing a Full-Text Search
CALL db.index.fulltext.queryNodes("PersonIndex", "searchTerm") YIELD node, score
RETURN node, score
This command searches for nodes in PersonIndex that match searchTerm and returns the nodes along with their relevance score.
Best Practices
- Ensure indexes are updated regularly to maintain search performance.
- Use specific search terms to enhance relevance and accuracy of results.
- Consider using stemming and synonyms to improve search results.
- Monitor performance and adjust your queries accordingly.
FAQ
What is the difference between full-text search and regular search?
Full-text search analyzes the text and can find matches for words, phrases, and even partial matches, while regular search typically looks for exact matches only.
Can I search multiple properties at once?
Yes, when creating a full-text index, you can specify multiple properties to allow searching across them simultaneously.
What is the maximum number of tokens that can be indexed?
While Neo4j does not impose a strict limit on the number of tokens, it is advisable to keep the index size manageable for efficient searching.