nips/119.md

NIP-119: AND Operator in Filters

Enable AND within a single tag filter by using an & modifier in filters for indexable tags.

filters: {
  "kinds": [1],
  "&t": ["meme", "cat"],
  "#t": ["black", "white"]
}
// returns kind `1` events with `t` tags that have both "meme" and "cat" that have the tag "black" or "white"

Rationale

• Reduce bandwidth for all, with an emphasis on mobile users: meme AND cat objectively consumes less bandwidth than meme OR cat
• Reduce clock-time for relays, indexing with AND is fast for all common index formats, and faster compared to OR for some index formats. (See section below)
• Reduce client-side caching requirements
• Reduce centralization vectors by reducing or even eliminating the need for centralized REST, GraphQL APIs or specialized relay "feed" endpoints.
• Give relays the option to be more useful at the protocol level while improving efficiency for all parties.

Rules

• AND MUST take precedence over OR
• Tags used in AND SHOULD NOT be used in standard OR tags [#]
• Any tag used in AND SHOULD be ignored in OR

Considerations

• New field for NIP-11.limitations: max_tags_per_and and max_tags_and
• Benchmarking should be conducted to validate that bandwidth and protocol usability as benefits supercede implementation and clock-time cost.

Index Efficiency

Index Type	AND Operation Efficiency	OR Operation Efficiency	Notes
B-Tree	High	Moderate	B-Tree indexes are very efficient for AND operations, especially with compound indexes. For OR operations, they are less efficient than for AND, as the database engine might need to traverse multiple paths.
Bitmap	High	High	Bitmap indexes excel in both AND and OR operations, particularly for columns with low cardinality. They utilize fast bitwise operations, making them ideal for read-heavy environments.
Hash	Not Applicable	Not Applicable	Hash indexes are designed for equality checks and do not directly support range-based queries or optimize for AND/OR operations efficiently.
Full-Text	High	High	Optimized for text search, full-text indexes efficiently handle both AND and OR conditions, making them suitable for complex text queries.