Graph on INFINI Pizza

Traverse query

Mon, 01 Jan 0001 00:00:00 +0000

Traverse query #

Term and full-text queries match document content; none of them can ask “what is connected to these documents?” — the question citation graphs, reference data and knowledge graphs are made of. The traverse query answers it: a bounded graph traversal over a relation-typed edge field — starting from seed documents, walk the edges up to max_depth hops and emit every reached node as a hit.

Scores encode distance — 1.0 / (1.0 + depth) — so seeds outrank 1-hop neighbors, which outrank 2-hop neighbors, and the standard top-K collector orders the results.

Graph projection block

Mon, 01 Jan 0001 00:00:00 +0000

Graph projection block #

Add a graph block to any search request and the response carries a graph — nodes and edges — built from the hit set, alongside the normal hits. Where the traverse query searches by walking edges, the graph block renders: it takes the documents a query already found and projects them into a node/edge structure a UI (or a GraphRAG pipeline) can consume directly.

graph LR subgraph walk["traverse — searches by walking"] S("seeds") -->|"walk edges
up to max_depth"| H1["hits — every reached node,
scored by distance"] end subgraph render["graph — renders what was found"] Q("any query") --> H2("hit set") H2 -->|"project the relation field"| G["nodes + edges
for a UI or GraphRAG"] end

Lesson 5 — Graph traversal

Mon, 01 Jan 0001 00:00:00 +0000

Lesson 5 — Graph traversal #

Relations are the first of the two features that most distinguish Pizza from a plain text index: edges as a first-class query target. This lesson walks edges inside one collection — the traversal sections run live in the browser widget, and the modeling section at the end is curl against a live node.

Graph queries are also the one lesson without a SQL pairing: traverse stays DSL-side — it is demand-gated outside the SQL M1 subset, which stops at the single-collection statement.