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FixpointState

uni_db::query::df_graph

Struct FixpointState 

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pub struct FixpointState { /* private fields */ }
Expand description

Per-rule state for fixpoint iteration.

Tracks accumulated facts and the delta (new facts from the latest iteration). Deduplication uses Arrow RowConverter with a persistent seen set (O(M) per iteration) when supported, with a legacy HashSet<Vec<ScalarKey>> fallback.

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impl FixpointState

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pub fn new( rule_name: String, schema: Arc<Schema>, key_column_indices: Vec<usize>, max_derived_bytes: usize, monotonic_agg: Option<MonotonicAggState>, strict_probability_domain: bool, ) -> FixpointState

Create a new fixpoint state for a rule.

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pub async fn merge_delta( &mut self, candidates: Vec<RecordBatch>, task_ctx: Option<Arc<TaskContext>>, ) -> Result<bool, DataFusionError>

Merge candidate rows into facts, computing delta (truly new rows).

Returns true if any new facts were added.

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pub fn is_converged(&self) -> bool

Check if this rule has converged (no new facts and aggs stable).

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pub fn all_facts(&self) -> &[RecordBatch]

Get all accumulated facts.

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pub fn all_delta(&self) -> &[RecordBatch]

Get the delta from the latest iteration.

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pub fn into_facts(self) -> Vec<RecordBatch>

Consume self and return facts.

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pub fn merge_best_by( &mut self, candidates: Vec<RecordBatch>, sort_criteria: &[SortCriterion], ) -> Result<bool, DataFusionError>

Merge candidates using BEST BY semantics.

Combines existing facts with new candidates, keeping only the best row per KEY group according to sort_criteria. Returns true if the best-per-KEY fact set actually changed (a genuinely better value was found or a new KEY appeared).

This replaces merge_delta for rules with BEST BY, enabling convergence on cyclic graphs where dominated ALONG values would otherwise produce an unbounded stream of “new” full-row facts.

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