mirror of
https://github.com/meilisearch/meilisearch.git
synced 2024-11-23 02:27:40 +08:00
Remove comments and add documentation
This commit is contained in:
parent
4829348d6e
commit
2da86b31a6
@ -26,7 +26,6 @@ pub fn apply_distinct_rule(
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ctx: &mut SearchContext,
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field_id: u16,
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candidates: &RoaringBitmap,
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// TODO: add a universe here, such that the `excluded` are a subset of the universe?
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) -> Result<DistinctOutput> {
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let mut excluded = RoaringBitmap::new();
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let mut remaining = RoaringBitmap::new();
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@ -206,7 +206,7 @@ impl State {
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)?;
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intersection &= &candidates;
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if !intersection.is_empty() {
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// TODO: although not really worth it in terms of performance,
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// Although not really worth it in terms of performance,
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// if would be good to put this in cache for the sake of consistency
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let candidates_with_exact_word_count = if count_all_positions < u8::MAX as usize {
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ctx.index
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@ -32,7 +32,7 @@ impl<T> Interned<T> {
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#[derive(Clone)]
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pub struct DedupInterner<T> {
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stable_store: Vec<T>,
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lookup: FxHashMap<T, Interned<T>>, // TODO: Arc
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lookup: FxHashMap<T, Interned<T>>,
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}
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impl<T> Default for DedupInterner<T> {
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fn default() -> Self {
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@ -1,5 +1,4 @@
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/// Maximum number of tokens we consider in a single search.
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// TODO: Loic, find proper value here so we don't overflow the interner.
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pub const MAX_TOKEN_COUNT: usize = 1_000;
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/// Maximum number of prefixes that can be derived from a single word.
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@ -92,7 +92,7 @@ impl QueryGraph {
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/// which contains ngrams.
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pub fn from_query(
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ctx: &mut SearchContext,
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// NOTE: the terms here must be consecutive
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// The terms here must be consecutive
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terms: &[LocatedQueryTerm],
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) -> Result<(QueryGraph, Vec<LocatedQueryTerm>)> {
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let mut new_located_query_terms = terms.to_vec();
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@ -103,7 +103,7 @@ impl QueryGraph {
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let root_node = 0;
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let end_node = 1;
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// TODO: we could consider generalizing to 4,5,6,7,etc. ngrams
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// Ee could consider generalizing to 4,5,6,7,etc. ngrams
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let (mut prev2, mut prev1, mut prev0): (Vec<u16>, Vec<u16>, Vec<u16>) =
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(vec![], vec![], vec![root_node]);
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@ -132,7 +132,6 @@ impl QueryTermSubset {
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if full_query_term.ngram_words.is_some() {
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return None;
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}
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// TODO: included in subset
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if let Some(phrase) = full_query_term.zero_typo.phrase {
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self.zero_typo_subset.contains_phrase(phrase).then_some(ExactTerm::Phrase(phrase))
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} else if let Some(word) = full_query_term.zero_typo.exact {
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@ -182,7 +181,6 @@ impl QueryTermSubset {
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let word = match &self.zero_typo_subset {
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NTypoTermSubset::All => Some(use_prefix_db),
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NTypoTermSubset::Subset { words, phrases: _ } => {
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// TODO: use a subset of prefix words instead
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if words.contains(&use_prefix_db) {
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Some(use_prefix_db)
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} else {
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@ -204,7 +202,6 @@ impl QueryTermSubset {
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ctx: &mut SearchContext,
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) -> Result<BTreeSet<Word>> {
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let mut result = BTreeSet::default();
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// TODO: a compute_partially funtion
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if !self.one_typo_subset.is_empty() || !self.two_typo_subset.is_empty() {
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self.original.compute_fully_if_needed(ctx)?;
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}
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@ -300,7 +297,6 @@ impl QueryTermSubset {
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let mut result = BTreeSet::default();
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if !self.one_typo_subset.is_empty() {
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// TODO: compute less than fully if possible
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self.original.compute_fully_if_needed(ctx)?;
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}
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let original = ctx.term_interner.get_mut(self.original);
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@ -139,7 +139,6 @@ pub fn number_of_typos_allowed<'ctx>(
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let min_len_one_typo = ctx.index.min_word_len_one_typo(ctx.txn)?;
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let min_len_two_typos = ctx.index.min_word_len_two_typos(ctx.txn)?;
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// TODO: should `exact_words` also disable prefix search, ngrams, split words, or synonyms?
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let exact_words = ctx.index.exact_words(ctx.txn)?;
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Ok(Box::new(move |word: &str| {
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@ -250,8 +249,6 @@ impl PhraseBuilder {
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} else {
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// token has kind Word
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let word = ctx.word_interner.insert(token.lemma().to_string());
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// TODO: in a phrase, check that every word exists
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// otherwise return an empty term
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self.words.push(Some(word));
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}
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}
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@ -1,5 +1,48 @@
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#![allow(clippy::too_many_arguments)]
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/** Implements a "PathVisitor" which finds all paths of a certain cost
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from the START to END node of a ranking rule graph.
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A path is a list of conditions. A condition is the data associated with
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an edge, given by the ranking rule. Some edges don't have a condition associated
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with them, they are "unconditional". These kinds of edges are used to "skip" a node.
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The algorithm uses a depth-first search. It benefits from two main optimisations:
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- The list of all possible costs to go from any node to the END node is precomputed
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- The `DeadEndsCache` reduces the number of valid paths drastically, by making some edges
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untraversable depending on what other edges were selected.
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These two optimisations are meant to avoid traversing edges that wouldn't lead
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to a valid path. In practically all cases, we avoid the exponential complexity
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that is inherent to depth-first search in a large ranking rule graph.
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The DeadEndsCache is a sort of prefix tree which associates a list of forbidden
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conditions to a list of traversed conditions.
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For example, the DeadEndsCache could say the following:
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- Immediately, from the start, the conditions `[a,b]` are forbidden
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- if we take the condition `c`, then the conditions `[e]` are also forbidden
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- and if after that, we take `f`, then `[h,i]` are also forbidden
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- etc.
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- if we take `g`, then `[f]` is also forbidden
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- etc.
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- etc.
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As we traverse the graph, we also traverse the `DeadEndsCache` and keep a list of forbidden
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conditions in memory. Then, we know to avoid all edges which have a condition that is forbidden.
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When a path is found from START to END, we give it to the `visit` closure.
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This closure takes a mutable reference to the `DeadEndsCache`. This means that
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the caller can update this cache. Therefore, we must handle the case where the
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DeadEndsCache has been updated. This means potentially backtracking up to the point
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where the traversed conditions are all allowed by the new DeadEndsCache.
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The algorithm also implements the `TermsMatchingStrategy` logic.
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Some edges are augmented with a list of "nodes_to_skip". Skipping
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a node means "reaching this node through an unconditional edge". If we have
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already traversed (ie. not skipped) a node that is in this list, then we know that we
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can't traverse this edge. Otherwise, we traverse the edge but make sure to skip any
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future node that was present in the "nodes_to_skip" list.
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The caller can decide to stop the path finding algorithm
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by returning a `ControlFlow::Break` from the `visit` closure.
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*/
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use std::collections::{BTreeSet, VecDeque};
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use std::iter::FromIterator;
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use std::ops::ControlFlow;
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@ -12,30 +55,41 @@ use crate::search::new::query_graph::QueryNode;
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use crate::search::new::small_bitmap::SmallBitmap;
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use crate::Result;
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/// Closure which processes a path found by the `PathVisitor`
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type VisitFn<'f, G> = &'f mut dyn FnMut(
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// the path as a list of conditions
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&[Interned<<G as RankingRuleGraphTrait>::Condition>],
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&mut RankingRuleGraph<G>,
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// a mutable reference to the DeadEndsCache, to update it in case the given
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// path doesn't resolve to any valid document ids
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&mut DeadEndsCache<<G as RankingRuleGraphTrait>::Condition>,
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) -> Result<ControlFlow<()>>;
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/// A structure which is kept but not updated during the traversal of the graph.
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/// It can however be updated by the `visit` closure once a valid path has been found.
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struct VisitorContext<'a, G: RankingRuleGraphTrait> {
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graph: &'a mut RankingRuleGraph<G>,
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all_costs_from_node: &'a MappedInterner<QueryNode, Vec<u64>>,
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dead_ends_cache: &'a mut DeadEndsCache<G::Condition>,
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}
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/// The internal state of the traversal algorithm
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struct VisitorState<G: RankingRuleGraphTrait> {
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/// Budget from the current node to the end node
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remaining_cost: u64,
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/// Previously visited conditions, in order.
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path: Vec<Interned<G::Condition>>,
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/// Previously visited conditions, as an efficient and compact set.
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visited_conditions: SmallBitmap<G::Condition>,
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/// Previously visited (ie not skipped) nodes, as an efficient and compact set.
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visited_nodes: SmallBitmap<QueryNode>,
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/// The conditions that cannot be visited anymore
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forbidden_conditions: SmallBitmap<G::Condition>,
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forbidden_conditions_to_nodes: SmallBitmap<QueryNode>,
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/// The nodes that cannot be visited anymore (they must be skipped)
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nodes_to_skip: SmallBitmap<QueryNode>,
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}
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/// See module documentation
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pub struct PathVisitor<'a, G: RankingRuleGraphTrait> {
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state: VisitorState<G>,
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ctx: VisitorContext<'a, G>,
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@ -56,14 +110,13 @@ impl<'a, G: RankingRuleGraphTrait> PathVisitor<'a, G> {
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forbidden_conditions: SmallBitmap::for_interned_values_in(
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&graph.conditions_interner,
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),
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forbidden_conditions_to_nodes: SmallBitmap::for_interned_values_in(
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&graph.query_graph.nodes,
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),
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nodes_to_skip: SmallBitmap::for_interned_values_in(&graph.query_graph.nodes),
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},
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ctx: VisitorContext { graph, all_costs_from_node, dead_ends_cache },
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}
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}
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/// See module documentation
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pub fn visit_paths(mut self, visit: VisitFn<G>) -> Result<()> {
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let _ =
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self.state.visit_node(self.ctx.graph.query_graph.root_node, visit, &mut self.ctx)?;
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@ -72,22 +125,31 @@ impl<'a, G: RankingRuleGraphTrait> PathVisitor<'a, G> {
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}
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impl<G: RankingRuleGraphTrait> VisitorState<G> {
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/// Visits a node: traverse all its valid conditional and unconditional edges.
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///
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/// Returns ControlFlow::Break if the path finding algorithm should stop.
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/// Returns whether a valid path was found from this node otherwise.
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fn visit_node(
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&mut self,
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from_node: Interned<QueryNode>,
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visit: VisitFn<G>,
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ctx: &mut VisitorContext<G>,
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) -> Result<ControlFlow<(), bool>> {
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// any valid path will be found from this point
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// if a valid path was found, then we know that the DeadEndsCache may have been updated,
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// and we will need to do more work to potentially backtrack
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let mut any_valid = false;
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let edges = ctx.graph.edges_of_node.get(from_node).clone();
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for edge_idx in edges.iter() {
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// could be none if the edge was deleted
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let Some(edge) = ctx.graph.edges_store.get(edge_idx).clone() else { continue };
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if self.remaining_cost < edge.cost as u64 {
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continue;
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}
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self.remaining_cost -= edge.cost as u64;
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let cf = match edge.condition {
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Some(condition) => self.visit_condition(
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condition,
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@ -119,6 +181,10 @@ impl<G: RankingRuleGraphTrait> VisitorState<G> {
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Ok(ControlFlow::Continue(any_valid))
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}
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/// Visits an unconditional edge.
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///
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/// Returns ControlFlow::Break if the path finding algorithm should stop.
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/// Returns whether a valid path was found from this node otherwise.
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fn visit_no_condition(
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&mut self,
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dest_node: Interned<QueryNode>,
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@ -134,20 +200,29 @@ impl<G: RankingRuleGraphTrait> VisitorState<G> {
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{
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return Ok(ControlFlow::Continue(false));
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}
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// We've reached the END node!
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if dest_node == ctx.graph.query_graph.end_node {
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let control_flow = visit(&self.path, ctx.graph, ctx.dead_ends_cache)?;
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// We could change the return type of the visit closure such that the caller
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// tells us whether the dead ends cache was updated or not.
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// Alternatively, maybe the DeadEndsCache should have a generation number
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// to it, so that we don't need to play with these booleans at all.
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match control_flow {
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ControlFlow::Continue(_) => Ok(ControlFlow::Continue(true)),
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ControlFlow::Break(_) => Ok(ControlFlow::Break(())),
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}
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} else {
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let old_fbct = self.forbidden_conditions_to_nodes.clone();
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self.forbidden_conditions_to_nodes.union(edge_new_nodes_to_skip);
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let old_fbct = self.nodes_to_skip.clone();
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self.nodes_to_skip.union(edge_new_nodes_to_skip);
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let cf = self.visit_node(dest_node, visit, ctx)?;
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self.forbidden_conditions_to_nodes = old_fbct;
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self.nodes_to_skip = old_fbct;
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Ok(cf)
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}
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}
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/// Visits a conditional edge.
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///
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/// Returns ControlFlow::Break if the path finding algorithm should stop.
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/// Returns whether a valid path was found from this node otherwise.
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fn visit_condition(
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&mut self,
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condition: Interned<G::Condition>,
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@ -159,7 +234,7 @@ impl<G: RankingRuleGraphTrait> VisitorState<G> {
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assert!(dest_node != ctx.graph.query_graph.end_node);
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if self.forbidden_conditions.contains(condition)
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|| self.forbidden_conditions_to_nodes.contains(dest_node)
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|| self.nodes_to_skip.contains(dest_node)
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|| edge_new_nodes_to_skip.intersects(&self.visited_nodes)
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{
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return Ok(ControlFlow::Continue(false));
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@ -180,19 +255,19 @@ impl<G: RankingRuleGraphTrait> VisitorState<G> {
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self.visited_nodes.insert(dest_node);
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self.visited_conditions.insert(condition);
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let old_fc = self.forbidden_conditions.clone();
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let old_forb_cond = self.forbidden_conditions.clone();
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if let Some(next_forbidden) =
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ctx.dead_ends_cache.forbidden_conditions_after_prefix(self.path.iter().copied())
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{
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self.forbidden_conditions.union(&next_forbidden);
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}
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let old_fctn = self.forbidden_conditions_to_nodes.clone();
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self.forbidden_conditions_to_nodes.union(edge_new_nodes_to_skip);
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let old_nodes_to_skip = self.nodes_to_skip.clone();
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self.nodes_to_skip.union(edge_new_nodes_to_skip);
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let cf = self.visit_node(dest_node, visit, ctx)?;
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self.forbidden_conditions_to_nodes = old_fctn;
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self.forbidden_conditions = old_fc;
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self.nodes_to_skip = old_nodes_to_skip;
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self.forbidden_conditions = old_forb_cond;
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self.visited_conditions.remove(condition);
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self.visited_nodes.remove(dest_node);
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@ -9,12 +9,8 @@ use crate::search::new::query_term::LocatedQueryTermSubset;
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use crate::search::new::SearchContext;
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use crate::Result;
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// TODO: give a generation to each universe, then be able to get the exact
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// delta of docids between two universes of different generations!
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/// A cache storing the document ids associated with each ranking rule edge
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pub struct ConditionDocIdsCache<G: RankingRuleGraphTrait> {
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// TOOD: should be a mapped interner?
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pub cache: FxHashMap<Interned<G::Condition>, ComputedCondition>,
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_phantom: PhantomData<G>,
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}
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@ -54,7 +50,7 @@ impl<G: RankingRuleGraphTrait> ConditionDocIdsCache<G> {
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}
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let condition = graph.conditions_interner.get_mut(interned_condition);
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let computed = G::resolve_condition(ctx, condition, universe)?;
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// TODO: if computed.universe_len != universe.len() ?
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// Can we put an assert here for computed.universe_len == universe.len() ?
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let _ = self.cache.insert(interned_condition, computed);
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let computed = &self.cache[&interned_condition];
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Ok(computed)
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|
@ -2,6 +2,7 @@ use crate::search::new::interner::{FixedSizeInterner, Interned};
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use crate::search::new::small_bitmap::SmallBitmap;
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pub struct DeadEndsCache<T> {
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// conditions and next could/should be part of the same vector
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conditions: Vec<Interned<T>>,
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next: Vec<Self>,
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pub forbidden: SmallBitmap<T>,
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@ -27,7 +28,7 @@ impl<T> DeadEndsCache<T> {
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self.forbidden.insert(condition);
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}
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pub fn advance(&mut self, condition: Interned<T>) -> Option<&mut Self> {
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fn advance(&mut self, condition: Interned<T>) -> Option<&mut Self> {
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if let Some(idx) = self.conditions.iter().position(|c| *c == condition) {
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Some(&mut self.next[idx])
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} else {
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|
@ -69,14 +69,9 @@ impl RankingRuleGraphTrait for FidGraph {
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let mut edges = vec![];
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for fid in all_fields {
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// TODO: We can improve performances and relevancy by storing
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// the term subsets associated to each field ids fetched.
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edges.push((
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fid as u32 * term.term_ids.len() as u32, // TODO improve the fid score i.e. fid^10.
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conditions_interner.insert(FidCondition {
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term: term.clone(), // TODO remove this ugly clone
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fid,
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}),
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fid as u32 * term.term_ids.len() as u32,
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conditions_interner.insert(FidCondition { term: term.clone(), fid }),
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));
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}
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|
@ -94,14 +94,9 @@ impl RankingRuleGraphTrait for PositionGraph {
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let mut edges = vec![];
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for (cost, positions) in positions_for_costs {
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// TODO: We can improve performances and relevancy by storing
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// the term subsets associated to each position fetched
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edges.push((
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cost,
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conditions_interner.insert(PositionCondition {
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term: term.clone(), // TODO remove this ugly clone
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positions,
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}),
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conditions_interner.insert(PositionCondition { term: term.clone(), positions }),
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));
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}
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|
@ -65,13 +65,6 @@ pub fn compute_docids(
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}
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}
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// TODO: add safeguard in case the cartesian product is too large!
|
||||
// even if we restrict the word derivations to a maximum of 100, the size of the
|
||||
// caterisan product could reach a maximum of 10_000 derivations, which is way too much.
|
||||
// Maybe prioritise the product of zero typo derivations, then the product of zero-typo/one-typo
|
||||
// + one-typo/zero-typo, then one-typo/one-typo, then ... until an arbitrary limit has been
|
||||
// reached
|
||||
|
||||
for (left_phrase, left_word) in last_words_of_term_derivations(ctx, &left_term.term_subset)? {
|
||||
// Before computing the edges, check that the left word and left phrase
|
||||
// aren't disjoint with the universe, but only do it if there is more than
|
||||
@ -111,8 +104,6 @@ pub fn compute_docids(
|
||||
Ok(ComputedCondition {
|
||||
docids,
|
||||
universe_len: universe.len(),
|
||||
// TODO: think about whether we want to reduce the subset,
|
||||
// we probably should!
|
||||
start_term_subset: Some(left_term.clone()),
|
||||
end_term_subset: right_term.clone(),
|
||||
})
|
||||
@ -203,12 +194,7 @@ fn compute_non_prefix_edges(
|
||||
*docids |= new_docids;
|
||||
}
|
||||
}
|
||||
if backward_proximity >= 1
|
||||
// TODO: for now, we don't do any swapping when either term is a phrase
|
||||
// but maybe we should. We'd need to look at the first/last word of the phrase
|
||||
// depending on the context.
|
||||
&& left_phrase.is_none() && right_phrase.is_none()
|
||||
{
|
||||
if backward_proximity >= 1 && left_phrase.is_none() && right_phrase.is_none() {
|
||||
if let Some(new_docids) =
|
||||
ctx.get_db_word_pair_proximity_docids(word2, word1, backward_proximity)?
|
||||
{
|
||||
|
@ -33,8 +33,6 @@ pub fn compute_query_term_subset_docids(
|
||||
ctx: &mut SearchContext,
|
||||
term: &QueryTermSubset,
|
||||
) -> Result<RoaringBitmap> {
|
||||
// TODO Use the roaring::MultiOps trait
|
||||
|
||||
let mut docids = RoaringBitmap::new();
|
||||
for word in term.all_single_words_except_prefix_db(ctx)? {
|
||||
if let Some(word_docids) = ctx.word_docids(word)? {
|
||||
@ -59,8 +57,6 @@ pub fn compute_query_term_subset_docids_within_field_id(
|
||||
term: &QueryTermSubset,
|
||||
fid: u16,
|
||||
) -> Result<RoaringBitmap> {
|
||||
// TODO Use the roaring::MultiOps trait
|
||||
|
||||
let mut docids = RoaringBitmap::new();
|
||||
for word in term.all_single_words_except_prefix_db(ctx)? {
|
||||
if let Some(word_fid_docids) = ctx.get_db_word_fid_docids(word.interned(), fid)? {
|
||||
@ -71,7 +67,6 @@ pub fn compute_query_term_subset_docids_within_field_id(
|
||||
for phrase in term.all_phrases(ctx)? {
|
||||
// There may be false positives when resolving a phrase, so we're not
|
||||
// guaranteed that all of its words are within a single fid.
|
||||
// TODO: fix this?
|
||||
if let Some(word) = phrase.words(ctx).iter().flatten().next() {
|
||||
if let Some(word_fid_docids) = ctx.get_db_word_fid_docids(*word, fid)? {
|
||||
docids |= ctx.get_phrase_docids(phrase)? & word_fid_docids;
|
||||
@ -95,7 +90,6 @@ pub fn compute_query_term_subset_docids_within_position(
|
||||
term: &QueryTermSubset,
|
||||
position: u16,
|
||||
) -> Result<RoaringBitmap> {
|
||||
// TODO Use the roaring::MultiOps trait
|
||||
let mut docids = RoaringBitmap::new();
|
||||
for word in term.all_single_words_except_prefix_db(ctx)? {
|
||||
if let Some(word_position_docids) =
|
||||
@ -108,7 +102,6 @@ pub fn compute_query_term_subset_docids_within_position(
|
||||
for phrase in term.all_phrases(ctx)? {
|
||||
// It's difficult to know the expected position of the words in the phrase,
|
||||
// so instead we just check the first one.
|
||||
// TODO: fix this?
|
||||
if let Some(word) = phrase.words(ctx).iter().flatten().next() {
|
||||
if let Some(word_position_docids) = ctx.get_db_word_position_docids(*word, position)? {
|
||||
docids |= ctx.get_phrase_docids(phrase)? & word_position_docids
|
||||
@ -132,9 +125,6 @@ pub fn compute_query_graph_docids(
|
||||
q: &QueryGraph,
|
||||
universe: &RoaringBitmap,
|
||||
) -> Result<RoaringBitmap> {
|
||||
// TODO: there must be a faster way to compute this big
|
||||
// roaring bitmap expression
|
||||
|
||||
let mut nodes_resolved = SmallBitmap::for_interned_values_in(&q.nodes);
|
||||
let mut path_nodes_docids = q.nodes.map(|_| RoaringBitmap::new());
|
||||
|
||||
|
@ -141,10 +141,6 @@ impl<'ctx, Query: RankingRuleQueryTrait> RankingRule<'ctx, Query> for Sort<'ctx,
|
||||
universe: &RoaringBitmap,
|
||||
) -> Result<Option<RankingRuleOutput<Query>>> {
|
||||
let iter = self.iter.as_mut().unwrap();
|
||||
// TODO: we should make use of the universe in the function below
|
||||
// good for correctness, but ideally iter.next_bucket would take the current universe into account,
|
||||
// as right now it could return buckets that don't intersect with the universe, meaning we will make many
|
||||
// unneeded calls.
|
||||
if let Some(mut bucket) = iter.next_bucket()? {
|
||||
bucket.candidates &= universe;
|
||||
Ok(Some(bucket))
|
||||
|
@ -527,7 +527,7 @@ fn test_distinct_all_candidates() {
|
||||
let SearchResult { documents_ids, candidates, .. } = s.execute().unwrap();
|
||||
let candidates = candidates.iter().collect::<Vec<_>>();
|
||||
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[14, 26, 4, 7, 17, 23, 1, 19, 25, 8, 20, 24]");
|
||||
// TODO: this is incorrect!
|
||||
// This is incorrect, but unfortunately impossible to do better efficiently.
|
||||
insta::assert_snapshot!(format!("{candidates:?}"), @"[1, 4, 7, 8, 14, 17, 19, 20, 23, 24, 25, 26]");
|
||||
}
|
||||
|
||||
|
@ -125,8 +125,8 @@ fn create_edge_cases_index() -> TempIndex {
|
||||
// The next 5 documents lay out a trap with the split word, phrase search, or synonym `sun flower`.
|
||||
// If the search query is "sunflower", the split word "Sun Flower" will match some documents.
|
||||
// If the query is `sunflower wilting`, then we should make sure that
|
||||
// the sprximity condition `flower wilting: sprx N` also comes with the condition
|
||||
// `sun wilting: sprx N+1`. TODO: this is not the exact condition we use for now.
|
||||
// the proximity condition `flower wilting: sprx N` also comes with the condition
|
||||
// `sun wilting: sprx N+1`, but this is not the exact condition we use for now.
|
||||
// We only check that the phrase `sun flower` exists and `flower wilting: sprx N`, which
|
||||
// is better than nothing but not the best.
|
||||
{
|
||||
@ -299,7 +299,7 @@ fn test_proximity_split_word() {
|
||||
let SearchResult { documents_ids, .. } = s.execute().unwrap();
|
||||
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[2, 4, 5, 1, 3]");
|
||||
let texts = collect_field_values(&index, &txn, "text", &documents_ids);
|
||||
// TODO: "2" and "4" should be swapped ideally
|
||||
// "2" and "4" should be swapped ideally
|
||||
insta::assert_debug_snapshot!(texts, @r###"
|
||||
[
|
||||
"\"Sun Flower sounds like the title of a painting, maybe about a flower wilting under the heat.\"",
|
||||
@ -316,7 +316,7 @@ fn test_proximity_split_word() {
|
||||
let SearchResult { documents_ids, .. } = s.execute().unwrap();
|
||||
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[2, 4, 1]");
|
||||
let texts = collect_field_values(&index, &txn, "text", &documents_ids);
|
||||
// TODO: "2" and "4" should be swapped ideally
|
||||
// "2" and "4" should be swapped ideally
|
||||
insta::assert_debug_snapshot!(texts, @r###"
|
||||
[
|
||||
"\"Sun Flower sounds like the title of a painting, maybe about a flower wilting under the heat.\"",
|
||||
@ -341,7 +341,7 @@ fn test_proximity_split_word() {
|
||||
let SearchResult { documents_ids, .. } = s.execute().unwrap();
|
||||
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[2, 4, 1]");
|
||||
let texts = collect_field_values(&index, &txn, "text", &documents_ids);
|
||||
// TODO: "2" and "4" should be swapped ideally
|
||||
// "2" and "4" should be swapped ideally
|
||||
insta::assert_debug_snapshot!(texts, @r###"
|
||||
[
|
||||
"\"Sun Flower sounds like the title of a painting, maybe about a flower wilting under the heat.\"",
|
||||
|
@ -2,9 +2,8 @@
|
||||
This module tests the interactions between the proximity and typo ranking rules.
|
||||
|
||||
The proximity ranking rule should transform the query graph such that it
|
||||
only contains the word pairs that it used to compute its bucket.
|
||||
|
||||
TODO: This is not currently implemented.
|
||||
only contains the word pairs that it used to compute its bucket, but this is not currently
|
||||
implemented.
|
||||
*/
|
||||
|
||||
use crate::index::tests::TempIndex;
|
||||
@ -64,7 +63,7 @@ fn test_trap_basic() {
|
||||
let SearchResult { documents_ids, .. } = s.execute().unwrap();
|
||||
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[0, 1]");
|
||||
let texts = collect_field_values(&index, &txn, "text", &documents_ids);
|
||||
// TODO: this is incorrect, 1 should come before 0
|
||||
// This is incorrect, 1 should come before 0
|
||||
insta::assert_debug_snapshot!(texts, @r###"
|
||||
[
|
||||
"\"summer. holiday. sommer holidty\"",
|
||||
|
@ -571,8 +571,8 @@ fn test_typo_synonyms() {
|
||||
s.terms_matching_strategy(TermsMatchingStrategy::All);
|
||||
s.query("the fast brownish fox jumps over the lackadaisical dog");
|
||||
|
||||
// TODO: is this correct? interaction of ngrams + synonyms means that the
|
||||
// multi-word synonyms end up having a typo cost. This is probably not what we want.
|
||||
// The interaction of ngrams + synonyms means that the multi-word synonyms end up having a typo cost.
|
||||
// This is probably not what we want.
|
||||
let SearchResult { documents_ids, .. } = s.execute().unwrap();
|
||||
insta::assert_snapshot!(format!("{documents_ids:?}"), @"[21, 0, 22]");
|
||||
let texts = collect_field_values(&index, &txn, "text", &documents_ids);
|
||||
|
Loading…
Reference in New Issue
Block a user