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| </pre><pre class="rust"><code><span class="kw">use </span>std::ops::{Deref, DerefMut}; |
| |
| <span class="kw">use </span><span class="kw">crate</span>::query::term_query::TermScorer; |
| <span class="kw">use </span><span class="kw">crate</span>::query::Scorer; |
| <span class="kw">use crate</span>::{DocId, DocSet, Score, TERMINATED}; |
| |
| <span class="doccomment">/// Takes a term_scorers sorted by their current doc() and a threshold and returns |
| /// Returns (pivot_len, pivot_ord) defined as follows: |
| /// - `pivot_doc` lowest document that has a chance of exceeding (>) the threshold score. |
| /// - `before_pivot_len` number of term_scorers such that term_scorer.doc() < pivot. |
| /// - `pivot_len` number of term_scorers such that term_scorer.doc() <= pivot. |
| /// |
| /// We always have `before_pivot_len` < `pivot_len`. |
| /// |
| /// `None` is returned if we establish that no document can exceed the threshold. |
| </span><span class="kw">fn </span>find_pivot_doc( |
| term_scorers: <span class="kw-2">&</span>[TermScorerWithMaxScore], |
| threshold: Score, |
| ) -> <span class="prelude-ty">Option</span><(usize, usize, DocId)> { |
| <span class="kw">let </span><span class="kw-2">mut </span>max_score = <span class="number">0.0</span>; |
| <span class="kw">let </span><span class="kw-2">mut </span>before_pivot_len = <span class="number">0</span>; |
| <span class="kw">let </span><span class="kw-2">mut </span>pivot_doc = TERMINATED; |
| <span class="kw">while </span>before_pivot_len < term_scorers.len() { |
| <span class="kw">let </span>term_scorer = <span class="kw-2">&</span>term_scorers[before_pivot_len]; |
| max_score += term_scorer.max_score; |
| <span class="kw">if </span>max_score > threshold { |
| pivot_doc = term_scorer.doc(); |
| <span class="kw">break</span>; |
| } |
| before_pivot_len += <span class="number">1</span>; |
| } |
| <span class="kw">if </span>pivot_doc == TERMINATED { |
| <span class="kw">return </span><span class="prelude-val">None</span>; |
| } |
| <span class="comment">// Right now i is an ordinal, we want a len. |
| </span><span class="kw">let </span><span class="kw-2">mut </span>pivot_len = before_pivot_len + <span class="number">1</span>; |
| <span class="comment">// Some other term_scorer may be positioned on the same document. |
| </span>pivot_len += term_scorers[pivot_len..] |
| .iter() |
| .take_while(|term_scorer| term_scorer.doc() == pivot_doc) |
| .count(); |
| <span class="prelude-val">Some</span>((before_pivot_len, pivot_len, pivot_doc)) |
| } |
| |
| <span class="doccomment">/// Advance the scorer with best score among the scorers[..pivot_len] to |
| /// the next doc candidate defined by the min of `last_doc_in_block + 1` for |
| /// scorer in scorers[..pivot_len] and `scorer.doc()` for scorer in scorers[pivot_len..]. |
| /// Note: before and after calling this method, scorers need to be sorted by their `.doc()`. |
| </span><span class="kw">fn </span>block_max_was_too_low_advance_one_scorer( |
| scorers: <span class="kw-2">&mut </span>[TermScorerWithMaxScore], |
| pivot_len: usize, |
| ) { |
| <span class="macro">debug_assert!</span>(is_sorted(scorers.iter().map(|scorer| scorer.doc()))); |
| <span class="kw">let </span><span class="kw-2">mut </span>scorer_to_seek = pivot_len - <span class="number">1</span>; |
| <span class="kw">let </span><span class="kw-2">mut </span>global_max_score = scorers[scorer_to_seek].max_score; |
| <span class="kw">let </span><span class="kw-2">mut </span>doc_to_seek_after = scorers[scorer_to_seek].last_doc_in_block(); |
| <span class="kw">for </span>scorer_ord <span class="kw">in </span>(<span class="number">0</span>..pivot_len - <span class="number">1</span>).rev() { |
| <span class="kw">let </span>scorer = <span class="kw-2">&</span>scorers[scorer_ord]; |
| <span class="kw">if </span>scorer.last_doc_in_block() <= doc_to_seek_after { |
| doc_to_seek_after = scorer.last_doc_in_block(); |
| } |
| <span class="kw">if </span>scorers[scorer_ord].max_score > global_max_score { |
| global_max_score = scorers[scorer_ord].max_score; |
| scorer_to_seek = scorer_ord; |
| } |
| } |
| <span class="comment">// Add +1 to go to the next block unless we are already at the end. |
| </span><span class="kw">if </span>doc_to_seek_after != TERMINATED { |
| doc_to_seek_after += <span class="number">1</span>; |
| } |
| <span class="kw">for </span>scorer <span class="kw">in </span><span class="kw-2">&</span>scorers[pivot_len..] { |
| <span class="kw">if </span>scorer.doc() <= doc_to_seek_after { |
| doc_to_seek_after = scorer.doc(); |
| } |
| } |
| scorers[scorer_to_seek].seek(doc_to_seek_after); |
| |
| restore_ordering(scorers, scorer_to_seek); |
| <span class="macro">debug_assert!</span>(is_sorted(scorers.iter().map(|scorer| scorer.doc()))); |
| } |
| |
| <span class="comment">// Given a list of term_scorers and a `ord` and assuming that `term_scorers[ord]` is sorted |
| // except term_scorers[ord] that might be in advance compared to its ranks, |
| // bubble up term_scorers[ord] in order to restore the ordering. |
| </span><span class="kw">fn </span>restore_ordering(term_scorers: <span class="kw-2">&mut </span>[TermScorerWithMaxScore], ord: usize) { |
| <span class="kw">let </span>doc = term_scorers[ord].doc(); |
| <span class="kw">for </span>i <span class="kw">in </span>ord + <span class="number">1</span>..term_scorers.len() { |
| <span class="kw">if </span>term_scorers[i].doc() >= doc { |
| <span class="kw">break</span>; |
| } |
| term_scorers.swap(i, i - <span class="number">1</span>); |
| } |
| <span class="macro">debug_assert!</span>(is_sorted(term_scorers.iter().map(|scorer| scorer.doc()))); |
| } |
| |
| <span class="comment">// Attempts to advance all term_scorers between `&term_scorers[0..before_len]` to the pivot. |
| // If this works, return true. |
| // If this fails (ie: one of the term_scorer does not contain `pivot_doc` and seek goes past the |
| // pivot), reorder the term_scorers to ensure the list is still sorted and returns `false`. |
| // If a term_scorer reach TERMINATED in the process return false remove the term_scorer and return. |
| </span><span class="kw">fn </span>align_scorers( |
| term_scorers: <span class="kw-2">&mut </span>Vec<TermScorerWithMaxScore>, |
| pivot_doc: DocId, |
| before_pivot_len: usize, |
| ) -> bool { |
| <span class="macro">debug_assert_ne!</span>(pivot_doc, TERMINATED); |
| <span class="kw">for </span>i <span class="kw">in </span>(<span class="number">0</span>..before_pivot_len).rev() { |
| <span class="kw">let </span>new_doc = term_scorers[i].seek(pivot_doc); |
| <span class="kw">if </span>new_doc != pivot_doc { |
| <span class="kw">if </span>new_doc == TERMINATED { |
| term_scorers.swap_remove(i); |
| } |
| <span class="comment">// We went past the pivot. |
| // We just go through the outer loop mechanic (Note that pivot is |
| // still a possible candidate). |
| // |
| // Termination is still guaranteed since we can only consider the same |
| // pivot at most term_scorers.len() - 1 times. |
| </span>restore_ordering(term_scorers, i); |
| <span class="kw">return </span><span class="bool-val">false</span>; |
| } |
| } |
| <span class="bool-val">true |
| </span>} |
| |
| <span class="comment">// Assumes terms_scorers[..pivot_len] are positioned on the same doc (pivot_doc). |
| // Advance term_scorers[..pivot_len] and out of these removes the terminated scores. |
| // Restores the ordering of term_scorers. |
| </span><span class="kw">fn </span>advance_all_scorers_on_pivot(term_scorers: <span class="kw-2">&mut </span>Vec<TermScorerWithMaxScore>, pivot_len: usize) { |
| <span class="kw">for </span>term_scorer <span class="kw">in </span><span class="kw-2">&mut </span>term_scorers[..pivot_len] { |
| term_scorer.advance(); |
| } |
| <span class="comment">// TODO use drain_filter when available. |
| </span><span class="kw">let </span><span class="kw-2">mut </span>i = <span class="number">0</span>; |
| <span class="kw">while </span>i != term_scorers.len() { |
| <span class="kw">if </span>term_scorers[i].doc() == TERMINATED { |
| term_scorers.swap_remove(i); |
| } <span class="kw">else </span>{ |
| i += <span class="number">1</span>; |
| } |
| } |
| term_scorers.sort_by_key(|scorer| scorer.doc()); |
| } |
| |
| <span class="doccomment">/// Implements the WAND (Weak AND) algorithm for dynamic pruning |
| /// described in the paper "Faster Top-k Document Retrieval Using Block-Max Indexes". |
| /// Link: <http://engineering.nyu.edu/~suel/papers/bmw.pdf> |
| </span><span class="kw">pub fn </span>block_wand( |
| <span class="kw-2">mut </span>scorers: Vec<TermScorer>, |
| <span class="kw-2">mut </span>threshold: Score, |
| callback: <span class="kw-2">&mut </span><span class="kw">dyn </span>FnMut(u32, Score) -> Score, |
| ) { |
| <span class="kw">let </span><span class="kw-2">mut </span>scorers: Vec<TermScorerWithMaxScore> = scorers |
| .iter_mut() |
| .map(TermScorerWithMaxScore::from) |
| .collect(); |
| scorers.sort_by_key(|scorer| scorer.doc()); |
| <span class="comment">// At this point we need to ensure that the scorers are sorted! |
| </span><span class="macro">debug_assert!</span>(is_sorted(scorers.iter().map(|scorer| scorer.doc()))); |
| <span class="kw">while let </span><span class="prelude-val">Some</span>((before_pivot_len, pivot_len, pivot_doc)) = |
| find_pivot_doc(<span class="kw-2">&</span>scorers[..], threshold) |
| { |
| <span class="macro">debug_assert!</span>(is_sorted(scorers.iter().map(|scorer| scorer.doc()))); |
| <span class="macro">debug_assert_ne!</span>(pivot_doc, TERMINATED); |
| <span class="macro">debug_assert!</span>(before_pivot_len < pivot_len); |
| |
| <span class="kw">let </span>block_max_score_upperbound: Score = scorers[..pivot_len] |
| .iter_mut() |
| .map(|scorer| { |
| scorer.shallow_seek(pivot_doc); |
| scorer.block_max_score() |
| }) |
| .sum(); |
| |
| <span class="comment">// Beware after shallow advance, skip readers can be in advance compared to |
| // the segment posting lists. |
| // |
| // `block_segment_postings.load_block()` need to be called separately. |
| </span><span class="kw">if </span>block_max_score_upperbound <= threshold { |
| <span class="comment">// Block max condition was not reached |
| // We could get away by simply advancing the scorers to DocId + 1 but it would |
| // be inefficient. The optimization requires proper explanation and was |
| // isolated in a different function. |
| </span>block_max_was_too_low_advance_one_scorer(<span class="kw-2">&mut </span>scorers, pivot_len); |
| <span class="kw">continue</span>; |
| } |
| |
| <span class="comment">// Block max condition is observed. |
| // |
| // Let's try and advance all scorers before the pivot to the pivot. |
| </span><span class="kw">if </span>!align_scorers(<span class="kw-2">&mut </span>scorers, pivot_doc, before_pivot_len) { |
| <span class="comment">// At least of the scorer does not contain the pivot. |
| // |
| // Let's stop scoring this pivot and go through the pivot selection again. |
| // Note that the current pivot is not necessarily a bad candidate and it |
| // may be picked again. |
| </span><span class="kw">continue</span>; |
| } |
| |
| <span class="comment">// At this point, all scorers are positioned on the doc. |
| </span><span class="kw">let </span>score = scorers[..pivot_len] |
| .iter_mut() |
| .map(|scorer| scorer.score()) |
| .sum(); |
| |
| <span class="kw">if </span>score > threshold { |
| threshold = callback(pivot_doc, score); |
| } |
| <span class="comment">// let's advance all of the scorers that are currently positioned on the pivot. |
| </span>advance_all_scorers_on_pivot(<span class="kw-2">&mut </span>scorers, pivot_len); |
| } |
| } |
| |
| <span class="doccomment">/// Specialized version of [`block_wand`] for a single scorer. |
| /// In this case, the algorithm is simple, readable and faster (~ x3) |
| /// than the generic algorithm. |
| /// The algorithm behaves as follows: |
| /// - While we don't hit the end of the docset: |
| /// - While the block max score is under the `threshold`, go to the next block. |
| /// - On a block, advance until the end and execute `callback` when the doc score is greater or |
| /// equal to the `threshold`. |
| </span><span class="kw">pub fn </span>block_wand_single_scorer( |
| <span class="kw-2">mut </span>scorer: TermScorer, |
| <span class="kw-2">mut </span>threshold: Score, |
| callback: <span class="kw-2">&mut </span><span class="kw">dyn </span>FnMut(u32, Score) -> Score, |
| ) { |
| <span class="kw">let </span><span class="kw-2">mut </span>doc = scorer.doc(); |
| <span class="kw">loop </span>{ |
| <span class="comment">// We position the scorer on a block that can reach |
| // the threshold. |
| </span><span class="kw">while </span>scorer.block_max_score() < threshold { |
| <span class="kw">let </span>last_doc_in_block = scorer.last_doc_in_block(); |
| <span class="kw">if </span>last_doc_in_block == TERMINATED { |
| <span class="kw">return</span>; |
| } |
| doc = last_doc_in_block + <span class="number">1</span>; |
| scorer.shallow_seek(doc); |
| } |
| <span class="comment">// Seek will effectively load that block. |
| </span>doc = scorer.seek(doc); |
| <span class="kw">if </span>doc == TERMINATED { |
| <span class="kw">break</span>; |
| } |
| <span class="kw">loop </span>{ |
| <span class="kw">let </span>score = scorer.score(); |
| <span class="kw">if </span>score > threshold { |
| threshold = callback(doc, score); |
| } |
| <span class="macro">debug_assert!</span>(doc <= scorer.last_doc_in_block()); |
| <span class="kw">if </span>doc == scorer.last_doc_in_block() { |
| <span class="kw">break</span>; |
| } |
| doc = scorer.advance(); |
| <span class="kw">if </span>doc == TERMINATED { |
| <span class="kw">return</span>; |
| } |
| } |
| doc += <span class="number">1</span>; |
| scorer.shallow_seek(doc); |
| } |
| } |
| |
| <span class="kw">struct </span>TermScorerWithMaxScore<<span class="lifetime">'a</span>> { |
| scorer: <span class="kw-2">&</span><span class="lifetime">'a </span><span class="kw-2">mut </span>TermScorer, |
| max_score: Score, |
| } |
| |
| <span class="kw">impl</span><<span class="lifetime">'a</span>> From<<span class="kw-2">&</span><span class="lifetime">'a </span><span class="kw-2">mut </span>TermScorer> <span class="kw">for </span>TermScorerWithMaxScore<<span class="lifetime">'a</span>> { |
| <span class="kw">fn </span>from(scorer: <span class="kw-2">&</span><span class="lifetime">'a </span><span class="kw-2">mut </span>TermScorer) -> <span class="self">Self </span>{ |
| <span class="kw">let </span>max_score = scorer.max_score(); |
| TermScorerWithMaxScore { scorer, max_score } |
| } |
| } |
| |
| <span class="kw">impl</span><<span class="lifetime">'a</span>> Deref <span class="kw">for </span>TermScorerWithMaxScore<<span class="lifetime">'a</span>> { |
| <span class="kw">type </span>Target = TermScorer; |
| |
| <span class="kw">fn </span>deref(<span class="kw-2">&</span><span class="self">self</span>) -> <span class="kw-2">&</span><span class="self">Self</span>::Target { |
| <span class="self">self</span>.scorer |
| } |
| } |
| |
| <span class="kw">impl</span><<span class="lifetime">'a</span>> DerefMut <span class="kw">for </span>TermScorerWithMaxScore<<span class="lifetime">'a</span>> { |
| <span class="kw">fn </span>deref_mut(<span class="kw-2">&mut </span><span class="self">self</span>) -> <span class="kw-2">&mut </span><span class="self">Self</span>::Target { |
| <span class="self">self</span>.scorer |
| } |
| } |
| |
| <span class="kw">fn </span>is_sorted<I: Iterator<Item = DocId>>(<span class="kw-2">mut </span>it: I) -> bool { |
| <span class="kw">if let </span><span class="prelude-val">Some</span>(first) = it.next() { |
| <span class="kw">let </span><span class="kw-2">mut </span>prev = first; |
| <span class="kw">for </span>doc <span class="kw">in </span>it { |
| <span class="kw">if </span>doc < prev { |
| <span class="kw">return </span><span class="bool-val">false</span>; |
| } |
| prev = doc; |
| } |
| } |
| <span class="bool-val">true |
| </span>} |
| <span class="attribute">#[cfg(test)] |
| </span><span class="kw">mod </span>tests { |
| <span class="kw">use </span>std::cmp::Ordering; |
| <span class="kw">use </span>std::collections::BinaryHeap; |
| <span class="kw">use </span>std::iter; |
| |
| <span class="kw">use </span>proptest::prelude::<span class="kw-2">*</span>; |
| |
| <span class="kw">use </span><span class="kw">crate</span>::query::score_combiner::SumCombiner; |
| <span class="kw">use </span><span class="kw">crate</span>::query::term_query::TermScorer; |
| <span class="kw">use </span><span class="kw">crate</span>::query::{Bm25Weight, Scorer, Union}; |
| <span class="kw">use crate</span>::{DocId, DocSet, Score, TERMINATED}; |
| |
| <span class="kw">struct </span>Float(Score); |
| |
| <span class="kw">impl </span>Eq <span class="kw">for </span>Float {} |
| |
| <span class="kw">impl </span>PartialEq <span class="kw">for </span>Float { |
| <span class="kw">fn </span>eq(<span class="kw-2">&</span><span class="self">self</span>, other: <span class="kw-2">&</span><span class="self">Self</span>) -> bool { |
| <span class="self">self</span>.cmp(other) == Ordering::Equal |
| } |
| } |
| |
| <span class="kw">impl </span>PartialOrd <span class="kw">for </span>Float { |
| <span class="kw">fn </span>partial_cmp(<span class="kw-2">&</span><span class="self">self</span>, other: <span class="kw-2">&</span><span class="self">Self</span>) -> <span class="prelude-ty">Option</span><Ordering> { |
| <span class="prelude-val">Some</span>(<span class="self">self</span>.cmp(other)) |
| } |
| } |
| |
| <span class="kw">impl </span>Ord <span class="kw">for </span>Float { |
| <span class="kw">fn </span>cmp(<span class="kw-2">&</span><span class="self">self</span>, other: <span class="kw-2">&</span><span class="self">Self</span>) -> Ordering { |
| other.<span class="number">0</span>.partial_cmp(<span class="kw-2">&</span><span class="self">self</span>.<span class="number">0</span>).unwrap_or(Ordering::Equal) |
| } |
| } |
| |
| <span class="kw">fn </span>nearly_equals(left: Score, right: Score) -> bool { |
| (left - right).abs() < <span class="number">0.0001 </span>* (left + right).abs() |
| } |
| |
| <span class="kw">fn </span>compute_checkpoints_for_each_pruning( |
| <span class="kw-2">mut </span>term_scorers: Vec<TermScorer>, |
| n: usize, |
| ) -> Vec<(DocId, Score)> { |
| <span class="kw">let </span><span class="kw-2">mut </span>heap: BinaryHeap<Float> = BinaryHeap::with_capacity(n); |
| <span class="kw">let </span><span class="kw-2">mut </span>checkpoints: Vec<(DocId, Score)> = Vec::new(); |
| <span class="kw">let </span><span class="kw-2">mut </span>limit: Score = <span class="number">0.0</span>; |
| |
| <span class="kw">let </span>callback = <span class="kw-2">&mut </span>|doc, score| { |
| heap.push(Float(score)); |
| <span class="kw">if </span>heap.len() > n { |
| heap.pop().unwrap(); |
| } |
| <span class="kw">if </span>heap.len() == n { |
| limit = heap.peek().unwrap().<span class="number">0</span>; |
| } |
| <span class="kw">if </span>!nearly_equals(score, limit) { |
| checkpoints.push((doc, score)); |
| } |
| limit |
| }; |
| |
| <span class="kw">if </span>term_scorers.len() == <span class="number">1 </span>{ |
| <span class="kw">let </span>scorer = term_scorers.pop().unwrap(); |
| <span class="kw">super</span>::block_wand_single_scorer(scorer, Score::MIN, callback); |
| } <span class="kw">else </span>{ |
| <span class="kw">super</span>::block_wand(term_scorers, Score::MIN, callback); |
| } |
| checkpoints |
| } |
| |
| <span class="kw">fn </span>compute_checkpoints_manual(term_scorers: Vec<TermScorer>, n: usize) -> Vec<(DocId, Score)> { |
| <span class="kw">let </span><span class="kw-2">mut </span>heap: BinaryHeap<Float> = BinaryHeap::with_capacity(n); |
| <span class="kw">let </span><span class="kw-2">mut </span>checkpoints: Vec<(DocId, Score)> = Vec::new(); |
| <span class="kw">let </span><span class="kw-2">mut </span>scorer = Union::build(term_scorers, SumCombiner::default); |
| |
| <span class="kw">let </span><span class="kw-2">mut </span>limit = Score::MIN; |
| <span class="kw">loop </span>{ |
| <span class="kw">if </span>scorer.doc() == TERMINATED { |
| <span class="kw">break</span>; |
| } |
| <span class="kw">let </span>doc = scorer.doc(); |
| <span class="kw">let </span>score = scorer.score(); |
| <span class="kw">if </span>score > limit { |
| heap.push(Float(score)); |
| <span class="kw">if </span>heap.len() > n { |
| heap.pop().unwrap(); |
| } |
| <span class="kw">if </span>heap.len() == n { |
| limit = heap.peek().unwrap().<span class="number">0</span>; |
| } |
| <span class="kw">if </span>!nearly_equals(score, limit) { |
| checkpoints.push((doc, score)); |
| } |
| } |
| scorer.advance(); |
| } |
| checkpoints |
| } |
| |
| <span class="kw">const </span>MAX_TERM_FREQ: u32 = <span class="number">100u32</span>; |
| |
| <span class="kw">fn </span>posting_list(max_doc: u32) -> BoxedStrategy<Vec<(DocId, u32)>> { |
| (<span class="number">1</span>..max_doc + <span class="number">1</span>) |
| .prop_flat_map(<span class="kw">move </span>|doc_freq| { |
| ( |
| proptest::bits::bitset::sampled(doc_freq <span class="kw">as </span>usize, <span class="number">0</span>..max_doc <span class="kw">as </span>usize), |
| proptest::collection::vec(<span class="number">1u32</span>..MAX_TERM_FREQ, doc_freq <span class="kw">as </span>usize), |
| ) |
| }) |
| .prop_map(|(docset, term_freqs)| { |
| docset |
| .iter() |
| .map(|doc| doc <span class="kw">as </span>u32) |
| .zip(term_freqs.iter().cloned()) |
| .collect::<Vec<<span class="kw">_</span>>>() |
| }) |
| .boxed() |
| } |
| |
| <span class="attribute">#[allow(clippy::type_complexity)] |
| </span><span class="kw">fn </span>gen_term_scorers(num_scorers: usize) -> BoxedStrategy<(Vec<Vec<(DocId, u32)>>, Vec<u32>)> { |
| (<span class="number">1u32</span>..<span class="number">100u32</span>) |
| .prop_flat_map(<span class="kw">move </span>|max_doc: u32| { |
| ( |
| proptest::collection::vec(posting_list(max_doc), num_scorers), |
| proptest::collection::vec(<span class="number">2u32</span>..<span class="number">10u32 </span>* MAX_TERM_FREQ, max_doc <span class="kw">as </span>usize), |
| ) |
| }) |
| .boxed() |
| } |
| |
| <span class="kw">fn </span>test_block_wand_aux(posting_lists: <span class="kw-2">&</span>[Vec<(DocId, u32)>], fieldnorms: <span class="kw-2">&</span>[u32]) { |
| <span class="comment">// We virtually repeat all docs 64 times in order to emulate blocks of 2 documents |
| // and surface blogs more easily. |
| </span><span class="kw">const </span>REPEAT: usize = <span class="number">64</span>; |
| <span class="kw">let </span>fieldnorms_expanded = fieldnorms |
| .iter() |
| .cloned() |
| .flat_map(|fieldnorm| iter::repeat(fieldnorm).take(REPEAT)) |
| .collect::<Vec<u32>>(); |
| |
| <span class="kw">let </span>postings_lists_expanded: Vec<Vec<(DocId, u32)>> = posting_lists |
| .iter() |
| .map(|posting_list| { |
| posting_list |
| .iter() |
| .cloned() |
| .flat_map(|(doc, term_freq)| { |
| (<span class="number">0_u32</span>..REPEAT <span class="kw">as </span>u32).map(<span class="kw">move </span>|offset| { |
| ( |
| doc * (REPEAT <span class="kw">as </span>u32) + offset, |
| <span class="kw">if </span>offset == <span class="number">0 </span>{ term_freq } <span class="kw">else </span>{ <span class="number">1 </span>}, |
| ) |
| }) |
| }) |
| .collect::<Vec<(DocId, u32)>>() |
| }) |
| .collect::<Vec<<span class="kw">_</span>>>(); |
| |
| <span class="kw">let </span>total_fieldnorms: u64 = fieldnorms_expanded |
| .iter() |
| .cloned() |
| .map(|fieldnorm| fieldnorm <span class="kw">as </span>u64) |
| .sum(); |
| <span class="kw">let </span>average_fieldnorm = (total_fieldnorms <span class="kw">as </span>Score) / (fieldnorms_expanded.len() <span class="kw">as </span>Score); |
| <span class="kw">let </span>max_doc = fieldnorms_expanded.len(); |
| |
| <span class="kw">let </span>term_scorers: Vec<TermScorer> = postings_lists_expanded |
| .iter() |
| .map(|postings| { |
| <span class="kw">let </span>bm25_weight = Bm25Weight::for_one_term( |
| postings.len() <span class="kw">as </span>u64, |
| max_doc <span class="kw">as </span>u64, |
| average_fieldnorm, |
| ); |
| TermScorer::create_for_test(postings, <span class="kw-2">&</span>fieldnorms_expanded[..], bm25_weight) |
| }) |
| .collect(); |
| <span class="kw">for </span>top_k <span class="kw">in </span><span class="number">1</span>..<span class="number">4 </span>{ |
| <span class="kw">let </span>checkpoints_for_each_pruning = |
| compute_checkpoints_for_each_pruning(term_scorers.clone(), top_k); |
| <span class="kw">let </span>checkpoints_manual = compute_checkpoints_manual(term_scorers.clone(), top_k); |
| <span class="macro">assert_eq!</span>(checkpoints_for_each_pruning.len(), checkpoints_manual.len()); |
| <span class="kw">for </span>(<span class="kw-2">&</span>(left_doc, left_score), <span class="kw-2">&</span>(right_doc, right_score)) <span class="kw">in </span>checkpoints_for_each_pruning |
| .iter() |
| .zip(checkpoints_manual.iter()) |
| { |
| <span class="macro">assert_eq!</span>(left_doc, right_doc); |
| <span class="macro">assert!</span>(nearly_equals(left_score, right_score)); |
| } |
| } |
| } |
| |
| <span class="macro">proptest! </span>{ |
| <span class="attribute">#![proptest_config(ProptestConfig::with_cases(<span class="number">500</span>))] |
| #[test] |
| </span><span class="kw">fn </span>test_block_wand_two_term_scorers((posting_lists, fieldnorms) <span class="kw">in </span>gen_term_scorers(<span class="number">2</span>)) { |
| test_block_wand_aux(<span class="kw-2">&</span>posting_lists[..], <span class="kw-2">&</span>fieldnorms[..]); |
| } |
| } |
| |
| <span class="macro">proptest! </span>{ |
| <span class="attribute">#![proptest_config(ProptestConfig::with_cases(<span class="number">500</span>))] |
| #[test] |
| </span><span class="kw">fn </span>test_block_wand_single_term_scorer((posting_lists, fieldnorms) <span class="kw">in </span>gen_term_scorers(<span class="number">1</span>)) { |
| test_block_wand_aux(<span class="kw-2">&</span>posting_lists[..], <span class="kw-2">&</span>fieldnorms[..]); |
| } |
| } |
| |
| <span class="attribute">#[test] |
| </span><span class="kw">fn </span>test_fn_reproduce_proptest() { |
| <span class="kw">let </span>postings_lists = <span class="kw-2">&</span>[ |
| <span class="macro">vec!</span>[ |
| (<span class="number">0</span>, <span class="number">1</span>), |
| (<span class="number">1</span>, <span class="number">1</span>), |
| (<span class="number">2</span>, <span class="number">1</span>), |
| (<span class="number">3</span>, <span class="number">1</span>), |
| (<span class="number">4</span>, <span class="number">1</span>), |
| (<span class="number">6</span>, <span class="number">1</span>), |
| (<span class="number">7</span>, <span class="number">7</span>), |
| (<span class="number">8</span>, <span class="number">1</span>), |
| (<span class="number">10</span>, <span class="number">1</span>), |
| (<span class="number">12</span>, <span class="number">1</span>), |
| (<span class="number">13</span>, <span class="number">1</span>), |
| (<span class="number">14</span>, <span class="number">1</span>), |
| (<span class="number">15</span>, <span class="number">1</span>), |
| (<span class="number">16</span>, <span class="number">1</span>), |
| (<span class="number">19</span>, <span class="number">1</span>), |
| (<span class="number">20</span>, <span class="number">1</span>), |
| (<span class="number">21</span>, <span class="number">1</span>), |
| (<span class="number">22</span>, <span class="number">1</span>), |
| (<span class="number">24</span>, <span class="number">1</span>), |
| (<span class="number">25</span>, <span class="number">1</span>), |
| (<span class="number">26</span>, <span class="number">1</span>), |
| (<span class="number">28</span>, <span class="number">1</span>), |
| (<span class="number">30</span>, <span class="number">1</span>), |
| (<span class="number">31</span>, <span class="number">1</span>), |
| (<span class="number">33</span>, <span class="number">1</span>), |
| (<span class="number">34</span>, <span class="number">1</span>), |
| (<span class="number">35</span>, <span class="number">1</span>), |
| (<span class="number">36</span>, <span class="number">95</span>), |
| (<span class="number">37</span>, <span class="number">1</span>), |
| (<span class="number">39</span>, <span class="number">1</span>), |
| (<span class="number">41</span>, <span class="number">1</span>), |
| (<span class="number">44</span>, <span class="number">1</span>), |
| (<span class="number">46</span>, <span class="number">1</span>), |
| ], |
| <span class="macro">vec!</span>[ |
| (<span class="number">0</span>, <span class="number">5</span>), |
| (<span class="number">2</span>, <span class="number">1</span>), |
| (<span class="number">4</span>, <span class="number">1</span>), |
| (<span class="number">5</span>, <span class="number">84</span>), |
| (<span class="number">6</span>, <span class="number">47</span>), |
| (<span class="number">7</span>, <span class="number">26</span>), |
| (<span class="number">8</span>, <span class="number">50</span>), |
| (<span class="number">9</span>, <span class="number">34</span>), |
| (<span class="number">11</span>, <span class="number">73</span>), |
| (<span class="number">12</span>, <span class="number">11</span>), |
| (<span class="number">13</span>, <span class="number">51</span>), |
| (<span class="number">14</span>, <span class="number">45</span>), |
| (<span class="number">15</span>, <span class="number">18</span>), |
| (<span class="number">18</span>, <span class="number">60</span>), |
| (<span class="number">19</span>, <span class="number">80</span>), |
| (<span class="number">20</span>, <span class="number">63</span>), |
| (<span class="number">23</span>, <span class="number">79</span>), |
| (<span class="number">24</span>, <span class="number">69</span>), |
| (<span class="number">26</span>, <span class="number">35</span>), |
| (<span class="number">28</span>, <span class="number">82</span>), |
| (<span class="number">29</span>, <span class="number">19</span>), |
| (<span class="number">30</span>, <span class="number">2</span>), |
| (<span class="number">31</span>, <span class="number">7</span>), |
| (<span class="number">33</span>, <span class="number">40</span>), |
| (<span class="number">34</span>, <span class="number">1</span>), |
| (<span class="number">35</span>, <span class="number">33</span>), |
| (<span class="number">36</span>, <span class="number">27</span>), |
| (<span class="number">37</span>, <span class="number">24</span>), |
| (<span class="number">38</span>, <span class="number">65</span>), |
| (<span class="number">39</span>, <span class="number">32</span>), |
| (<span class="number">40</span>, <span class="number">85</span>), |
| (<span class="number">41</span>, <span class="number">1</span>), |
| (<span class="number">42</span>, <span class="number">69</span>), |
| (<span class="number">43</span>, <span class="number">11</span>), |
| (<span class="number">45</span>, <span class="number">45</span>), |
| (<span class="number">47</span>, <span class="number">97</span>), |
| ], |
| <span class="macro">vec!</span>[ |
| (<span class="number">2</span>, <span class="number">1</span>), |
| (<span class="number">4</span>, <span class="number">1</span>), |
| (<span class="number">7</span>, <span class="number">94</span>), |
| (<span class="number">8</span>, <span class="number">1</span>), |
| (<span class="number">9</span>, <span class="number">1</span>), |
| (<span class="number">10</span>, <span class="number">1</span>), |
| (<span class="number">12</span>, <span class="number">1</span>), |
| (<span class="number">15</span>, <span class="number">1</span>), |
| (<span class="number">22</span>, <span class="number">1</span>), |
| (<span class="number">23</span>, <span class="number">1</span>), |
| (<span class="number">26</span>, <span class="number">1</span>), |
| (<span class="number">27</span>, <span class="number">1</span>), |
| (<span class="number">32</span>, <span class="number">1</span>), |
| (<span class="number">33</span>, <span class="number">1</span>), |
| (<span class="number">34</span>, <span class="number">1</span>), |
| (<span class="number">36</span>, <span class="number">96</span>), |
| (<span class="number">39</span>, <span class="number">1</span>), |
| (<span class="number">41</span>, <span class="number">1</span>), |
| ], |
| ]; |
| <span class="kw">let </span>fieldnorms = <span class="kw-2">&</span>[ |
| <span class="number">685</span>, <span class="number">239</span>, <span class="number">780</span>, <span class="number">564</span>, <span class="number">664</span>, <span class="number">827</span>, <span class="number">5</span>, <span class="number">56</span>, <span class="number">930</span>, <span class="number">887</span>, <span class="number">263</span>, <span class="number">665</span>, <span class="number">167</span>, <span class="number">127</span>, <span class="number">120</span>, <span class="number">919</span>, <span class="number">292</span>, <span class="number">92</span>, |
| <span class="number">489</span>, <span class="number">734</span>, <span class="number">814</span>, <span class="number">724</span>, <span class="number">700</span>, <span class="number">304</span>, <span class="number">128</span>, <span class="number">779</span>, <span class="number">311</span>, <span class="number">877</span>, <span class="number">774</span>, <span class="number">15</span>, <span class="number">866</span>, <span class="number">368</span>, <span class="number">894</span>, <span class="number">371</span>, <span class="number">982</span>, |
| <span class="number">502</span>, <span class="number">507</span>, <span class="number">669</span>, <span class="number">680</span>, <span class="number">76</span>, <span class="number">594</span>, <span class="number">626</span>, <span class="number">578</span>, <span class="number">331</span>, <span class="number">170</span>, <span class="number">639</span>, <span class="number">665</span>, <span class="number">186</span>, |
| ][..]; |
| test_block_wand_aux(postings_lists, fieldnorms); |
| } |
| |
| <span class="macro">proptest! </span>{ |
| <span class="attribute">#![proptest_config(ProptestConfig::with_cases(<span class="number">500</span>))] |
| #[ignore] |
| #[test] |
| #[ignore] |
| </span><span class="kw">fn </span>test_block_wand_three_term_scorers((posting_lists, fieldnorms) <span class="kw">in </span>gen_term_scorers(<span class="number">3</span>)) { |
| test_block_wand_aux(<span class="kw-2">&</span>posting_lists[..], <span class="kw-2">&</span>fieldnorms[..]); |
| } |
| } |
| } |
| </code></pre></div> |
| </section></div></main><div id="rustdoc-vars" data-root-path="../../../../" data-current-crate="tantivy" data-themes="ayu,dark,light" data-resource-suffix="" data-rustdoc-version="1.66.0-nightly (5c8bff74b 2022-10-21)" ></div></body></html> |
