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Revert "Integrate the stop_words in the querytree"

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This reverts commit 12fb509d84.
We revert this commit because it's causing the bug #150.
The initial algorithm we implemented for the stop_words was:

1. remove the stop_words from the dataset
2. keep the stop_words in the query to see if we can generate new words by
   integrating typos or if the word was a prefix
=> This was causing the bug since, in the case of “The hobbit”, we were
   **always** looking for something starting with “t he” or “th e”
   instead of ignoring the word completely.

For now we are going to fix the bug by completely ignoring the
stop_words in the query.
This could cause another problem were someone mistyped a normal word and
ended up typing a stop_word.

For example imagine someone searching for the music “Won't he do it”.
If that person misplace one space and write “Won' the do it” then we
will loose a part of the request.

One fix would be to update our query tree to something like that:

---------------------
OR
  OR
    TOLERANT hobbit # the first option is to ignore the stop_word
    AND
      CONSECUTIVE   # the second option is to do as we are doing
        EXACT t	    # currently
        EXACT he
      TOLERANT hobbit
---------------------

This would increase drastically the size of our query tree on request
with a lot of stop_words. For example think of “The Lord Of The Rings”.

For now whatsoever we decided we were going to ignore this problem and consider
that it doesn't reduce too much the relevancy of the search to do that
while it improves the performances.
This commit is contained in:
tamo 2021-04-08 15:12:37 +02:00
parent f9eab6e0de
commit da036dcc3e
No known key found for this signature in database
GPG Key ID: 20CD8020AFA88D69
1 changed files with 18 additions and 42 deletions
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46
milli/src/search/query_tree.rs
View File

@ -1,7 +1,6 @@
use std::collections::HashSet;
use std::{fmt, cmp, mem};
use fst::Set;
use levenshtein_automata::{DFA, Distance};
use meilisearch_tokenizer::{TokenKind, tokenizer::TokenStream};
use roaring::RoaringBitmap;
@ -155,10 +154,6 @@ impl fmt::Debug for Query {
trait Context {
fn word_docids(&self, word: &str) -> heed::Result<Option<RoaringBitmap>>;
fn stop_words(&self) -> anyhow::Result<Option<Set<&[u8]>>>;
fn is_stop_word(&self, word: &str) -> anyhow::Result<bool> {
Ok(self.stop_words()?.map_or(false, |s| s.contains(word)))
}
fn synonyms<S: AsRef<str>>(&self, words: &[S]) -> heed::Result<Option<Vec<Vec<String>>>>;
fn word_documents_count(&self, word: &str) -> heed::Result<Option<u64>> {
match self.word_docids(word)? {
@ -188,10 +183,6 @@ impl<'a> Context for QueryTreeBuilder<'a> {
fn synonyms<S: AsRef<str>>(&self, _words: &[S]) -> heed::Result<Option<Vec<Vec<String>>>> {
Ok(None)
}
fn stop_words(&self) -> anyhow::Result<Option<Set<&[u8]>>> {
self.index.stop_words(self.rtxn)
}
}
impl<'a> QueryTreeBuilder<'a> {
@ -340,7 +331,8 @@ fn create_query_tree(
optional_words: bool,
authorize_typos: bool,
query: PrimitiveQuery,
) -> anyhow::Result<Operation> {
) -> anyhow::Result<Operation>
{
/// Matches on the `PrimitiveQueryPart` and create an operation from it.
fn resolve_primitive_part(
ctx: &impl Context,
@ -358,12 +350,7 @@ fn create_query_tree(
if let Some(child) = split_best_frequency(ctx, &word)? {
children.push(child);
}
let is_stop_word = ctx.is_stop_word(&word)?;
let query = Query { prefix, kind: typos(word, authorize_typos) };
if query.prefix || query.kind.is_tolerant() || !is_stop_word {
children.push(Operation::Query(query));
}
children.push(Operation::Query(Query { prefix, kind: typos(word, authorize_typos) }));
Ok(Operation::or(false, children))
},
// create a CONSECUTIVE operation wrapping all word in the phrase
@ -378,11 +365,12 @@ fn create_query_tree(
ctx: &impl Context,
authorize_typos: bool,
query: &[PrimitiveQueryPart],
) -> anyhow::Result<Operation> {
) -> anyhow::Result<Operation>
{
const MAX_NGRAM: usize = 3;
let mut op_children = Vec::new();
for sub_query in query.linear_group_by(|a, b| !(a.is_phrase() || b.is_phrase())) {
for sub_query in query.linear_group_by(|a, b| !(a.is_phrase() || b.is_phrase()) ) {
let mut or_op_children = Vec::new();
for ngram in 1..=MAX_NGRAM.min(sub_query.len()) {
@ -393,33 +381,25 @@ fn create_query_tree(
match group {
[part] => {
let operation =
resolve_primitive_part(ctx, authorize_typos, part.clone())?;
let operation = resolve_primitive_part(ctx, authorize_typos, part.clone())?;
and_op_children.push(operation);
}
},
words => {
let is_prefix = words.last().map_or(false, |part| part.is_prefix());
let words: Vec<_> = words
.iter()
.filter_map(|part| {
let is_prefix = words.last().map(|part| part.is_prefix()).unwrap_or(false);
let words: Vec<_> = words.iter().filter_map(| part| {
if let PrimitiveQueryPart::Word(word, _) = part {
Some(word.as_str())
} else {
None
}
})
.collect();
}).collect();
let mut operations = synonyms(ctx, &words)?.unwrap_or_default();
let concat = words.concat();
let is_stop_word = ctx.is_stop_word(&concat)?;
let query = Query { prefix: is_prefix, kind: typos(concat, authorize_typos) };
if query.prefix || query.kind.is_tolerant() || !is_stop_word {
operations.push(Operation::Query(query));
and_op_children.push(Operation::or(false, operations));
}
}
}
if !is_last {
let ngrams = ngrams(ctx, authorize_typos, tail)?;
@ -601,10 +581,6 @@ mod test {
let words: Vec<_> = words.iter().map(|s| s.as_ref().to_owned()).collect();
Ok(self.synonyms.get(&words).cloned())
}
fn stop_words(&self) -> anyhow::Result<Option<Set<&[u8]>>> {
Ok(None)
}
}
impl Default for TestContext {