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Refine some details in word_prefix_pair_proximity indexing code

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Loïc Lecrenier 2022-09-19 16:22:07 +02:00 committed by Loïc Lecrenier
parent e6e76fbefe
commit ab2f6f3aa4
2 changed files with 17 additions and 19 deletions
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33
milli/src/update/prefix_word_pairs/prefix_word.rs
View File

@ -35,9 +35,6 @@ pub fn index_prefix_word_database(
.filter(|s| s.len() <= max_prefix_length)
.collect();
// If the prefix trie is not empty, then we can iterate over all new
// word pairs to look for new (word1, common_prefix, proximity) elements
// to insert in the DB
for proximity in 1..=max_proximity - 1 {
for prefix in common_prefixes.iter() {
let mut prefix_key = vec![];
@ -135,13 +132,11 @@ pub fn index_prefix_word_database(
Ok(())
}
/// This is the core of the algorithm to initialise the Word Prefix Pair Proximity Docids database.
/// This is the core of the algorithm to initialise the Prefix Word Pair Proximity Docids database.
///
/// Its main arguments are:
/// 1. a sorted prefix iterator over ((word1, word2, proximity), docids) elements
/// 2. a closure to describe how to handle the new computed (word1, prefix, proximity) elements
///
/// For more information about what this function does, read the module documentation.
/// Its arguments are:
/// - an iterator over the words following the given `prefix` with the given `proximity`
/// - a closure to describe how to handle the new computed (proximity, prefix, word2) elements
fn execute_on_word_pairs_and_prefixes<I>(
proximity: u8,
prefix: &[u8],
@ -151,28 +146,32 @@ fn execute_on_word_pairs_and_prefixes<I>(
) -> Result<()> {
let mut batch: BTreeMap<Vec<u8>, Vec<Cow<'static, [u8]>>> = <_>::default();
while let Some((word2, data)) = next_word2_and_docids(iter)? {
// Memory usage check:
// The content of the loop will be called for each `word2` that follows a word beginning
// with `prefix` with the given proximity.
// In practice, I don't think the batch can ever get too big.
while let Some((word2, docids)) = next_word2_and_docids(iter)? {
let entry = batch.entry(word2.to_owned()).or_default();
entry.push(Cow::Owned(data.to_owned()));
entry.push(Cow::Owned(docids.to_owned()));
}
let mut key_buffer = Vec::with_capacity(8);
let mut key_buffer = Vec::with_capacity(512);
key_buffer.push(proximity);
key_buffer.extend_from_slice(prefix);
key_buffer.push(0);
let mut value_buffer = Vec::with_capacity(65_536);
for (key, values) in batch {
for (word2, docids) in batch {
key_buffer.truncate(prefix.len() + 2);
value_buffer.clear();
key_buffer.extend_from_slice(&key);
let data = if values.len() > 1 {
CboRoaringBitmapCodec::merge_into(&values, &mut value_buffer)?;
key_buffer.extend_from_slice(&word2);
let data = if docids.len() > 1 {
CboRoaringBitmapCodec::merge_into(&docids, &mut value_buffer)?;
value_buffer.as_slice()
} else {
&values[0]
&docids[0]
};
insert(key_buffer.as_slice(), data)?;
}

3
milli/src/update/prefix_word_pairs/word_prefix.rs
View File

@ -1,5 +1,4 @@
/*!
## What is WordPrefix?
The word-prefix-pair-proximity-docids database is a database whose keys are of
the form `(proximity, word, prefix)` and the values are roaring bitmaps of
the documents which contain `word` followed by another word starting with
@ -320,7 +319,7 @@ fn execute_on_word_pairs_and_prefixes<I>(
let mut merge_buffer = Vec::with_capacity(65_536);
while let Some(((proximity, word1, word2), data)) = next_word_pair_proximity(iter)? {
// skip this iteration if the proximity is over the threshold
// stop indexing if the proximity is over the threshold
if proximity > max_proximity {
break;
};