meilisearch/meilidb-core/src/lib.rs

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Rust
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mod automaton;
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mod error;
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mod number;
mod query_builder;
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mod ranked_map;
mod raw_document;
mod reordered_attrs;
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mod update;
pub mod criterion;
pub mod raw_indexer;
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pub mod serde;
pub mod store;
pub use self::query_builder::QueryBuilder;
pub use self::raw_document::RawDocument;
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pub use self::error::{Error, MResult};
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pub use self::number::{Number, ParseNumberError};
pub use self::ranked_map::RankedMap;
pub use self::store::Index;
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use std::collections::HashMap;
use std::io;
use std::path::Path;
use std::sync::{Arc, RwLock};
pub struct Database {
rkv: Arc<RwLock<rkv::Rkv>>,
main_store: rkv::SingleStore,
indexes: RwLock<HashMap<String, Index>>,
}
impl Database {
pub fn open_or_create(path: impl AsRef<Path>) -> io::Result<Database> {
let manager = rkv::Manager::singleton();
let mut rkv_write = manager.write().unwrap();
let rkv = rkv_write
.get_or_create(path.as_ref(), |path| {
let mut builder = rkv::Rkv::environment_builder();
builder.set_max_dbs(3000).set_map_size(10 * 1024 * 1024 * 1024); // 10GB
rkv::Rkv::from_env(path, builder)
})
.unwrap();
drop(rkv_write);
let mut indexes = HashMap::new();
let main_store;
{
let rkv_read = rkv.read().unwrap();
main_store = rkv_read
.open_single("indexes", rkv::store::Options::create())
.unwrap();
let mut must_open = Vec::new();
let reader = rkv_read.read().unwrap();
for result in main_store.iter_start(&reader).unwrap() {
let (key, _) = result.unwrap();
if let Ok(index_name) = std::str::from_utf8(key) {
println!("{:?}", index_name);
must_open.push(index_name.to_owned());
}
}
drop(reader);
for index_name in must_open {
let index = store::open(&rkv_read, &index_name).unwrap();
indexes.insert(index_name, index);
}
}
Ok(Database { rkv, main_store, indexes: RwLock::new(indexes) })
}
pub fn open_index(&self, name: impl Into<String>) -> MResult<Index> {
let read = self.indexes.read().unwrap();
let name = name.into();
match read.get(&name) {
Some(index) => Ok(*index),
None => {
drop(read);
let rkv = self.rkv.read().unwrap();
let mut write = self.indexes.write().unwrap();
let index = store::create(&rkv, &name).unwrap();
let mut writer = rkv.write().unwrap();
let value = rkv::Value::Blob(&[]);
self.main_store.put(&mut writer, &name, &value).unwrap();
writer.commit().unwrap();
Ok(*write.entry(name.clone()).or_insert(index))
},
}
}
}
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use zerocopy::{AsBytes, FromBytes};
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use ::serde::{Serialize, Deserialize};
/// Represent an internally generated document unique identifier.
///
/// It is used to inform the database the document you want to deserialize.
/// Helpful for custom ranking.
#[derive(Debug, Copy, Clone, Eq, PartialEq, PartialOrd, Ord, Hash)]
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#[derive(Serialize, Deserialize)]
#[derive(AsBytes, FromBytes)]
#[repr(C)]
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pub struct DocumentId(pub u64);
/// This structure represent the position of a word
/// in a document and its attributes.
///
/// This is stored in the map, generated at index time,
/// extracted and interpreted at search time.
#[derive(Debug, Copy, Clone, PartialEq, Eq, PartialOrd, Ord, Hash)]
#[derive(AsBytes, FromBytes)]
#[repr(C)]
pub struct DocIndex {
/// The document identifier where the word was found.
pub document_id: DocumentId,
/// The attribute in the document where the word was found
/// along with the index in it.
pub attribute: u16,
pub word_index: u16,
/// The position in bytes where the word was found
/// along with the length of it.
///
/// It informs on the original word area in the text indexed
/// without needing to run the tokenizer again.
pub char_index: u16,
pub char_length: u16,
}
/// This structure represent a matching word with informations
/// on the location of the word in the document.
///
/// The order of the field is important because it defines
/// the way these structures are ordered between themselves.
#[derive(Debug, Copy, Clone, PartialEq, Eq, PartialOrd, Ord, Hash)]
pub struct Highlight {
/// The attribute in the document where the word was found
/// along with the index in it.
pub attribute: u16,
/// The position in bytes where the word was found.
///
/// It informs on the original word area in the text indexed
/// without needing to run the tokenizer again.
pub char_index: u16,
/// The length in bytes of the found word.
///
/// It informs on the original word area in the text indexed
/// without needing to run the tokenizer again.
pub char_length: u16,
}
#[doc(hidden)]
#[derive(Debug, Copy, Clone, PartialEq, Eq, PartialOrd, Ord, Hash)]
pub struct TmpMatch {
pub query_index: u32,
pub distance: u8,
pub attribute: u16,
pub word_index: u16,
pub is_exact: bool,
}
#[derive(Debug, Clone, PartialEq, Eq, PartialOrd, Ord, Hash)]
pub struct Document {
pub id: DocumentId,
pub highlights: Vec<Highlight>,
#[cfg(test)]
pub matches: Vec<TmpMatch>,
}
impl Document {
#[cfg(not(test))]
fn from_raw(raw: RawDocument) -> Document {
Document { id: raw.id, highlights: raw.highlights }
}
#[cfg(test)]
fn from_raw(raw: RawDocument) -> Document {
let len = raw.query_index().len();
let mut matches = Vec::with_capacity(len);
let query_index = raw.query_index();
let distance = raw.distance();
let attribute = raw.attribute();
let word_index = raw.word_index();
let is_exact = raw.is_exact();
for i in 0..len {
let match_ = TmpMatch {
query_index: query_index[i],
distance: distance[i],
attribute: attribute[i],
word_index: word_index[i],
is_exact: is_exact[i],
};
matches.push(match_);
}
Document { id: raw.id, matches, highlights: raw.highlights }
}
}
#[cfg(test)]
mod tests {
use super::*;
use std::mem;
#[test]
fn docindex_mem_size() {
assert_eq!(mem::size_of::<DocIndex>(), 16);
}
}