Merge pull request #36 from meilisearch/index-facets

Index facets values and support facet numbers
This commit is contained in:
Clément Renault 2020-11-14 14:32:05 +01:00 committed by GitHub
commit b0c5f59c07
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GPG Key ID: 4AEE18F83AFDEB23
21 changed files with 812 additions and 182 deletions

17
Cargo.lock generated
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@ -550,6 +550,12 @@ dependencies = [
"cfg-if 0.1.10",
]
[[package]]
name = "maplit"
version = "1.0.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "3e2e65a1a2e43cfcb47a895c4c8b10d1f4a61097f9f254f183aee60cad9c651d"
[[package]]
name = "matches"
version = "0.1.8"
@ -608,10 +614,12 @@ dependencies = [
"levenshtein_automata",
"linked-hash-map",
"log",
"maplit",
"memmap",
"near-proximity",
"obkv",
"once_cell",
"ordered-float",
"rayon",
"ringtail",
"roaring",
@ -708,6 +716,15 @@ version = "11.1.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "a170cebd8021a008ea92e4db85a72f80b35df514ec664b296fdcbb654eac0b2c"
[[package]]
name = "ordered-float"
version = "2.0.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "9fe9037165d7023b1228bc4ae9a2fa1a2b0095eca6c2998c624723dfd01314a5"
dependencies = [
"num-traits",
]
[[package]]
name = "page_size"
version = "0.4.2"

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@ -23,6 +23,7 @@ memmap = "0.7.0"
near-proximity = { git = "https://github.com/Kerollmops/plane-sweep-proximity", rev = "6608205" }
obkv = "0.1.0"
once_cell = "1.4.0"
ordered-float = "2.0.0"
rayon = "1.3.1"
ringtail = "0.3.0"
roaring = "0.6.1"
@ -44,6 +45,7 @@ stderrlog = "0.5.0"
[dev-dependencies]
criterion = "0.3.3"
maplit = "1.0.2"
[build-dependencies]
fst = "0.4.4"

10
http-ui/Cargo.lock generated
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@ -989,6 +989,7 @@ dependencies = [
"near-proximity",
"obkv",
"once_cell",
"ordered-float",
"rayon",
"ringtail",
"roaring",
@ -1205,6 +1206,15 @@ version = "0.3.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "624a8340c38c1b80fd549087862da4ba43e08858af025b236e509b6649fc13d5"
[[package]]
name = "ordered-float"
version = "2.0.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "9fe9037165d7023b1228bc4ae9a2fa1a2b0095eca6c2998c624723dfd01314a5"
dependencies = [
"num-traits",
]
[[package]]
name = "page_size"
version = "0.4.2"

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@ -1,5 +1,5 @@
use std::borrow::Cow;
use std::collections::HashSet;
use std::collections::{HashMap, HashSet};
use std::fs::{File, create_dir_all};
use std::net::SocketAddr;
use std::path::PathBuf;
@ -210,6 +210,8 @@ enum UpdateMetaProgress {
}
#[derive(Debug, Clone, Serialize, Deserialize)]
#[serde(deny_unknown_fields)]
#[serde(rename_all = "camelCase")]
struct Settings {
#[serde(
default,
@ -224,6 +226,9 @@ struct Settings {
skip_serializing_if = "Option::is_none",
)]
searchable_attributes: Option<Option<Vec<String>>>,
#[serde(default)]
faceted_attributes: Option<HashMap<String, String>>,
}
// Any value that is present is considered Some value, including null.
@ -367,6 +372,11 @@ async fn main() -> anyhow::Result<()> {
}
}
// We transpose the settings JSON struct into a real setting update.
if let Some(facet_types) = settings.faceted_attributes {
builder.set_faceted_fields(facet_types);
}
let result = builder.execute(|indexing_step| {
let (current, total) = match indexing_step {
TransformFromUserIntoGenericFormat { documents_seen } => (documents_seen, None),

50
src/facet/facet_type.rs Normal file
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@ -0,0 +1,50 @@
use std::error::Error;
use std::fmt;
use std::str::FromStr;
use serde::{Serialize, Deserialize};
#[derive(Debug, Copy, Clone, PartialOrd, Ord, PartialEq, Eq, Hash)]
#[derive(Serialize, Deserialize)]
pub enum FacetType {
String,
Float,
Integer,
}
impl fmt::Display for FacetType {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
match self {
FacetType::String => f.write_str("string"),
FacetType::Float => f.write_str("float"),
FacetType::Integer => f.write_str("integer"),
}
}
}
impl FromStr for FacetType {
type Err = InvalidFacetType;
fn from_str(s: &str) -> Result<Self, Self::Err> {
if s.eq_ignore_ascii_case("string") {
Ok(FacetType::String)
} else if s.eq_ignore_ascii_case("float") {
Ok(FacetType::Float)
} else if s.eq_ignore_ascii_case("integer") {
Ok(FacetType::Integer)
} else {
Err(InvalidFacetType)
}
}
}
#[derive(Debug, Copy, Clone, PartialOrd, Ord, PartialEq, Eq, Hash)]
pub struct InvalidFacetType;
impl fmt::Display for InvalidFacetType {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
f.write_str(r#"Invalid facet type, must be "string", "float" or "integer""#)
}
}
impl Error for InvalidFacetType { }

4
src/facet/mod.rs Normal file
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@ -0,0 +1,4 @@
mod facet_type;
pub mod value_encoding;
pub use self::facet_type::FacetType;

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@ -0,0 +1,69 @@
// https://stackoverflow.com/a/43305015/1941280
#[inline]
pub fn f64_into_bytes(float: f64) -> Option<[u8; 8]> {
if float.is_finite() {
if float == 0.0 || float == -0.0 {
return Some(xor_first_bit(0.0_f64.to_be_bytes()));
} else if float.is_sign_negative() {
return Some(xor_all_bits(float.to_be_bytes()));
} else if float.is_sign_positive() {
return Some(xor_first_bit(float.to_be_bytes()));
}
}
None
}
#[inline]
pub fn i64_into_bytes(int: i64) -> [u8; 8] {
xor_first_bit(int.to_be_bytes())
}
#[inline]
pub fn i64_from_bytes(bytes: [u8; 8]) -> i64 {
i64::from_be_bytes(xor_first_bit(bytes))
}
#[inline]
fn xor_first_bit(mut x: [u8; 8]) -> [u8; 8] {
x[0] ^= 0x80;
x
}
#[inline]
fn xor_all_bits(mut x: [u8; 8]) -> [u8; 8] {
x.iter_mut().for_each(|b| *b ^= 0xff);
x
}
#[cfg(test)]
mod tests {
use std::cmp::Ordering::Less;
use super::*;
fn is_sorted<T: Ord>(x: &[T]) -> bool {
x.windows(2).map(|x| x[0].cmp(&x[1])).all(|o| o == Less)
}
#[test]
fn ordered_f64_bytes() {
let a = -13_f64;
let b = -10.0;
let c = -0.0;
let d = 1.0;
let e = 43.0;
let vec: Vec<_> = [a, b, c, d, e].iter().cloned().map(f64_into_bytes).collect();
assert!(is_sorted(&vec), "{:?}", vec);
}
#[test]
fn ordered_i64_bytes() {
let a = -10_i64;
let b = -0_i64;
let c = 1_i64;
let d = 43_i64;
let vec: Vec<_> = [a, b, c, d].iter().cloned().map(i64_into_bytes).collect();
assert!(is_sorted(&vec), "{:?}", vec);
}
}

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@ -0,0 +1,50 @@
use std::borrow::Cow;
use std::convert::TryInto;
use crate::facet::value_encoding::f64_into_bytes;
pub struct FacetValueF64Codec;
impl<'a> heed::BytesDecode<'a> for FacetValueF64Codec {
type DItem = (u8, f64);
fn bytes_decode(bytes: &'a [u8]) -> Option<Self::DItem> {
let (field_id, buffer) = bytes.split_first()?;
let value = buffer[8..].try_into().ok().map(f64::from_be_bytes)?;
Some((*field_id, value))
}
}
impl heed::BytesEncode<'_> for FacetValueF64Codec {
type EItem = (u8, f64);
fn bytes_encode((field_id, value): &Self::EItem) -> Option<Cow<[u8]>> {
let mut buffer = [0u8; 16];
// Write the globally ordered float.
let bytes = f64_into_bytes(*value)?;
buffer[..8].copy_from_slice(&bytes[..]);
// Then the f64 value just to be able to read it back.
let bytes = value.to_be_bytes();
buffer[8..].copy_from_slice(&bytes[..]);
let mut bytes = Vec::with_capacity(buffer.len() + 1);
bytes.push(*field_id);
bytes.extend_from_slice(&buffer[..]);
Some(Cow::Owned(bytes))
}
}
#[cfg(test)]
mod tests {
use heed::{BytesEncode, BytesDecode};
use super::*;
#[test]
fn globally_ordered_f64() {
let bytes = FacetValueF64Codec::bytes_encode(&(3, -32.0)).unwrap();
let (name, value) = FacetValueF64Codec::bytes_decode(&bytes).unwrap();
assert_eq!((name, value), (3, -32.0));
}
}

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@ -0,0 +1,28 @@
use std::borrow::Cow;
use std::convert::TryInto;
use crate::facet::value_encoding::{i64_from_bytes, i64_into_bytes};
pub struct FacetValueI64Codec;
impl<'a> heed::BytesDecode<'a> for FacetValueI64Codec {
type DItem = (u8, i64);
fn bytes_decode(bytes: &'a [u8]) -> Option<Self::DItem> {
let (field_id, buffer) = bytes.split_first()?;
let value = buffer.try_into().map(i64_from_bytes).ok()?;
Some((*field_id, value))
}
}
impl heed::BytesEncode<'_> for FacetValueI64Codec {
type EItem = (u8, i64);
fn bytes_encode((field_id, value): &Self::EItem) -> Option<Cow<[u8]>> {
let value = i64_into_bytes(*value);
let mut bytes = Vec::with_capacity(value.len() + 1);
bytes.push(*field_id);
bytes.extend_from_slice(&value[..]);
Some(Cow::Owned(bytes))
}
}

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@ -0,0 +1,25 @@
use std::borrow::Cow;
use std::str;
pub struct FacetValueStringCodec;
impl<'a> heed::BytesDecode<'a> for FacetValueStringCodec {
type DItem = (u8, &'a str);
fn bytes_decode(bytes: &'a [u8]) -> Option<Self::DItem> {
let (field_id, bytes) = bytes.split_first()?;
let value = str::from_utf8(bytes).ok()?;
Some((*field_id, value))
}
}
impl<'a> heed::BytesEncode<'a> for FacetValueStringCodec {
type EItem = (u8, &'a str);
fn bytes_encode((field_id, value): &Self::EItem) -> Option<Cow<[u8]>> {
let mut bytes = Vec::with_capacity(value.len() + 1);
bytes.push(*field_id);
bytes.extend_from_slice(value.as_bytes());
Some(Cow::Owned(bytes))
}
}

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@ -0,0 +1,7 @@
mod facet_value_f64_codec;
mod facet_value_i64_codec;
mod facet_value_string_codec;
pub use self::facet_value_f64_codec::FacetValueF64Codec;
pub use self::facet_value_i64_codec::FacetValueI64Codec;
pub use self::facet_value_string_codec::FacetValueStringCodec;

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@ -4,6 +4,7 @@ mod cbo_roaring_bitmap_codec;
mod obkv_codec;
mod roaring_bitmap_codec;
mod str_str_u8_codec;
pub mod facet;
pub use self::beu32_str_codec::BEU32StrCodec;
pub use self::bo_roaring_bitmap_codec::BoRoaringBitmapCodec;

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@ -1,4 +1,5 @@
use std::borrow::Cow;
use std::collections::HashMap;
use std::path::Path;
use anyhow::Context;
@ -6,9 +7,10 @@ use heed::types::*;
use heed::{PolyDatabase, Database, RwTxn, RoTxn};
use roaring::RoaringBitmap;
use crate::facet::FacetType;
use crate::fields_ids_map::FieldsIdsMap;
use crate::Search;
use crate::{BEU32, DocumentId};
use crate::fields_ids_map::FieldsIdsMap;
use crate::{
RoaringBitmapCodec, BEU32StrCodec, StrStrU8Codec, ObkvCodec,
BoRoaringBitmapCodec, CboRoaringBitmapCodec,
@ -16,6 +18,7 @@ use crate::{
pub const DISPLAYED_FIELDS_KEY: &str = "displayed-fields";
pub const DOCUMENTS_IDS_KEY: &str = "documents-ids";
pub const FACETED_FIELDS_KEY: &str = "faceted-fields";
pub const FIELDS_IDS_MAP_KEY: &str = "fields-ids-map";
pub const PRIMARY_KEY_KEY: &str = "primary-key";
pub const SEARCHABLE_FIELDS_KEY: &str = "searchable-fields";
@ -34,22 +37,33 @@ pub struct Index {
pub docid_word_positions: Database<BEU32StrCodec, BoRoaringBitmapCodec>,
/// Maps the proximity between a pair of words with all the docids where this relation appears.
pub word_pair_proximity_docids: Database<StrStrU8Codec, CboRoaringBitmapCodec>,
/// Maps the facet field id and the globally ordered value with the docids that corresponds to it.
pub facet_field_id_value_docids: Database<ByteSlice, CboRoaringBitmapCodec>,
/// Maps the document id to the document as an obkv store.
pub documents: Database<OwnedType<BEU32>, ObkvCodec>,
}
impl Index {
pub fn new<P: AsRef<Path>>(mut options: heed::EnvOpenOptions, path: P) -> anyhow::Result<Index> {
options.max_dbs(5);
options.max_dbs(6);
let env = options.open(path)?;
let main = env.create_poly_database(Some("main"))?;
let word_docids = env.create_database(Some("word-docids"))?;
let docid_word_positions = env.create_database(Some("docid-word-positions"))?;
let word_pair_proximity_docids = env.create_database(Some("word-pair-proximity-docids"))?;
let facet_field_id_value_docids = env.create_database(Some("facet-field-id-value-docids"))?;
let documents = env.create_database(Some("documents"))?;
Ok(Index { env, main, word_docids, docid_word_positions, word_pair_proximity_docids, documents })
Ok(Index {
env,
main,
word_docids,
docid_word_positions,
word_pair_proximity_docids,
facet_field_id_value_docids,
documents,
})
}
/// Create a write transaction to be able to write into the index.
@ -175,6 +189,24 @@ impl Index {
self.main.get::<_, Str, ByteSlice>(rtxn, SEARCHABLE_FIELDS_KEY)
}
/* faceted fields */
/// Writes the facet fields ids associated with their facet type or `None` if
/// the facet type is currently unknown.
pub fn put_faceted_fields(&self, wtxn: &mut RwTxn, fields_types: &HashMap<u8, FacetType>) -> heed::Result<()> {
self.main.put::<_, Str, SerdeJson<_>>(wtxn, FACETED_FIELDS_KEY, fields_types)
}
/// Deletes the facet fields ids associated with their facet type.
pub fn delete_faceted_fields(&self, wtxn: &mut RwTxn) -> heed::Result<bool> {
self.main.delete::<_, Str>(wtxn, FACETED_FIELDS_KEY)
}
/// Returns the facet fields ids associated with their facet type.
pub fn faceted_fields(&self, wtxn: &RoTxn) -> heed::Result<HashMap<u8, FacetType>> {
Ok(self.main.get::<_, Str, SerdeJson<_>>(wtxn, FACETED_FIELDS_KEY)?.unwrap_or_default())
}
/* words fst */
/// Writes the FST which is the words dictionnary of the engine.

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@ -4,6 +4,7 @@ mod index;
mod mdfs;
mod query_tokens;
mod search;
pub mod facet;
pub mod heed_codec;
pub mod proximity;
pub mod subcommand;
@ -33,6 +34,7 @@ pub type FastMap8<K, V> = HashMap<K, V, BuildHasherDefault<FxHasher64>>;
pub type SmallString32 = smallstr::SmallString<[u8; 32]>;
pub type SmallVec32<T> = smallvec::SmallVec<[T; 32]>;
pub type SmallVec16<T> = smallvec::SmallVec<[T; 16]>;
pub type SmallVec8<T> = smallvec::SmallVec<[T; 8]>;
pub type BEU32 = heed::zerocopy::U32<heed::byteorder::BE>;
pub type BEU64 = heed::zerocopy::U64<heed::byteorder::BE>;
pub type DocumentId = u32;
@ -60,9 +62,9 @@ pub fn obkv_to_json(
}
/// Transform a JSON value into a string that can be indexed.
pub fn json_to_string(value: Value) -> Option<String> {
pub fn json_to_string(value: &Value) -> Option<String> {
fn inner(value: Value, output: &mut String) -> bool {
fn inner(value: &Value, output: &mut String) -> bool {
use std::fmt::Write;
match value {
Value::Null => false,
@ -121,7 +123,7 @@ mod tests {
"not_there": null,
});
let string = json_to_string(value).unwrap();
let string = json_to_string(&value).unwrap();
assert_eq!(string, "name: John Doe. age: 43. ");
}
@ -135,7 +137,7 @@ mod tests {
null,
]);
let string = json_to_string(value).unwrap();
let string = json_to_string(&value).unwrap();
// We don't care about having two point (.) after the other as
// the distance of hard separators is clamped to 8 anyway.
assert_eq!(string, "name: John Doe. . 43. hello. I. am. fine. . ");

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@ -78,6 +78,16 @@ enum Command {
words: Vec<String>,
},
/// Outputs a CSV with the documents ids along with the facet values where it appears.
FacetValuesDocids {
/// Display the whole documents ids in details.
#[structopt(long)]
full_display: bool,
/// The field name in the document.
field_name: String,
},
/// Outputs the total size of all the docid-word-positions keys and values.
TotalDocidWordPositionsSize,
@ -147,6 +157,9 @@ pub fn run(opt: Opt) -> anyhow::Result<()> {
MostCommonWords { limit } => most_common_words(&index, &rtxn, limit),
BiggestValues { limit } => biggest_value_sizes(&index, &rtxn, limit),
WordsDocids { full_display, words } => words_docids(&index, &rtxn, !full_display, words),
FacetValuesDocids { full_display, field_name } => {
facet_values_docids(&index, &rtxn, !full_display, field_name)
},
TotalDocidWordPositionsSize => total_docid_word_positions_size(&index, &rtxn),
AverageNumberOfWordsByDoc => average_number_of_words_by_doc(&index, &rtxn),
AverageNumberOfPositionsByWord => {
@ -256,6 +269,64 @@ fn words_docids(index: &Index, rtxn: &heed::RoTxn, debug: bool, words: Vec<Strin
Ok(wtr.flush()?)
}
fn facet_values_docids(index: &Index, rtxn: &heed::RoTxn, debug: bool, field_name: String) -> anyhow::Result<()> {
use crate::facet::FacetType;
use crate::heed_codec::facet::{FacetValueStringCodec, FacetValueF64Codec, FacetValueI64Codec};
use heed::{BytesDecode, Error::Decoding};
let fields_ids_map = index.fields_ids_map(&rtxn)?;
let faceted_fields = index.faceted_fields(&rtxn)?;
let field_id = fields_ids_map.id(&field_name)
.with_context(|| format!("field {} not found", field_name))?;
let field_type = faceted_fields.get(&field_id)
.with_context(|| format!("field {} is not faceted", field_name))?;
let iter = index.facet_field_id_value_docids.prefix_iter(&rtxn, &[field_id])?;
let iter = match field_type {
FacetType::String => {
let iter = iter
.map(|result| result.and_then(|(key, value)| {
let (_, key) = FacetValueStringCodec::bytes_decode(key).ok_or(Decoding)?;
Ok((key.to_string(), value))
}));
Box::new(iter) as Box<dyn Iterator<Item=_>>
},
FacetType::Float => {
let iter = iter
.map(|result| result.and_then(|(key, value)| {
let (_, key) = FacetValueF64Codec::bytes_decode(key).ok_or(Decoding)?;
Ok((key.to_string(), value))
}));
Box::new(iter)
},
FacetType::Integer => {
let iter = iter
.map(|result| result.and_then(|(key, value)| {
let (_, key) = FacetValueI64Codec::bytes_decode(key).ok_or(Decoding)?;
Ok((key.to_string(), value))
}));
Box::new(iter)
},
};
let stdout = io::stdout();
let mut wtr = csv::Writer::from_writer(stdout.lock());
wtr.write_record(&["facet_value", "documents_ids"])?;
for result in iter {
let (value, docids) = result?;
let docids = if debug {
format!("{:?}", docids)
} else {
format!("{:?}", docids.iter().collect::<Vec<_>>())
};
wtr.write_record(&[value, docids])?;
}
Ok(wtr.flush()?)
}
fn export_words_fst(index: &Index, rtxn: &heed::RoTxn, output: PathBuf) -> anyhow::Result<()> {
use std::fs::File;
use std::io::Write as _;

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@ -18,33 +18,25 @@ impl<'t, 'u, 'i> ClearDocuments<'t, 'u, 'i> {
word_docids,
docid_word_positions,
word_pair_proximity_docids,
facet_field_id_value_docids,
documents,
} = self.index;
// We clear the word fst.
// We retrieve the number of documents ids that we are deleting.
let number_of_documents = self.index.number_of_documents(self.wtxn)?;
// We clean some of the main engine datastructures.
self.index.put_words_fst(self.wtxn, &fst::Set::default())?;
// We clear the users ids documents ids.
self.index.put_users_ids_documents_ids(self.wtxn, &fst::Map::default())?;
// We retrieve the documents ids.
let documents_ids = self.index.documents_ids(self.wtxn)?;
// We clear the internal documents ids.
self.index.put_documents_ids(self.wtxn, &RoaringBitmap::default())?;
// We clear the word docids.
// Clear the other databases.
word_docids.clear(self.wtxn)?;
// We clear the docid word positions.
docid_word_positions.clear(self.wtxn)?;
// We clear the word pair proximity docids.
word_pair_proximity_docids.clear(self.wtxn)?;
// We clear the documents themselves.
facet_field_id_value_docids.clear(self.wtxn)?;
documents.clear(self.wtxn)?;
Ok(documents_ids.len() as usize)
Ok(number_of_documents)
}
}

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@ -76,6 +76,7 @@ impl<'t, 'u, 'i> DeleteDocuments<'t, 'u, 'i> {
word_docids,
docid_word_positions,
word_pair_proximity_docids,
facet_field_id_value_docids,
documents,
} = self.index;
@ -158,7 +159,9 @@ impl<'t, 'u, 'i> DeleteDocuments<'t, 'u, 'i> {
}
// We construct an FST set that contains the words to delete from the words FST.
let words_to_delete = words.iter().filter_map(|(w, d)| if *d { Some(w.as_ref()) } else { None });
let words_to_delete = words.iter().filter_map(|(word, must_remove)| {
if *must_remove { Some(word.as_ref()) } else { None }
});
let words_to_delete = fst::Set::from_iter(words_to_delete)?;
let new_words_fst = {
@ -191,6 +194,20 @@ impl<'t, 'u, 'i> DeleteDocuments<'t, 'u, 'i> {
}
}
drop(iter);
// We delete the documents ids that are under the facet field id values.
let mut iter = facet_field_id_value_docids.iter_mut(self.wtxn)?;
while let Some(result) = iter.next() {
let (bytes, mut docids) = result?;
docids.difference_with(&self.documents_ids);
if docids.is_empty() {
iter.del_current()?;
} else {
iter.put_current(bytes, &docids)?;
}
}
Ok(self.documents_ids.len() as usize)
}
}

View File

@ -29,23 +29,13 @@ pub fn main_merge(key: &[u8], values: &[Cow<[u8]>]) -> anyhow::Result<Vec<u8>> {
ensure!(values.windows(2).all(|vs| vs[0] == vs[1]), "fields ids map doesn't match");
Ok(values[0].to_vec())
},
DOCUMENTS_IDS_KEY => word_docids_merge(&[], values),
DOCUMENTS_IDS_KEY => roaring_bitmap_merge(values),
otherwise => bail!("wut {:?}", otherwise),
}
}
pub fn word_docids_merge(_key: &[u8], values: &[Cow<[u8]>]) -> anyhow::Result<Vec<u8>> {
let (head, tail) = values.split_first().unwrap();
let mut head = RoaringBitmap::deserialize_from(&head[..])?;
for value in tail {
let bitmap = RoaringBitmap::deserialize_from(&value[..])?;
head.union_with(&bitmap);
}
let mut vec = Vec::with_capacity(head.serialized_size());
head.serialize_into(&mut vec)?;
Ok(vec)
roaring_bitmap_merge(values)
}
pub fn docid_word_positions_merge(key: &[u8], _values: &[Cow<[u8]>]) -> anyhow::Result<Vec<u8>> {
@ -53,17 +43,11 @@ pub fn docid_word_positions_merge(key: &[u8], _values: &[Cow<[u8]>]) -> anyhow::
}
pub fn words_pairs_proximities_docids_merge(_key: &[u8], values: &[Cow<[u8]>]) -> anyhow::Result<Vec<u8>> {
let (head, tail) = values.split_first().unwrap();
let mut head = CboRoaringBitmapCodec::deserialize_from(&head[..])?;
cbo_roaring_bitmap_merge(values)
}
for value in tail {
let bitmap = CboRoaringBitmapCodec::deserialize_from(&value[..])?;
head.union_with(&bitmap);
}
let mut vec = Vec::new();
CboRoaringBitmapCodec::serialize_into(&head, &mut vec)?;
Ok(vec)
pub fn facet_field_value_docids_merge(_key: &[u8], values: &[Cow<[u8]>]) -> anyhow::Result<Vec<u8>> {
cbo_roaring_bitmap_merge(values)
}
pub fn documents_merge(key: &[u8], _values: &[Cow<[u8]>]) -> anyhow::Result<Vec<u8>> {
@ -85,3 +69,31 @@ pub fn merge_two_obkvs(base: obkv::KvReader, update: obkv::KvReader, buffer: &mu
writer.finish().unwrap();
}
fn roaring_bitmap_merge(values: &[Cow<[u8]>]) -> anyhow::Result<Vec<u8>> {
let (head, tail) = values.split_first().unwrap();
let mut head = RoaringBitmap::deserialize_from(&head[..])?;
for value in tail {
let bitmap = RoaringBitmap::deserialize_from(&value[..])?;
head.union_with(&bitmap);
}
let mut vec = Vec::with_capacity(head.serialized_size());
head.serialize_into(&mut vec)?;
Ok(vec)
}
fn cbo_roaring_bitmap_merge(values: &[Cow<[u8]>]) -> anyhow::Result<Vec<u8>> {
let (head, tail) = values.split_first().unwrap();
let mut head = CboRoaringBitmapCodec::deserialize_from(&head[..])?;
for value in tail {
let bitmap = CboRoaringBitmapCodec::deserialize_from(&value[..])?;
head.union_with(&bitmap);
}
let mut vec = Vec::new();
CboRoaringBitmapCodec::serialize_into(&head, &mut vec)?;
Ok(vec)
}

View File

@ -16,10 +16,10 @@ use rayon::ThreadPool;
use crate::index::Index;
use crate::update::UpdateIndexingStep;
use self::store::Store;
use self::store::{Store, Readers};
use self::merge_function::{
main_merge, word_docids_merge, words_pairs_proximities_docids_merge,
docid_word_positions_merge, documents_merge,
docid_word_positions_merge, documents_merge, facet_field_value_docids_merge,
};
pub use self::transform::{Transform, TransformOutput};
@ -327,8 +327,10 @@ impl<'t, 'u, 'i, 'a> IndexDocuments<'t, 'u, 'i, 'a> {
enum DatabaseType {
Main,
WordDocids,
FacetValuesDocids,
}
let faceted_fields = self.index.faceted_fields(self.wtxn)?;
let searchable_fields: HashSet<_> = match self.index.searchable_fields(self.wtxn)? {
Some(fields) => fields.iter().copied().collect(),
None => fields_ids_map.iter().map(|(id, _name)| id).collect(),
@ -362,6 +364,7 @@ impl<'t, 'u, 'i, 'a> IndexDocuments<'t, 'u, 'i, 'a> {
.map(|(i, documents)| {
let store = Store::new(
searchable_fields.clone(),
faceted_fields.clone(),
linked_hash_map_size,
max_nb_chunks,
max_memory_by_job,
@ -384,13 +387,23 @@ impl<'t, 'u, 'i, 'a> IndexDocuments<'t, 'u, 'i, 'a> {
let mut word_docids_readers = Vec::with_capacity(readers.len());
let mut docid_word_positions_readers = Vec::with_capacity(readers.len());
let mut words_pairs_proximities_docids_readers = Vec::with_capacity(readers.len());
let mut facet_field_value_docids_readers = Vec::with_capacity(readers.len());
let mut documents_readers = Vec::with_capacity(readers.len());
readers.into_iter().for_each(|readers| {
main_readers.push(readers.main);
word_docids_readers.push(readers.word_docids);
docid_word_positions_readers.push(readers.docid_word_positions);
words_pairs_proximities_docids_readers.push(readers.words_pairs_proximities_docids);
documents_readers.push(readers.documents);
let Readers {
main,
word_docids,
docid_word_positions,
words_pairs_proximities_docids,
facet_field_value_docids,
documents
} = readers;
main_readers.push(main);
word_docids_readers.push(word_docids);
docid_word_positions_readers.push(docid_word_positions);
words_pairs_proximities_docids_readers.push(words_pairs_proximities_docids);
facet_field_value_docids_readers.push(facet_field_value_docids);
documents_readers.push(documents);
});
// This is the function that merge the readers
@ -413,6 +426,11 @@ impl<'t, 'u, 'i, 'a> IndexDocuments<'t, 'u, 'i, 'a> {
vec![
(DatabaseType::Main, main_readers, main_merge as MergeFn),
(DatabaseType::WordDocids, word_docids_readers, word_docids_merge),
(
DatabaseType::FacetValuesDocids,
facet_field_value_docids_readers,
facet_field_value_docids_merge,
),
]
.into_par_iter()
.for_each(|(dbtype, readers, merge)| {
@ -463,9 +481,11 @@ impl<'t, 'u, 'i, 'a> IndexDocuments<'t, 'u, 'i, 'a> {
self.index.put_documents_ids(self.wtxn, &documents_ids)?;
let mut database_count = 0;
let total_databases = 6;
progress_callback(UpdateIndexingStep::MergeDataIntoFinalDatabase {
databases_seen: 0,
total_databases: 5,
total_databases,
});
debug!("Writing the docid word positions into LMDB on disk...");
@ -480,7 +500,7 @@ impl<'t, 'u, 'i, 'a> IndexDocuments<'t, 'u, 'i, 'a> {
database_count += 1;
progress_callback(UpdateIndexingStep::MergeDataIntoFinalDatabase {
databases_seen: database_count,
total_databases: 5,
total_databases,
});
debug!("Writing the documents into LMDB on disk...");
@ -495,7 +515,7 @@ impl<'t, 'u, 'i, 'a> IndexDocuments<'t, 'u, 'i, 'a> {
database_count += 1;
progress_callback(UpdateIndexingStep::MergeDataIntoFinalDatabase {
databases_seen: database_count,
total_databases: 5,
total_databases,
});
debug!("Writing the words pairs proximities docids into LMDB on disk...");
@ -510,7 +530,7 @@ impl<'t, 'u, 'i, 'a> IndexDocuments<'t, 'u, 'i, 'a> {
database_count += 1;
progress_callback(UpdateIndexingStep::MergeDataIntoFinalDatabase {
databases_seen: database_count,
total_databases: 5,
total_databases,
});
for (db_type, result) in receiver {
@ -537,16 +557,27 @@ impl<'t, 'u, 'i, 'a> IndexDocuments<'t, 'u, 'i, 'a> {
write_method,
)?;
},
DatabaseType::FacetValuesDocids => {
debug!("Writing the facet values docids into LMDB on disk...");
let db = *self.index.facet_field_id_value_docids.as_polymorph();
write_into_lmdb_database(
self.wtxn,
db,
content,
facet_field_value_docids_merge,
write_method,
)?;
},
}
database_count += 1;
progress_callback(UpdateIndexingStep::MergeDataIntoFinalDatabase {
databases_seen: database_count,
total_databases: 5,
total_databases,
});
}
debug_assert_eq!(database_count, 5);
debug_assert_eq!(database_count, total_databases);
info!("Transform output indexed in {:.02?}", before_indexing.elapsed());

View File

@ -1,3 +1,4 @@
use std::borrow::Cow;
use std::collections::{BTreeMap, HashMap, HashSet};
use std::convert::{TryFrom, TryInto};
use std::fs::File;
@ -5,22 +6,29 @@ use std::iter::FromIterator;
use std::time::Instant;
use std::{cmp, iter};
use anyhow::Context;
use anyhow::{bail, Context};
use bstr::ByteSlice as _;
use grenad::{Reader, FileFuse, Writer, Sorter, CompressionType};
use heed::BytesEncode;
use linked_hash_map::LinkedHashMap;
use log::{debug, info};
use grenad::{Reader, FileFuse, Writer, Sorter, CompressionType};
use ordered_float::OrderedFloat;
use roaring::RoaringBitmap;
use serde_json::Value;
use tempfile::tempfile;
use crate::facet::FacetType;
use crate::heed_codec::{BoRoaringBitmapCodec, CboRoaringBitmapCodec};
use crate::heed_codec::facet::{FacetValueStringCodec, FacetValueF64Codec, FacetValueI64Codec};
use crate::tokenizer::{simple_tokenizer, only_token};
use crate::update::UpdateIndexingStep;
use crate::{json_to_string, SmallVec32, Position, DocumentId};
use crate::{json_to_string, SmallVec8, SmallVec32, SmallString32, Position, DocumentId};
use super::{MergeFn, create_writer, create_sorter, writer_into_reader};
use super::merge_function::{main_merge, word_docids_merge, words_pairs_proximities_docids_merge};
use super::merge_function::{
main_merge, word_docids_merge, words_pairs_proximities_docids_merge,
facet_field_value_docids_merge,
};
const LMDB_MAX_KEY_LENGTH: usize = 511;
const ONE_KILOBYTE: usize = 1024 * 1024;
@ -33,17 +41,21 @@ pub struct Readers {
pub word_docids: Reader<FileFuse>,
pub docid_word_positions: Reader<FileFuse>,
pub words_pairs_proximities_docids: Reader<FileFuse>,
pub facet_field_value_docids: Reader<FileFuse>,
pub documents: Reader<FileFuse>,
}
pub struct Store {
// Indexing parameters
searchable_fields: HashSet<u8>,
faceted_fields: HashMap<u8, FacetType>,
// Caches
word_docids: LinkedHashMap<SmallVec32<u8>, RoaringBitmap>,
word_docids_limit: usize,
words_pairs_proximities_docids: LinkedHashMap<(SmallVec32<u8>, SmallVec32<u8>, u8), RoaringBitmap>,
words_pairs_proximities_docids_limit: usize,
facet_field_value_docids: LinkedHashMap<(u8, FacetValue), RoaringBitmap>,
facet_field_value_docids_limit: usize,
// MTBL parameters
chunk_compression_type: CompressionType,
chunk_compression_level: Option<u32>,
@ -52,6 +64,7 @@ pub struct Store {
main_sorter: Sorter<MergeFn>,
word_docids_sorter: Sorter<MergeFn>,
words_pairs_proximities_docids_sorter: Sorter<MergeFn>,
facet_field_value_docids_sorter: Sorter<MergeFn>,
// MTBL writers
docid_word_positions_writer: Writer<File>,
documents_writer: Writer<File>,
@ -60,6 +73,7 @@ pub struct Store {
impl Store {
pub fn new(
searchable_fields: HashSet<u8>,
faceted_fields: HashMap<u8, FacetType>,
linked_hash_map_size: Option<usize>,
max_nb_chunks: Option<usize>,
max_memory: Option<usize>,
@ -69,7 +83,7 @@ impl Store {
) -> anyhow::Result<Store>
{
// We divide the max memory by the number of sorter the Store have.
let max_memory = max_memory.map(|mm| cmp::max(ONE_KILOBYTE, mm / 3));
let max_memory = max_memory.map(|mm| cmp::max(ONE_KILOBYTE, mm / 4));
let linked_hash_map_size = linked_hash_map_size.unwrap_or(500);
let main_sorter = create_sorter(
@ -96,6 +110,14 @@ impl Store {
max_nb_chunks,
max_memory,
);
let facet_field_value_docids_sorter = create_sorter(
facet_field_value_docids_merge,
chunk_compression_type,
chunk_compression_level,
chunk_fusing_shrink_size,
max_nb_chunks,
max_memory,
);
let documents_writer = tempfile().and_then(|f| {
create_writer(chunk_compression_type, chunk_compression_level, f)
@ -107,11 +129,14 @@ impl Store {
Ok(Store {
// Indexing parameters.
searchable_fields,
faceted_fields,
// Caches
word_docids: LinkedHashMap::with_capacity(linked_hash_map_size),
word_docids_limit: linked_hash_map_size,
words_pairs_proximities_docids: LinkedHashMap::with_capacity(linked_hash_map_size),
words_pairs_proximities_docids_limit: linked_hash_map_size,
facet_field_value_docids: LinkedHashMap::with_capacity(linked_hash_map_size),
facet_field_value_docids_limit: linked_hash_map_size,
// MTBL parameters
chunk_compression_type,
chunk_compression_level,
@ -120,6 +145,7 @@ impl Store {
main_sorter,
word_docids_sorter,
words_pairs_proximities_docids_sorter,
facet_field_value_docids_sorter,
// MTBL writers
docid_word_positions_writer,
documents_writer,
@ -147,6 +173,35 @@ impl Store {
Ok(())
}
// Save the documents ids under the facet field id and value we have seen it.
fn insert_facet_values_docid(
&mut self,
field_id: u8,
field_value: FacetValue,
id: DocumentId,
) -> anyhow::Result<()>
{
let key = (field_id, field_value);
// if get_refresh finds the element it is assured to be at the end of the linked hash map.
match self.facet_field_value_docids.get_refresh(&key) {
Some(old) => { old.insert(id); },
None => {
// A newly inserted element is append at the end of the linked hash map.
self.facet_field_value_docids.insert(key, RoaringBitmap::from_iter(Some(id)));
// If the word docids just reached it's capacity we must make sure to remove
// one element, this way next time we insert we doesn't grow the capacity.
if self.facet_field_value_docids.len() == self.facet_field_value_docids_limit {
// Removing the front element is equivalent to removing the LRU element.
Self::write_docid_facet_field_values(
&mut self.facet_field_value_docids_sorter,
self.facet_field_value_docids.pop_front(),
)?;
}
}
}
Ok(())
}
// Save the documents ids under the words pairs proximities that it contains.
fn insert_words_pairs_proximities_docids<'a>(
&mut self,
@ -187,7 +242,8 @@ impl Store {
fn write_document(
&mut self,
document_id: DocumentId,
words_positions: &HashMap<String, SmallVec32<Position>>,
words_positions: &mut HashMap<String, SmallVec32<Position>>,
facet_values: &mut HashMap<u8, SmallVec8<FacetValue>>,
record: &[u8],
) -> anyhow::Result<()>
{
@ -196,13 +252,20 @@ impl Store {
self.insert_words_pairs_proximities_docids(words_pair_proximities, document_id)?;
// We store document_id associated with all the words the record contains.
for (word, _) in words_positions {
self.insert_word_docid(word, document_id)?;
for (word, _) in words_positions.drain() {
self.insert_word_docid(&word, document_id)?;
}
self.documents_writer.insert(document_id.to_be_bytes(), record)?;
Self::write_docid_word_positions(&mut self.docid_word_positions_writer, document_id, words_positions)?;
// We store document_id associated with all the field id and values.
for (field, values) in facet_values.drain() {
for value in values {
self.insert_facet_values_docid(field, value, document_id)?;
}
}
Ok(())
}
@ -263,6 +326,31 @@ impl Store {
Ok(())
}
fn write_docid_facet_field_values<I>(
sorter: &mut Sorter<MergeFn>,
iter: I,
) -> anyhow::Result<()>
where I: IntoIterator<Item=((u8, FacetValue), RoaringBitmap)>
{
use FacetValue::*;
for ((field_id, value), docids) in iter {
let result = match value {
String(s) => FacetValueStringCodec::bytes_encode(&(field_id, &s)).map(Cow::into_owned),
Float(f) => FacetValueF64Codec::bytes_encode(&(field_id, *f)).map(Cow::into_owned),
Integer(i) => FacetValueI64Codec::bytes_encode(&(field_id, i)).map(Cow::into_owned),
};
let key = result.context("could not serialize facet key")?;
let bytes = CboRoaringBitmapCodec::bytes_encode(&docids)
.context("could not serialize docids")?;
if lmdb_key_valid_size(&key) {
sorter.insert(&key, &bytes)?;
}
}
Ok(())
}
fn write_word_docids<I>(sorter: &mut Sorter<MergeFn>, iter: I) -> anyhow::Result<()>
where I: IntoIterator<Item=(SmallVec32<u8>, RoaringBitmap)>
{
@ -301,6 +389,7 @@ impl Store {
let mut before = Instant::now();
let mut words_positions = HashMap::new();
let mut facet_values = HashMap::new();
let mut count: usize = 0;
while let Some((key, value)) = documents.next()? {
@ -320,27 +409,34 @@ impl Store {
}
for (attr, content) in document.iter() {
if !self.searchable_fields.contains(&attr) {
continue;
}
if self.faceted_fields.contains_key(&attr) || self.searchable_fields.contains(&attr) {
let value = serde_json::from_slice(content)?;
let value = serde_json::from_slice(content)?;
let content = match json_to_string(value) {
Some(content) => content,
None => continue,
};
if let Some(ftype) = self.faceted_fields.get(&attr) {
let mut values = parse_facet_value(*ftype, &value).with_context(|| {
format!("extracting facets from the value {}", value)
})?;
facet_values.entry(attr).or_insert_with(SmallVec8::new).extend(values.drain(..));
}
let tokens = simple_tokenizer(&content).filter_map(only_token);
for (pos, token) in tokens.enumerate().take(MAX_POSITION) {
let word = token.to_lowercase();
let position = (attr as usize * MAX_POSITION + pos) as u32;
words_positions.entry(word).or_insert_with(SmallVec32::new).push(position);
if self.searchable_fields.contains(&attr) {
let content = match json_to_string(&value) {
Some(content) => content,
None => continue,
};
let tokens = simple_tokenizer(&content).filter_map(only_token);
for (pos, token) in tokens.enumerate().take(MAX_POSITION) {
let word = token.to_lowercase();
let position = (attr as usize * MAX_POSITION + pos) as u32;
words_positions.entry(word).or_insert_with(SmallVec32::new).push(position);
}
}
}
}
// We write the document in the documents store.
self.write_document(document_id, &words_positions, value)?;
words_positions.clear();
self.write_document(document_id, &mut words_positions, &mut facet_values, value)?;
}
// Compute the document id of the next document.
@ -367,6 +463,10 @@ impl Store {
&mut self.words_pairs_proximities_docids_sorter,
self.words_pairs_proximities_docids,
)?;
Self::write_docid_facet_field_values(
&mut self.facet_field_value_docids_sorter,
self.facet_field_value_docids,
)?;
let mut word_docids_wtr = tempfile().and_then(|f| create_writer(comp_type, comp_level, f))?;
let mut builder = fst::SetBuilder::memory();
@ -388,9 +488,13 @@ impl Store {
let mut words_pairs_proximities_docids_wtr = tempfile().and_then(|f| create_writer(comp_type, comp_level, f))?;
self.words_pairs_proximities_docids_sorter.write_into(&mut words_pairs_proximities_docids_wtr)?;
let mut facet_field_value_docids_wtr = tempfile().and_then(|f| create_writer(comp_type, comp_level, f))?;
self.facet_field_value_docids_sorter.write_into(&mut facet_field_value_docids_wtr)?;
let main = writer_into_reader(main_wtr, shrink_size)?;
let word_docids = writer_into_reader(word_docids_wtr, shrink_size)?;
let words_pairs_proximities_docids = writer_into_reader(words_pairs_proximities_docids_wtr, shrink_size)?;
let facet_field_value_docids = writer_into_reader(facet_field_value_docids_wtr, shrink_size)?;
let docid_word_positions = writer_into_reader(self.docid_word_positions_writer, shrink_size)?;
let documents = writer_into_reader(self.documents_writer, shrink_size)?;
@ -399,6 +503,7 @@ impl Store {
word_docids,
docid_word_positions,
words_pairs_proximities_docids,
facet_field_value_docids,
documents,
})
}
@ -444,3 +549,70 @@ fn format_count(n: usize) -> String {
fn lmdb_key_valid_size(key: &[u8]) -> bool {
!key.is_empty() && key.len() <= LMDB_MAX_KEY_LENGTH
}
#[derive(Debug, Clone, PartialEq, Eq, Hash)]
enum FacetValue {
String(SmallString32),
Float(OrderedFloat<f64>),
Integer(i64),
}
fn parse_facet_value(ftype: FacetType, value: &Value) -> anyhow::Result<SmallVec8<FacetValue>> {
use FacetValue::*;
fn inner_parse_facet_value(
ftype: FacetType,
value: &Value,
can_recurse: bool,
output: &mut SmallVec8<FacetValue>,
) -> anyhow::Result<()>
{
match value {
Value::Null => Ok(()),
Value::Bool(b) => Ok(output.push(Integer(*b as i64))),
Value::Number(number) => match ftype {
FacetType::String => bail!("invalid facet type, expecting {} found number", ftype),
FacetType::Float => match number.as_f64() {
Some(float) => Ok(output.push(Float(OrderedFloat(float)))),
None => bail!("invalid facet type, expecting {} found integer", ftype),
},
FacetType::Integer => match number.as_i64() {
Some(integer) => Ok(output.push(Integer(integer))),
None => if number.is_f64() {
bail!("invalid facet type, expecting {} found float", ftype)
} else {
bail!("invalid facet type, expecting {} found out-of-bound integer (64bit)", ftype)
},
},
},
Value::String(string) => {
let string = string.trim();
if string.is_empty() { return Ok(()) }
match ftype {
FacetType::String => {
let string = SmallString32::from(string);
Ok(output.push(String(string)))
},
FacetType::Float => match string.parse() {
Ok(float) => Ok(output.push(Float(OrderedFloat(float)))),
Err(_err) => bail!("invalid facet type, expecting {} found string", ftype),
},
FacetType::Integer => match string.parse() {
Ok(integer) => Ok(output.push(Integer(integer))),
Err(_err) => bail!("invalid facet type, expecting {} found string", ftype),
},
}
},
Value::Array(values) => if can_recurse {
values.iter().map(|v| inner_parse_facet_value(ftype, v, false, output)).collect()
} else {
bail!("invalid facet type, expecting {} found sub-array ()", ftype)
},
Value::Object(_) => bail!("invalid facet type, expecting {} found object", ftype),
}
}
let mut facet_values = SmallVec8::new();
inner_parse_facet_value(ftype, value, true, &mut facet_values)?;
Ok(facet_values)
}

View File

@ -1,9 +1,13 @@
use anyhow::Context;
use std::collections::HashMap;
use std::str::FromStr;
use anyhow::{ensure, Context};
use grenad::CompressionType;
use rayon::ThreadPool;
use crate::update::index_documents::{Transform, IndexDocumentsMethod};
use crate::update::{ClearDocuments, IndexDocuments, UpdateIndexingStep};
use crate::facet::FacetType;
use crate::{Index, FieldsIdsMap};
pub struct Settings<'a, 't, 'u, 'i> {
@ -22,6 +26,7 @@ pub struct Settings<'a, 't, 'u, 'i> {
// however if it is `Some(None)` it means that the user forced a reset of the setting.
searchable_fields: Option<Option<Vec<String>>>,
displayed_fields: Option<Option<Vec<String>>>,
faceted_fields: Option<HashMap<String, String>>,
}
impl<'a, 't, 'u, 'i> Settings<'a, 't, 'u, 'i> {
@ -39,6 +44,7 @@ impl<'a, 't, 'u, 'i> Settings<'a, 't, 'u, 'i> {
thread_pool: None,
searchable_fields: None,
displayed_fields: None,
faceted_fields: None,
}
}
@ -58,71 +64,92 @@ impl<'a, 't, 'u, 'i> Settings<'a, 't, 'u, 'i> {
self.displayed_fields = Some(Some(names));
}
pub fn set_faceted_fields(&mut self, names_facet_types: HashMap<String, String>) {
self.faceted_fields = Some(names_facet_types);
}
pub fn execute<F>(self, progress_callback: F) -> anyhow::Result<()>
where
F: Fn(UpdateIndexingStep) + Sync
{
// Check that the searchable attributes have been specified.
if let Some(value) = self.searchable_fields {
let current_displayed_fields = self.index.displayed_fields(self.wtxn)?;
let current_fields_ids_map = self.index.fields_ids_map(self.wtxn)?;
let mut updated_searchable_fields = None;
let mut updated_faceted_fields = None;
let mut updated_displayed_fields = None;
let result = match value {
Some(fields_names) => {
let mut fields_ids_map = current_fields_ids_map.clone();
let searchable_fields: Vec<_> =
fields_names.iter()
.map(|name| fields_ids_map.insert(name))
.collect::<Option<Vec<_>>>()
.context("field id limit reached")?;
// Construct the new FieldsIdsMap based on the searchable fields order.
let fields_ids_map = self.index.fields_ids_map(self.wtxn)?;
let mut fields_ids_map = match self.searchable_fields {
Some(Some(searchable_fields)) => {
let mut new_fields_ids_map = FieldsIdsMap::new();
let mut new_searchable_fields = Vec::new();
// If the searchable fields are ordered we don't have to generate a new `FieldsIdsMap`.
if searchable_fields.windows(2).all(|win| win[0] < win[1]) {
(
fields_ids_map,
Some(searchable_fields),
current_displayed_fields.map(ToOwned::to_owned),
)
} else {
// We create or generate the fields ids corresponding to those names.
let mut fields_ids_map = FieldsIdsMap::new();
let mut searchable_fields = Vec::new();
for name in fields_names {
let id = fields_ids_map.insert(&name).context("field id limit reached")?;
searchable_fields.push(id);
}
for name in searchable_fields {
let id = new_fields_ids_map.insert(&name).context("field id limit reached")?;
new_searchable_fields.push(id);
}
// We complete the new FieldsIdsMap with the previous names.
for (_id, name) in current_fields_ids_map.iter() {
fields_ids_map.insert(name).context("field id limit reached")?;
}
for (_, name) in fields_ids_map.iter() {
new_fields_ids_map.insert(name).context("field id limit reached")?;
}
// We must also update the displayed fields according to the new `FieldsIdsMap`.
let displayed_fields = match current_displayed_fields {
Some(fields) => {
let mut displayed_fields = Vec::new();
for id in fields {
let name = current_fields_ids_map.name(*id).unwrap();
let id = fields_ids_map.id(name).context("field id limit reached")?;
displayed_fields.push(id);
}
Some(displayed_fields)
},
None => None,
};
updated_searchable_fields = Some(Some(new_searchable_fields));
new_fields_ids_map
},
Some(None) => {
updated_searchable_fields = Some(None);
fields_ids_map
},
None => fields_ids_map,
};
(fields_ids_map, Some(searchable_fields), displayed_fields)
// We compute or generate the new primary key field id.
// TODO make the primary key settable.
let primary_key = match self.index.primary_key(&self.wtxn)? {
Some(id) => {
let current_fields_ids_map = self.index.fields_ids_map(self.wtxn)?;
let name = current_fields_ids_map.name(id).unwrap();
fields_ids_map.insert(name).context("field id limit reached")?
},
None => fields_ids_map.insert("id").context("field id limit reached")?,
};
if let Some(fields_names_facet_types) = self.faceted_fields {
let current_faceted_fields = self.index.faceted_fields(self.wtxn)?;
let mut faceted_fields = HashMap::new();
for (name, sftype) in fields_names_facet_types {
let ftype = FacetType::from_str(&sftype).with_context(|| format!("parsing facet type {:?}", sftype))?;
let id = fields_ids_map.insert(&name).context("field id limit reached")?;
match current_faceted_fields.get(&id) {
Some(pftype) => {
ensure!(ftype == *pftype, "{} facet type changed from {} to {}", name, ftype, pftype);
faceted_fields.insert(id, ftype)
},
None => faceted_fields.insert(id, ftype),
};
}
updated_faceted_fields = Some(faceted_fields);
}
// Check that the displayed attributes have been specified.
if let Some(value) = self.displayed_fields {
match value {
Some(names) => {
let mut new_displayed_fields = Vec::new();
for name in names {
let id = fields_ids_map.insert(&name).context("field id limit reached")?;
new_displayed_fields.push(id);
}
},
None => (
current_fields_ids_map.clone(),
None,
current_displayed_fields.map(ToOwned::to_owned),
),
};
let (mut fields_ids_map, searchable_fields, displayed_fields) = result;
updated_displayed_fields = Some(Some(new_displayed_fields));
}
None => updated_displayed_fields = Some(None),
}
}
// If any setting have modified any of the datastructures it means that we need
// to retrieve the documents and then reindex then with the new settings.
if updated_searchable_fields.is_some() || updated_faceted_fields.is_some() {
let transform = Transform {
rtxn: &self.wtxn,
index: self.index,
@ -136,15 +163,6 @@ impl<'a, 't, 'u, 'i> Settings<'a, 't, 'u, 'i> {
autogenerate_docids: false,
};
// We compute or generate the new primary key field id.
let primary_key = match self.index.primary_key(&self.wtxn)? {
Some(id) => {
let name = current_fields_ids_map.name(id).unwrap();
fields_ids_map.insert(name).context("field id limit reached")?
},
None => fields_ids_map.insert("id").context("field id limit reached")?,
};
// We remap the documents fields based on the new `FieldsIdsMap`.
let output = transform.remap_index_documents(primary_key, fields_ids_map.clone())?;
@ -152,18 +170,18 @@ impl<'a, 't, 'u, 'i> Settings<'a, 't, 'u, 'i> {
// this way next indexing methods will be based on that.
self.index.put_fields_ids_map(self.wtxn, &fields_ids_map)?;
// The new searchable fields are also written down to make sure
// that the IndexDocuments system takes only these ones into account.
match searchable_fields {
Some(fields) => self.index.put_searchable_fields(self.wtxn, &fields)?,
None => self.index.delete_searchable_fields(self.wtxn).map(drop)?,
if let Some(faceted_fields) = updated_faceted_fields {
// We write the faceted_fields fields into the database here.
self.index.put_faceted_fields(self.wtxn, &faceted_fields)?;
}
// We write the displayed fields into the database here
// to make sure that the right fields are displayed.
match displayed_fields {
Some(fields) => self.index.put_displayed_fields(self.wtxn, &fields)?,
None => self.index.delete_displayed_fields(self.wtxn).map(drop)?,
if let Some(searchable_fields) = updated_searchable_fields {
// The new searchable fields are also written down to make sure
// that the IndexDocuments system takes only these ones into account.
match searchable_fields {
Some(fields) => self.index.put_searchable_fields(self.wtxn, &fields)?,
None => self.index.delete_searchable_fields(self.wtxn).map(drop)?,
}
}
// We clear the full database (words-fst, documents ids and documents content).
@ -180,33 +198,15 @@ impl<'a, 't, 'u, 'i> Settings<'a, 't, 'u, 'i> {
indexing_builder.chunk_compression_level = self.chunk_compression_level;
indexing_builder.chunk_fusing_shrink_size = self.chunk_fusing_shrink_size;
indexing_builder.thread_pool = self.thread_pool;
indexing_builder.execute_raw(output, progress_callback)?;
indexing_builder.execute_raw(output, &progress_callback)?;
}
// Check that the displayed attributes have been specified.
if let Some(value) = self.displayed_fields {
match value {
// If it has been set, and it was a list of fields names, we create
// or generate the fields ids corresponds to those names and store them
// in the database in the order they were specified.
Some(fields_names) => {
let mut fields_ids_map = self.index.fields_ids_map(self.wtxn)?;
// We create or generate the fields ids corresponding to those names.
let mut fields_ids = Vec::new();
for name in fields_names {
let id = fields_ids_map.insert(&name).context("field id limit reached")?;
fields_ids.push(id);
}
self.index.put_displayed_fields(self.wtxn, &fields_ids)?;
},
// If it was set to `null` it means that the user wants to get the default behavior
// which is displaying all the attributes in no specific order (FieldsIdsMap order),
// we just have to delete the displayed fields.
None => {
self.index.delete_displayed_fields(self.wtxn)?;
},
if let Some(displayed_fields) = updated_displayed_fields {
// We write the displayed fields into the database here
// to make sure that the right fields are displayed.
match displayed_fields {
Some(fields) => self.index.put_displayed_fields(self.wtxn, &fields)?,
None => self.index.delete_displayed_fields(self.wtxn).map(drop)?,
}
}
@ -219,6 +219,7 @@ mod tests {
use super::*;
use crate::update::{IndexDocuments, UpdateFormat};
use heed::EnvOpenOptions;
use maplit::hashmap;
#[test]
fn set_and_reset_searchable_fields() {
@ -386,4 +387,31 @@ mod tests {
assert_eq!(fields_ids, None);
drop(rtxn);
}
#[test]
fn set_faceted_fields() {
let path = tempfile::tempdir().unwrap();
let mut options = EnvOpenOptions::new();
options.map_size(10 * 1024 * 1024); // 10 MB
let index = Index::new(options, &path).unwrap();
// Set the faceted fields to be the age.
let mut wtxn = index.write_txn().unwrap();
let mut builder = Settings::new(&mut wtxn, &index);
builder.set_faceted_fields(hashmap!{ "age".into() => "integer".into() });
builder.execute(|_| ()).unwrap();
// Then index some documents.
let content = &b"name,age\nkevin,23\nkevina,21\nbenoit,34\n"[..];
let mut builder = IndexDocuments::new(&mut wtxn, &index);
builder.update_format(UpdateFormat::Csv);
builder.execute(content, |_| ()).unwrap();
wtxn.commit().unwrap();
// Check that the displayed fields are correctly set.
let rtxn = index.read_txn().unwrap();
let fields_ids = index.faceted_fields(&rtxn).unwrap();
assert_eq!(fields_ids, hashmap!{ 1 => FacetType::Integer });
drop(rtxn);
}
}