Files
tantivy/examples/warmer.rs
Harrison Burt 1c7c6fd591 POC: Tantivy documents as a trait (#2071)
* fix windows build (#1)

* Fix windows build

* Add doc traits

* Add field value iter

* Add value and serialization

* Adjust order

* Fix bug

* Correct type

* Fix generic bugs

* Reformat code

* Add generic to index writer which I forgot about

* Fix missing generics on single segment writer

* Add missing type export

* Add default methods for convenience

* Cleanup

* Fix more-like-this query to use standard types

* Update API and fix tests

* Add doc traits

* Add field value iter

* Add value and serialization

* Adjust order

* Fix bug

* Correct type

* Rebase main and fix conflicts

* Reformat code

* Merge upstream

* Fix missing generics on single segment writer

* Add missing type export

* Add default methods for convenience

* Cleanup

* Fix more-like-this query to use standard types

* Update API and fix tests

* Add tokenizer improvements from previous commits

* Add tokenizer improvements from previous commits

* Reformat

* Fix unit tests

* Fix unit tests

* Use enum in changes

* Stage changes

* Add new deserializer logic

* Add serializer integration

* Add document deserializer

* Implement new (de)serialization api for existing types

* Fix bugs and type errors

* Add helper implementations

* Fix errors

* Reformat code

* Add unit tests and some code organisation for serialization

* Add unit tests to deserializer

* Add some small docs

* Add support for deserializing serde values

* Reformat

* Fix typo

* Fix typo

* Change repr of facet

* Remove unused trait methods

* Add child value type

* Resolve comments

* Fix build

* Fix more build errors

* Fix more build errors

* Fix the tests I missed

* Fix examples

* fix numerical order, serialize PreTok Str

* fix coverage

* rename Document to TantivyDocument, rename DocumentAccess to Document

add Binary prefix to binary de/serialization

* fix coverage

---------

Co-authored-by: Pascal Seitz <pascal.seitz@gmail.com>
2023-10-02 10:01:16 +02:00

225 lines
7.0 KiB
Rust

use std::cmp::Reverse;
use std::collections::{HashMap, HashSet};
use std::sync::{Arc, RwLock, Weak};
use tantivy::collector::TopDocs;
use tantivy::query::QueryParser;
use tantivy::schema::{Schema, FAST, TEXT};
use tantivy::{
doc, DocAddress, DocId, Index, IndexWriter, Opstamp, Searcher, SearcherGeneration, SegmentId,
SegmentReader, Warmer,
};
// This example shows how warmers can be used to
// load values from an external sources and
// tie their lifecycle to that of the index segments
// using the Warmer API.
//
// In this example, we assume an e-commerce search engine.
type ProductId = u64;
type Price = u32;
pub trait PriceFetcher: Send + Sync + 'static {
fn fetch_prices(&self, product_ids: &[ProductId]) -> Vec<Price>;
}
type SegmentKey = (SegmentId, Option<Opstamp>);
struct DynamicPriceColumn {
field: String,
price_cache: RwLock<HashMap<SegmentKey, Arc<Vec<Price>>>>,
price_fetcher: Box<dyn PriceFetcher>,
}
impl DynamicPriceColumn {
pub fn with_product_id_field<T: PriceFetcher>(field: String, price_fetcher: T) -> Self {
DynamicPriceColumn {
field,
price_cache: Default::default(),
price_fetcher: Box::new(price_fetcher),
}
}
pub fn price_for_segment(&self, segment_reader: &SegmentReader) -> Option<Arc<Vec<Price>>> {
let segment_key = (segment_reader.segment_id(), segment_reader.delete_opstamp());
self.price_cache.read().unwrap().get(&segment_key).cloned()
}
}
impl Warmer for DynamicPriceColumn {
fn warm(&self, searcher: &Searcher) -> tantivy::Result<()> {
for segment in searcher.segment_readers() {
let product_id_reader = segment
.fast_fields()
.u64(&self.field)?
.first_or_default_col(0);
let product_ids: Vec<ProductId> = segment
.doc_ids_alive()
.map(|doc| product_id_reader.get_val(doc))
.collect();
let mut prices = self.price_fetcher.fetch_prices(&product_ids).into_iter();
let prices: Vec<Price> = (0..segment.max_doc())
.map(|doc| {
if !segment.is_deleted(doc) {
prices.next().unwrap()
} else {
0
}
})
.collect();
let key = (segment.segment_id(), segment.delete_opstamp());
self.price_cache
.write()
.unwrap()
.insert(key, Arc::new(prices));
}
Ok(())
}
fn garbage_collect(&self, live_generations: &[&SearcherGeneration]) {
let live_keys: HashSet<SegmentKey> = live_generations
.iter()
.flat_map(|gen| gen.segments())
.map(|(&segment_id, &opstamp)| (segment_id, opstamp))
.collect();
self.price_cache
.write()
.unwrap()
.retain(|key, _| live_keys.contains(key));
}
}
// For the sake of this example, the table is just an editable HashMap behind a RwLock.
// This map represents a map (ProductId -> Price)
//
// In practise, it could be fetching things from an external service, like a SQL table.
#[derive(Default, Clone)]
pub struct ExternalPriceTable {
prices: Arc<RwLock<HashMap<ProductId, Price>>>,
}
impl ExternalPriceTable {
pub fn update_price(&self, product_id: ProductId, price: Price) {
self.prices.write().unwrap().insert(product_id, price);
}
}
impl PriceFetcher for ExternalPriceTable {
fn fetch_prices(&self, product_ids: &[ProductId]) -> Vec<Price> {
let prices = self.prices.read().unwrap();
product_ids
.iter()
.map(|product_id| prices.get(product_id).cloned().unwrap_or(0))
.collect()
}
}
fn main() -> tantivy::Result<()> {
// Declaring our schema.
let mut schema_builder = Schema::builder();
// The product id is assumed to be a primary id for our external price source.
let product_id = schema_builder.add_u64_field("product_id", FAST);
let text = schema_builder.add_text_field("text", TEXT);
let schema: Schema = schema_builder.build();
let price_table = ExternalPriceTable::default();
let price_dynamic_column = Arc::new(DynamicPriceColumn::with_product_id_field(
"product_id".to_string(),
price_table.clone(),
));
price_table.update_price(OLIVE_OIL, 12);
price_table.update_price(GLOVES, 13);
price_table.update_price(SNEAKERS, 80);
const OLIVE_OIL: ProductId = 323423;
const GLOVES: ProductId = 3966623;
const SNEAKERS: ProductId = 23222;
let index = Index::create_in_ram(schema);
let mut writer: IndexWriter = index.writer_with_num_threads(1, 15_000_000)?;
writer.add_document(doc!(product_id=>OLIVE_OIL, text=>"cooking olive oil from greece"))?;
writer.add_document(doc!(product_id=>GLOVES, text=>"kitchen gloves, perfect for cooking"))?;
writer.add_document(doc!(product_id=>SNEAKERS, text=>"uber sweet sneakers"))?;
writer.commit()?;
let warmers = vec![Arc::downgrade(&price_dynamic_column) as Weak<dyn Warmer>];
let reader = index.reader_builder().warmers(warmers).try_into()?;
let query_parser = QueryParser::for_index(&index, vec![text]);
let query = query_parser.parse_query("cooking")?;
let searcher = reader.searcher();
let score_by_price = move |segment_reader: &SegmentReader| {
let price = price_dynamic_column
.price_for_segment(segment_reader)
.unwrap();
move |doc_id: DocId| Reverse(price[doc_id as usize])
};
let most_expensive_first = TopDocs::with_limit(10).custom_score(score_by_price);
let hits = searcher.search(&query, &most_expensive_first)?;
assert_eq!(
&hits,
&[
(
Reverse(12u32),
DocAddress {
segment_ord: 0,
doc_id: 0u32
}
),
(
Reverse(13u32),
DocAddress {
segment_ord: 0,
doc_id: 1u32
}
),
]
);
// Olive oil just got more expensive!
price_table.update_price(OLIVE_OIL, 15);
// The price update are directly reflected on `reload`.
//
// Be careful here though!...
// You may have spotted that we are still using the same `Searcher`.
//
// It is up to the `Warmer` implementer to decide how
// to control this behavior.
reader.reload()?;
let hits_with_new_prices = searcher.search(&query, &most_expensive_first)?;
assert_eq!(
&hits_with_new_prices,
&[
(
Reverse(13u32),
DocAddress {
segment_ord: 0,
doc_id: 1u32
}
),
(
Reverse(15u32),
DocAddress {
segment_ord: 0,
doc_id: 0u32
}
),
]
);
Ok(())
}