Files
tantivy/examples/working_with_json.rs
Paul Masurel 07d87e154b Collector refactoring and multithreaded search (#437)
* Split Collector into an overall Collector and a per-segment SegmentCollector. Precursor to cross-segment parallelism, and as a side benefit cleans up any per-segment fields from being Option<T> to just T.

* Attempt to add MultiCollector back

* working. Chained collector is broken though

* Fix chained collector

* Fix test

* Make Weight Send+Sync for parallelization purposes

* Expose parameters of RangeQuery for external usage

* Removed &mut self

* fixing tests

* Restored TestCollectors

* blop

* multicollector working

* chained collector working

* test broken

* fixing unit test

* blop

* blop

* Blop

* simplifying APi

* blop

* better syntax

* Simplifying top_collector

* refactoring

* blop

* Sync with master

* Added multithread search

* Collector refactoring

* Schema::builder

* CR and rustdoc

* CR comments

* blop

* Added an executor

* Sorted the segment readers in the searcher

* Update searcher.rs

* Fixed unit testst

* changed the place where we have the sort-segment-by-count heuristic

* using crossbeam::channel

* inlining

* Comments about panics propagating

* Added unit test for executor panicking

* Readded default

* Removed Default impl

* Added unit test for executor
2018-11-30 22:46:59 +09:00

42 lines
1.4 KiB
Rust

extern crate tantivy;
use tantivy::schema::*;
// # Document from json
//
// For convenience, `Document` can be parsed directly from json.
fn main() -> tantivy::Result<()> {
// Let's first define a schema and an index.
// Check out the basic example if this is confusing to you.
//
// first we need to define a schema ...
let mut schema_builder = Schema::builder();
schema_builder.add_text_field("title", TEXT | STORED);
schema_builder.add_text_field("body", TEXT);
schema_builder.add_u64_field("year", INT_INDEXED);
let schema = schema_builder.build();
// Let's assume we have a json-serialized document.
let mice_and_men_doc_json = r#"{
"title": "Of Mice and Men",
"year": 1937
}"#;
// We can parse our document
let _mice_and_men_doc = schema.parse_document(&mice_and_men_doc_json)?;
// Multi-valued field are allowed, they are
// expressed in JSON by an array.
// The following document has two titles.
let frankenstein_json = r#"{
"title": ["Frankenstein", "The Modern Prometheus"],
"year": 1818
}"#;
let _frankenstein_doc = schema.parse_document(&frankenstein_json)?;
// Note that the schema is saved in your index directory.
//
// As a result, Indexes are aware of their schema, and you can use this feature
// just by opening an existing `Index`, and calling `index.schema()..parse_document(json)`.
Ok(())
}