Crate elastic_types [−] [src]

Elasticsearch Core Types

An implementation of the core types in Elasticsearch documents.

Provides structs and traits for defining Elasticsearch type mapping, where correctness is enforced by Rust's type system. The act of annotating your types with mapping metadata is zero-cost.

Supported Versions

`elastic_types`	Elasticsearch
`0.x`	`5.x`

Usage

This crate is on crates.io.

There are two ways to reference elastic_types in your projects, depending on whether you're on the stable/beta or nightly channels.

Builds on nightly benefit from compile-time codegen for better performance and easier mapping definitions.

Nightly

To get started, add elastic_types and elastic_types_derive to your Cargo.toml:

[dependencies]
elastic_types = { version = "*", features = "nightly" }
elastic_types_derive = "*"Run

And reference it in your crate root:

#![feature(proc_macro)]

#[macro_use]
extern crate elastic_types_derive;
#[macro_use]
extern crate elastic_types;Run

Stable

To get started, add elastic_types to your Cargo.toml:

[dependencies]
elastic_types = "*"Run

And reference it in your crate root:

#[macro_use]
extern crate elastic_types;Run

Map Your Types

This section shows you how to add mapping metadata on the nightly channel. For mapping on stable, see here.

NOTE: Once Macros 1.1 is stabilised, you'll be able to use elastic_types_derive on the stable channel.

Derive ElasticType on your Elasticsearch-mappable types:

#[derive(Serialize, ElasticType)]
pub struct MyType {
    pub my_date: Date<DefaultDateFormat>,
    pub my_num: i32
}Run

You can then serialise your mapping as json using the TypeMapper:

let mapping = TypeMapper::to_string(MyType::mapping()).unwrap();Run

This will produce the following result:

{
    "properties": {
        "my_date": {
            "type": "date",
            "format": "basic_date_time"
        },
        "my_num": {
            "type": "integer"
        }
    }
}Run

Mapping structs as fields

Of course, structs that derive ElasticType can also be used as fields in other Elasticsearch types:

#[derive(Serialize, Deserialize, ElasticType)]
pub struct MyOtherType {
    pub my_type: MyType
}Run

Our mapping for MyOtherType then looks like:

{
    "properties": {
        "my_type": {
            "type": "nested",
            "properties": {
                "my_date": {
                    "type": "date",
                    "format": "basic_date_time"
                },
                "my_num": {
                    "type": "integer"
                }
            }
        }
    }
}Run

Mapping `Option` and `Vec`

Elasticsearch doesn't differentiate between nullable types or collections, so it's also possible to derive mapping from Option or Vec types:

#[derive(Serialize, Deserialize, ElasticType)]
pub struct MyType {
    pub my_date: Option<Date<DefaultDateFormat>>,
    pub my_num: Vec<i32>
}Run

This produces the same mapping as before. See the object mod for more details.

Overloading default mapping

You can override the default mapping for Elasticsearch's core datatypes by implementing the appropriate trait. In the below example, we create a custom boolean mapping:

#[derive(Default)]
struct MyMapping;
impl BooleanMapping for MyMapping {
    fn boost() -> Option<f32> { Some(1.04) }
}Run

For more details about the supported core datatypes and how to use them, see here.

Serialise Your Types

Types that derive ElasticType are themselves serialisable, which can be very helpful when using types like date with special formats. Take the following document:

{
    "id": 15,
    "timestamp": 1435935302478,
    "title": "my timestamped object"
}Run

Using the Date<EpochMillis> type for the timestamp, we can correctly deserialise the document as a strongly typed object:

#[derive(Serialize, Deserialize, ElasticType)]
struct MyType {
    id: i32,
    timestamp: Date<EpochMillis>,
    title: String
}
 
let de: MyType = serde_json::from_str(json).unwrap();
 
assert_eq!(2015, de.timestamp.year());Run

A Complete Example

Before digging in to the API, consider the following complete example for defining and mapping a type called Article on nightly. As json, the Article type should look something like this:

{
    "id": 1,
    "title": "An article",
    "content": "Some prose for this article.",
    "timstamp": 1435935302478,
    "geoip": {
        "ip": "10.0.0.1",
        "loc": [ -71.34, 41.12 ]
    }
}Run

Our Cargo.toml specifies the dependencies as above:

[dependencies]
elastic_types = { version = "*", features = "nightly" }
elastic_types_derive = "*"Run

And our main.rs contains the following:

 
#[macro_use]
extern crate serde_derive;
extern crate serde;
 
#[macro_use]
extern crate elastic_types_derive;
#[macro_use]
extern crate elastic_types;
 
use elastic_types::prelude::*;
 
// Our main datatype, `article`
 
#[derive(Serialize, Deserialize, ElasticType)]
struct Article {
    pub id: i32,
    pub title: String,
    pub content: Text<ContentMapping>,
    pub timestamp: Option<Date<EpochMillis, TimestampMapping>>,
    pub geoip: GeoIp
}
 
 
// A second datatype, `geoip`
 
#[derive(Serialize, Deserialize, ElasticType)]
struct GeoIp {
    pub ip: ::std::net::Ipv4Addr,
    pub loc: GeoPoint<DefaultGeoPointFormat>
}
 
 
// Mappings for our datatype fields
 
#[derive(Default)]
struct ContentMapping;
impl TextMapping for ContentMapping {
    fn analyzer() -> Option<&'static str> {
        Some("content_text")
    }
}
 
#[derive(Default)]
struct TimestampMapping;
impl DateMapping for TimestampMapping {
    type Format = EpochMillis;
    
    fn null_value() -> Option<Date<EpochMillis, Self>> {
        Some(Date::now())
    }
}
 
fn main() {
    println!("\"{}\":{{ {} }}", 
        Article::name(), 
        TypeMapper::to_string(Article::mapping()).unwrap()
    );
}Run

The above example defines a struct called Article with a few fields:

A default integer field called id
A default string field called title
A text field with a custom analyser called content
A date field with the epoch_millis format that defaults to the time the index was created called timestamp
An object field called GeoIp with default ip and geo_point fields.

Go ahead and run that sample and see what it outputs. In case you're interested, it'll look something like this (minus the whitespace):

"article": { 
    "properties": {
        "id":{
            "type": "integer"
        },
        "title": {
            "type":"text",
            "fields": {
                "keyword": {
                    "type": "keyword",
                    "ignore_above": 256
                }
            }
        },
        "content": {
            "type": "text",
            "analyzer": "content_text"
        },
        "timestamp": {
            "type": "date",
            "format": "epoch_millis",
            "null_value": "1435935302478"
        },
        "geoip": {
            "type": "nested",
            "properties": {
                "ip": {
                    "type": "ip"
                },
                "loc": {
                    "type": "geo_point"
                }
            }
        }
    }
}Run

The mapping is constructed by inspecting the type parameters of the fields on Article and GeoIp. This mapping is then serialised by serde.

Types

Types in Elasticsearch are a combination of source and mapping. The source is the data (like 42 or "my string") and the mapping is metadata about how to interpret and use the data (like the format of a date string).

The approach elastic_types takes to types is to bundle the mapping up as a Zero Sized Type, which is then bound to a field type as a generic parameter. For example:

ElasticBoolean<MyMapping>Run

The source type is boolean and the mapping is MyMapping.

All Elasticsearch types implement the base ElasticType<M: ElasticFieldMapping<F>, F> trait where M is the mapping and F is a type-specific format.

The following table illustrates the types provided by elastic_types:

Elasticsearch Type	Rust Type (Default Mapping)	Crate	Rust Type (Custom Mapping)	Format Type
`object`	-	-	type implementing `ElasticType<ObjectMapping>`	-
`integer`	`i32`	`std`	`Integer<M>`	-
`long`	`i64`	`std`	`Long<M>`	-
`short`	`i16`	`std`	`Short<M>`	-
`byte`	`i8`	`std`	`Byte<M>`	-
`float`	`f32`	`std`	`Float<M>`	-
`double`	`f64`	`std`	`Double<M>`	-
`keyword`	-	-	`Keyword<M>`	-
`text`	`String`	`std`	`Text<M>`	-
`boolean`	`bool`	`std`	`Boolean<M>`	-
`ip`	`Ipv4Addr`	`std`	`Ip<M>`	-
`date`	`DateTime<UTC>`	`chrono`	`Date<F, M>`	`DateFormat`
`geo_point`	`Point`	`geo`	`GeoPoint<F, M>`	`GeoPointFormat`
`geo_shape`	-	`geojson`	`GeoShape<M>`	-

Mapping

Having the mapping available at compile-time captures the fact that a mapping is static and tied to the data type.

Where there's a std type that's equivalent to an Elasticsearch type (like i32 for integer), a default mapping is implemented for that type. That means you can use primitives in your structs and have them mapped to the correct type in Elasticsearch. If you want to provide your own mapping for a std type, there's also a struct provided by elastic_types that wraps the std type but also takes an explicit mapping (like Integer which implements Deref<Target = i32>).

Where there isn't a std type available (like date), an external crate is used and an implementation of that type is provided (like Date, which implements Deref<Target = chrono::DateTime<UTC>>).

Formats

For some types (like Date), it's helpful to have an extra generic parameter that describes the way the data can be interpreted. For most types the format isn't exposed, because there aren't any alternative formats available. This is a particularly helpful feature for serialisation.

Links

Reexports

pub extern crate chrono;

pub extern crate geo as georust;

pub extern crate geojson;

Modules

boolean	Implementation of the Elasticsearch `boolean` types.
date	Implementation of the Elasticsearch `date` type.
geo	Implementation of the Elasticsearch `geo` types.
ip	Implementation of the Elasticsearch `boolean` type.
mappers	Helper mappers for `ElasticType`.
mapping	Base requirements for type mappings.
number	Implementation of the Elasticsearch `number` types.
object	Requirements for mapping `user-defined` types.
prelude	Includes all data types.
string	Implementation of the Elasticsearch `keyword` and `text` types.
template	Requirements for creating an index template for predefined mapping types.

Macros

date_fmt

Implement DateFormat for the given type.