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Quickstart: A Tutorial Introduction to Rest.li
In this tutorial, we’ll take a first look at Rest.li and learn about some of its most basic features. We’ll construct a server that dispenses “Fortune Cookies” in response to GET requests and also create a client that sends a request to the server and prints a fortune returned by the server.
Rest.li uses an “inversion of control” model in which Rest.li defines the client and server architecture and handles many details of constructing, receiving, and processing RESTful requests. On the server-side, Rest.li calls your code at the appropriate time to respond to requests. You only need to worry about your application-specific response to requests. On the client side, Rest.li helps send type-safe requests to the server, and receives type-safe responses.
To allow Rest.li to perform its tasks, you need to conform to a simple architecture, in which you define a schema for your data, and classes that support REST operations on that data. Your classes will designate handlers for REST operations using Annotations, and return objects that represent your data schema. Rest.li will handle pretty much everything else.
We’ll see how Rest.li helps you perform these actions via automatic code generation, supporting base classes and other infrastructure.
Note: You will notice references to “Pegasus” in various places as you work through this tutorial and read other Rest.li documents. Pegasus is the code name for the project that includes Rest.li and some related modules and is used in some package names.
If you like to do things yourself, you should be able to enter the code in this tutorial into whatever editor you like and construct each step of the process. You can also follow along using the ready-made source directory, in the source repository under the example-standalone-app
directory. Using the provided source tree frees you from worrying about the build scripts and directory structure until you want to use Rest.li in your own projects.
The example can be built using gradle. Many of the steps involve code generation that is automated by gradle plugins provided as part of Rest.li. We’ll show you the basic build scripts you need for this example as we go along. For more details about the build process see Build Tool Integration.
Before we get started, you’ll need to create a basic directory structure to hold your classes. At the root of the example source tree, you should have three sub-directories, api/
, client/
and server/
.
You also need a top level build.gradle file and a settings.gradle.
The file settings.gradle just includes the build scripts for each sub-project:
The file build.gradle should contain:
apply plugin: 'idea'
apply plugin: 'eclipse'
pegasusVersion = "1.7.0"
spec = [
"product" : [
"pegasus" : [
"data" : "com.linkedin.pegasus:data:"+pegasusVersion,
"generator" : "com.linkedin.pegasus:generator:"+pegasusVersion,
"restliClient" : "com.linkedin.pegasus:restli-client:"+pegasusVersion,
"restliServer" : "com.linkedin.pegasus:restli-server:"+pegasusVersion,
"restliTools" : "com.linkedin.pegasus:restli-tools:"+pegasusVersion,
"pegasusCommon" : "com.linkedin.pegasus:pegasus-common:"+pegasusVersion,
"restliCommon" : "com.linkedin.pegasus:restli-common:"+pegasusVersion,
"r2" : "com.linkedin.pegasus:r2:"+pegasusVersion,
"r2Jetty" : "com.linkedin.pegasus:r2-jetty:"+pegasusVersion
]
]
]
buildscript {
repositories {
mavenLocal()
mavenCentral()
maven {
url "https://oss.sonatype.org/content/repositories/comlinkedin-461/"
}
}
dependencies {
classpath group: 'com.linkedin.pegasus', name: 'gradle-plugins', version: '1.7.0'
}
}
subprojects {
apply plugin: 'eclipse'
apply plugin: 'maven'
apply plugin: 'idea'
apply plugin: 'eclipse'
sourceCompatibility = JavaVersion.VERSION_1_6
repositories {
mavenLocal()
mavenCentral()
maven {
url "https://oss.sonatype.org/content/repositories/comlinkedin-461/"
}
}
}
This gradle build file pulls all required jars from a global Maven repository. It also loads some plugins that facilitate the build process and various code generation steps. Notice that plugins are also provided for IntelliJ Idea and Eclipse. For example, executing
gradle idea
will generate an Idea project ready to open in Idea. Using Idea of Eclipse is a handy way to explore and follow along as you read this tutorial.
Here’s how the structure of your top-level project should look as we begin:
-
example-standalone-app/
- build.gradle
- settings.gradle
- api/
- client/
- server/
The first thing we will do is implement a very simple server that responds to GET requests.
The basic steps you will follow to create a Rest.li server are:
- Define your data schema – Rest.li uses an Avro-like format known as Pegasus Data Schema.
Rest.li will generate java classes that correspond to this data schema, to be used
by your server.
- Implement Resource classes that implement REST operations and act on your data.
Rest.li provides a set of base classes and Annotations that map the
methods of your class to URIs and REST operations
- Create an HTTP server that instantiates a Rest.li server.
The Rest.li server will automatically locate your Resource classes and invoke
the appropriate methods when a request is received.
Rest.li provides tools to make these steps simple, including code generators that create classes from the data schema, base classes, and annotations that map entry points in your code to REST operations.
Let’s walk through each step of the process.
The first step in creating a Rest.li service is to define a data model or schema for the data that will be returned by your server. We will define the data model in the api
directory, which serves to define the API or interface between the server and clients.
All Rest.li data models are defined in Pegasus Data Schema files, which have a .pdsc suffix. We’ll define a Fortune data model in Fortune.pdsc. The location of this file is important, be sure to place it in a path corresponding to your namespace, under api/src/main/pegasus/
{
"type": "record",
"name": "Fortune",
"namespace": "com.example.fortune",
"doc": "Generate a fortune cookie",
"fields": [{"name": "fortune","type": "string","doc": "The Fortune cookie string"}]
}
Fortune.pdsc defines a record named Fortune, with an associated namespace. The record has a single field, d a string whose name is “fortune”. Fields as well as the record itself can have optional documentation strings. This is, of course, a very simple schema. See Data Schema and Templates for details on the Pegasus Data Schema for details on the syntax and more complex examples.
Rest.li uses the data model in .pdsc files to generate java versions of the model that can be used by the server. The easiest way to generate these classes is to use the gradle integration provided as part of Rest.li. You will need a build.gradle file in the api
directory that looks like this:
apply plugin: 'pegasus'
apply plugin: 'java'
dependencies {
compile spec.product.pegasus.restliClient
dataTemplateCompile spec.product.pegasus.data
dataTemplateGenerator spec.product.pegasus.generator
restClientCompile spec.product.pegasus.restliClient
restTools spec.product.pegasus.restliTools
}
With the Fortune.pdsc file and build.gradle in place, you can generate a java binding for the data model. This java version is what will actually be used by your server to return data to calling clients. Change into the api
directory in the example-standalone-server and run the command:
gradle build
The pegasus
gradle plugin will detect the presence of Fortune.pdsc and use the `dataTemplateGenerator` to generate Fortune.java, and place it in a mainGeneratedDataTemplate
directory under the api/src/
directory.
Your file system structure should now look like this:
-
example-standalone-app/
-
api/
-
src/
-
main/
-
pegasus/
-
com/
-
example/
-
fortune/
- Fortune.pdsc
-
fortune/
-
example/
-
com/
-
pegasus/
-
mainGeneratedDataTemplate/
-
java/
-
com/
-
example/
-
fortune/
- Fortune.java
-
fortune/
-
example/
-
com/
-
java/
-
main/
-
src/
- client/
- server/
-
api/
The generated java file contains a java representation of the data model defined in the schema, and includes get
and set
methods for each element of the model, as well as other supporting methods. You can look at the generated file to see the full implementation if you are curious; the following excerpt should give you the general idea. This class is entirely derived from your data model and should not be modified.
file: example-standalone-app/api/src/main/mainGeneratedTemplate/java/com/example/fortune/Fortune.java
@Generated(...)
public class Fortune
extends RecordTemplate
{
// other methods ...
/**
* Getter for fortune
*
* @see Fields#fortune
*/
public String getFortune() {
return getFortune(GetMode.STRICT);
}
/**
* Setter for fortune
*
* @see Fields#fortune
*/
public Fortune setFortune(String value) {
putDirect(FIELD_Fortune, String.class, String.class, value, SetMode.DISALLOW_NULL);
return this;
}
// other methods ...Rest.li-User-Guide
}
Now that we have defined our data model, the next step is to define a ‘resource’ class that will be invoked by the Rest.li server in response to requests from clients. We’ll create a class named FortunesResource. This class is written by hand, and implements any REST operations you want to support, returning data using the java data model class generated in the previous step. The file should be placed according to your package path under server/src/main/java
package com.example.fortune.impl;
import com.linkedin.restli.server.annotations.RestLiCollection;
import com.linkedin.restli.server.resources.CollectionResourceTemplate;
import com.example.fortune.Fortune;
import java.util.HashMap;
import java.util.Map;
/**
* Very simple Rest.li Resource that serves up a fortune cookie.
*/
@RestLiCollection(name = "fortunes", namespace = "com.example.fortune")
public class FortunesResource extends CollectionResourceTemplate<Long, Fortune>
{
// Create trivial db for fortunes
static Map<Long, String> fortunes = new HashMap<Long, String>();
static {
fortunes.put(1L, "Today is your lucky day.");
fortunes.put(2L, "There's no time like the present.");
fortunes.put(3L, "Don't worry, be happy.");
}
@Override
public Fortune get(Long key)
{
// Retrieve the requested fortune
String fortune = fortunes.get(key);
if(fortune == null)
fortune = "Your luck has run out. No fortune for id="+key;
// return an object that represents the fortune cookie
return new Fortune().setId(key).setFortune(fortune);
}
}
FortunesResource extends a Rest.li class, CollectionResourceTemplate and, for this simple example, overrides a single method, get
, which takes a single argument, an id of a resource to be returned. Rest.li will call this method when it dispatches a GET request to the Fortune resource. Additional REST operations could be provided by overriding other methods. See the Rest.li User Guide for more details about supporting additional REST methods and other types of resources.
The RestLiCollection
annotation at the top of the file marks this class as a REST collection, and declares that this resource handles the /fortunes
URI. The result is that calling http://localhost/fortunes/ (assuming your server is running on localhost) will call FortunesResource.get()
, which should return a Fortune object corresponding to the given id
. For this simple implementation, we will create a static HashMap that maps several fortune strings to ids. If a requested id is found in the HashMap, we will construct a Fortune
object, set the message and id, and return the object. If the requested id is not found, we’ll return a default message. Rest.li will handle delivering the result to the calling client as a Json object. (Recall that Fortune.java was generated in a previous step and is found under the api
directory)
In a real implementation, you would, of course, perform whatever steps are required to retrieve or construct your response to the request, but ultimately, you will return an instance of your data model class that represents the data defines in your schema.
We’ve now completed the bulk of our application-specific server-side code. We’ve defined our data model, and implemented a Resource class that can respond to a GET request by returning data according to the model. The only thing remaining is to implement a server to call our application logic. Rest.li provides a class RestLiServer, which handles dispatching of requests to your Resource classes. Rest.li also includes a Request Response layer (R2) that provides a transport abstraction and other services. The RestLiFortunesServer found in example-standalone-app/server/src/main/java/com.example.fortune/
is an extremely simple example that leverages R2 and the RestLiServer class to implement a server that can route requests to our FortunesResource class.
Notice that RestLiServer automatically scans all resource classes in the specified package and initializes the REST endpoints/routes without any hard-coded connection. Adding additional resources or operations can be done simply by expanding your data schema and providing additional functionality in your Resource class(es).
package com.example.fortune;
import com.linkedin.r2.transport.http.server.HttpServer;
import com.linkedin.r2.transport.http.server.HttpServerFactory;
import com.linkedin.restli.server.DelegatingTransportDispatcher;
import com.linkedin.restli.server.RestLiConfig;
import com.linkedin.restli.server.RestLiServer;
public class RestLiFortunesServer
{
public static void main(String[] args) throws Exception
{
// Create a config that supplies the path to our Resources.
// Resources will be loaded and used automatically
RestLiConfig config = new RestLiConfig();
config.addResourcePackageNames("com.example.fortune.impl");
// Create and run an HTTP server on port 7279 for the RestLiServer
HttpServer server = new HttpServerFactory()
.createServer(7279,
new DelegatingTransportDispatcher(new RestLiServer(config)));
server.start();
System.out.println("Fortune server running on port 7279 Press any key to stop.");
System.in.read();
server.stop();
}
}
To compile and run the server, we need a build.gradle
file in the server directory, which should look like this:
apply plugin: 'java'
apply plugin: 'pegasus'
ext.apiProject = project(':api')
pegasus.main.idlOptions.addIdlItem(['com.example.fortune.impl'])
dependencies {
compile project(path: ':api', configuration: 'dataTemplate')
compile spec.product.pegasus.r2
compile spec.product.pegasus.r2Jetty
compile spec.product.pegasus.restliServer
compile spec.product.pegasus.restliCommon
compile spec.product.pegasus.pegasusCommon
restTools spec.product.pegasus.restliTools
// need to figure out why this is not already in the classpath..
compile files("${System.properties['java.home']}/../lib/tools.jar")
}
task startFortunesServer(type: JavaExec) {
main = 'com.example.fortune.RestLiFortunesServer'
classpath = sourceSets.main.runtimeClasspath
standardInput = System.in
}
Also create a gradle.properties file, containing the following line:
rest.model.compatibility=off
This prevents some checks on generated files that you will want in place in a real project, but that complicate the development process for this simple example.
With these files in place, your server directory structure should look like this:
-
example-standalone-app/
- api/ …
- client/
-
server/
- build.gradle
- gradle.properties
-
src/
-
main/
-
java/
-
com/
-
example/
-
fortune/
- RestLiFortunesServer.java
-
impl/
- FortunesResource.java
-
fortune/
-
example/
-
com/
-
java/
-
main/
Now you can build the server from the /server
directory with:
gradle build
Note: If prompted, run the build command a second time. The first build runs a bootstrapping code generation process, requiring a second build to compile the generated code.
After building the server, you can launch it using gradle:
gradle startFortunesServer
Once the server is running, you can test using curl:
curl -v http://localhost:7279/fortunes/1
curl -v http://localhost:7279/fortunes/1
* About to connect() to localhost port 7279 (#0)
* Trying ::1... connected
* Connected to localhost (::1) port 7279 (#0)
> GET /fortunes/1 HTTP/1.1
> User-Agent: curl/7.19.7 (x86_64-redhat-linux-gnu) libcurl/7.19.7 NSS/3.12.9.0 zlib/1.2.3 libidn/1.18 libssh2/1.2.2
> Host: localhost:7279
> Accept: */*
>
< HTTP/1.1 200 OK
< X-LinkedIn-Type: com.example.fortune.Fortune
< Content-Type: application/json
< Content-Length: 45
< Server: Jetty(6.1.26)
<
* Connection #0 to host localhost left intact
* Closing connection #0
{"id":1,"fortune":"Today is your lucky day."}[
Here, curl issued a GET request for /fortunes/1. Rest.li routed the request to the FortunesResource, which interpreted the argument 1
, found the corresponding string, and constructed a Fortune object to return. Rest.li automatically transforms the java data model to Json and returns the result to the caller.
.h2 The Server’s Public Interface
Before we move on to look at the Rest.Li’s client support, notice that the process of building the server generated an additional file. If you look at your directory structure, you should see an IDL file under @server/src/mainGeneratedRest/*. The file is in Json format and defines the interface supported by the server. The interface is generated as a result of the annotations in the Resource class, in this example, FortunesResource.java
Here is the generated IDL. Notice that all of this information was derived from server’s FortunesResource.java, even the documentation string.
file: example-standalone-app/server/src/mainGeneratedRest/idl/com.example.fortune.fortunes.restspec.json
{
"name" : "fortune",
"namespace" : "com.example.fortune",
"path" : "/fortunes",
"schema" : "com.linkedin.restli.example.Fortune",
"doc" : "Very simple RestLi Resource that serves up a fortune cookie.\n\ngenerated from: com.example.fortune.impl.FortunesResource",
"collection" : {
"identifier" : {
"name" : "fortuneId",
"type" : "long"
},
"supports" : [ "get" ],
"methods" : [ {
"method" : "get"
} ],
"entity" : {
"path" : "/fortunes/{fortuneId}"
}
}
}
This file represents the contract between the server and the client. Accordingly, the build also copied the IDL to the api
module, where it can be accessed by the client code.
Just to verify that everything is in place, here how your project’s api/
and server/
structure should look at this point:
-
example-standalone-app/
-
api/
-
src/
-
main/
-
idl/
- com.example.fortune.fortunes.restspec.json
-
pegasus/
-
com/
-
example/
-
fortune/
- Fortune.pdsc
-
fortune/
-
example/
-
com/
-
idl/
-
mainGeneratedDataTemplate/
-
java/
-
com/
-
example/
-
fortune/
- Fortune.java
-
fortune/
-
example/
-
com/
-
java/
-
main/
-
src/
- client/
-
server/
- build.gradle
- gradle.properties
-
src/
-
main/
-
java/
-
com/
-
example/
-
fortune/
- RestLiFortunesServer.java
-
impl/
- FortunesResource.java
-
fortune/
-
example/
-
com/
-
java/
-
mainGeneratedRest/
- com.example.fortune.fortunes.restspec.json
-
main/
-
api/
Now that we have a server implemented and tested with curl, let’s see how we can use Rest.li to help build a client.
Rest.li uses the IDL published by the server to generate client classes that can be used to construct requests. The pegasus
gradle plugin provides tools to generate these classes. Let’s start by creating a build.gradle
file in the client
directory:
apply plugin: 'java'
apply plugin: 'pegasus'
dependencies {
compile project(path: ':api', configuration: 'restClient')
compile spec.product.pegasus.pegasusCommon
compile spec.product.pegasus.r2
compile spec.product.pegasus.restliClient
compile spec.product.pegasus.data
compile spec.product.pegasus.restliCommon
testCompile "commons-httpclient:commons-httpclient:3.1"
}
task startFortunesClient(type: JavaExec) {
main = 'com.example.fortune.RestLiFortunesClient'
classpath = sourceSets.main.runtimeClasspath
}
To generate the interface classes used by the client, change to the client
directory and type
gradle build
Building in the client directory generates java classes that represent the resources and operations on those resources supported by the server. These are basically convenience classes that help you create or “build” requests in a client. In this example, you should see two new java files, FortunesBuilders.java and FortunesGetBuilder.java. These files are placed in the api
directory, where they can be shared among multiple clients. FortunesBuilders is a factory class that instantiates the actual request builder. In this example, our Fortune server only supports GET requests, so the process has just generated a FortunesGetBuilder class. You can look at the generated source code under the api/src/mainGeneratedRest
directory, if you’re interested, but for this tutorial, let’s just go on to creating a client and see how a builder is used.
Creating a client involves using a few classes to handle connecting to the server, and using the Builder classes generated in the previous step to construct requests. Let’s see how that works before we look at the actual client code.
The following lines of code instantiate a FortunesBuilders factory, and then call its get()
method to create a FortunesGetBuilder object. Finally, the FortunesGetBuilder lets you supply the information needed in the request, and builds a Request object.
FortunesBuilders _fortunesBuilder = new FortunesBuilders();
FortunesGetBuilder getBuilder = _fortunesBuilder.get();
Request<Fortune> getReq = getBuilder.id(fortuneId).build();
The process of sending a request from a client basically consists of creating a RestClient object, and invoking its sendRequest() method to send a Request object to the server:
RestClient restClient = new RestClient(r2Client, "http://localhost:7279/");
ResponseFuture<Fortune> getFuture = restClient.sendRequest(getReq);
Response<Fortune> resp = getFuture.getResponse();
RestClient.sendRequest() returns a Future, which can be used to wait on and retrieve the response from the server. Note that the response is type-safe, and parametrized as type Fortune, so we can use the Fortune interface to retrieve results, like this:
String message = resp.getEntity().getFortune();
long id = resp.getEntity().getId();
Here is a completed RestLiFortunesClient class, which uses the R2 library to create the transport mechanisms. For this example, the client will just generate a random ID between 0 and 5, and print the response. This file should go in the client/
directory, under client/src/main/java/<package
package com.example.fortune;
import com.linkedin.common.callback.Callback;
import com.linkedin.common.callback.FutureCallback;
import com.linkedin.common.util.None;
import com.linkedin.r2.transport.common.Client;
import com.linkedin.r2.transport.common.bridge.client.TransportClient;
import com.linkedin.r2.transport.common.bridge.client.TransportClientAdapter;
import com.linkedin.r2.transport.http.client.HttpClientFactory;
import com.linkedin.restli.client.Request;
import com.linkedin.restli.client.Response;
import com.linkedin.restli.client.ResponseFuture;
import com.linkedin.restli.client.RestClient;
import com.example.fortune.FortunesBuilders;
import java.util.Collections;
public class RestLiFortunesClient
{
/**
* This stand-alone app demos the client-side Rest.li API.
* To see the demo, run RestLiFortunesServer, then start the client
*/
public static void main(String[] args) throws Exception
{
// Create an HttpClient and wrap it in an abstraction layer
final HttpClientFactory http = new HttpClientFactory();
final Client r2Client = new TransportClientAdapter(
http.getClient(Collections.<String, String>emptyMap()));
// Create a RestClient to talk to localhost:7279
RestClient restClient = new RestClient(r2Client, "http://localhost:7279/");
// Generate a random ID for a fortune cookie, in the range 0-5
long fortuneId = (long) (Math.random() * 5);
// Construct a request for the specified fortune
FortunesGetBuilder getBuilder = _fortuneBuilder.get();
Request<Fortune> getReq = getBuilder.id(fortuneId).build();
// Send the request and wait for a response
final ResponseFuture<Fortune> getFuture = restClient.sendRequest(getReq);
final Response<Fortune> resp = getFuture.getResponse();
// Print the response
System.out.println(resp.getEntity().getFortune());
// shutdown
restClient.shutdown(new FutureCallback<None>());
http.shutdown(new FutureCallback<None>());
}
private static final FortunesBuilders _fortuneBuilder = new FortunesBuilders();
}
With your client code in place, your directory structure should look like this:
-
example-standalone-app/
- api/ …
-
client/
- build.gradle
-
src/
-
java/
-
com/
-
example/
- fortune/
- RestLiFortunesClient.java
-
example/
-
com/
-
java/
- server/ …
Build the client by building in the client directory:
gradle build
To test our final client/server pair, start the server in one terminal window:
gradle startFortunesServer
Then in another window, run:
gradle startFortunesClient
You should see a “fortune cookie” printed out from the client before it exits.
If you want to inspect the request being sent by the client, stop the server, and run netcat
or another protocol sniffer to listen on post 7279, and run the client again:
netcat -l -p 7279
GET /fortunes/1 HTTP/1.1
Host: localhost:7279
X-LI-R2-W-MsgType: REST
Content-Length: 0
It’s relatively straightforward to run rest.li in any servlet container.
First, update /server/build.gradle, replacing the ‘java’ plugin with a ‘jetty’ (or ‘war’ if you don’t want jetty) plugin
//apply plugin: 'java'
apply plugin: 'jetty'
Next, add a server/src/main/java/com/example/fortune/RestliFortunesServlet.java file:
package com.example.fortune;
import java.io.*;
import javax.servlet.*;
import javax.servlet.http.*;
import com.linkedin.r2.transport.http.server.HttpServer;
import com.linkedin.r2.transport.http.server.HttpServerFactory;
import com.linkedin.restli.server.DelegatingTransportDispatcher;
import com.linkedin.restli.server.RestLiConfig;
import com.linkedin.restli.server.RestLiServer;
import com.linkedin.r2.transport.http.server.RAPServlet;
public class RestliFortunesServlet extends HttpServlet
{
private HttpServlet mServlet;
public void init(ServletConfig servletConfig) throws ServletException
{
super.init(servletConfig);
RestLiConfig config = new RestLiConfig();
config.addResourcePackageNames("com.example.fortune.impl");
// Create and run an HTTP server on port 7279 for the RestLiServer
mServlet = new RAPServlet(new DelegatingTransportDispatcher(new RestLiServer(config)));
mServlet.init(servletConfig);
}
public void destroy()
{
mServlet.destroy();
}
public void service(ServletRequest req, ServletResponse res) throws ServletException, IOException
{
mServlet.service(req, res);
}
}
And, lastly, add a ‘server/src/main/webapp/WEB-INF/web.xml’ file:
<web-app>
<display-name>Fortune Service</display-name>
<servlet>
<servlet-name>R2Servlet</servlet-name>
<servlet-class>com.example.fortune.RestliServlet</servlet-class>
<init-param>
<param-name>servlet</param-name>
<param-value>lin:restLiServlet</param-value>
</init-param>
<load-on-startup>1</load-on-startup>
</servlet>
<servlet-mapping>
<servlet-name>R2Servlet</servlet-name>
<url-pattern>/*</url-pattern>
</servlet-mapping>
</web-app>
We’ve now completed a quick tour of a few of the most basic features of Rest.li. Let’s review the steps we took to create a server and a corresponding client:
- Define a Data Model (Fortune.pdsc)
- Generate Java Record Templates (Rest.li creates Fortune.java)
- Create a Resource that responds to REST requests
(FortuneResource.java) by subclassing CollectionResourceTemplate and
using RestLiAnnotations to define operations and entry points - Write a server that locates our Resource classes and uses
RestLiServer to dispatch requests (RestLiFortuneServer) - Generate IDL (fortune.restpec.json) and java client bindings from
the server Resource file (FortunesBuilders.java and FortunesGetBuilder.java) - Create a client that uses RestClient to send requests constructed by
calling the Builder classes (RestLiFortuneClient.java)
Notice that (ignoring gradle build files) there are only four files in this
example that you had to create:
- The original Pegasus Data Model file (Fortune.pdsc)
- The server resource file (FortunesResource.java)
- The server (RestLiFortuneServer.java)
- The client (RestLiFortuneClient.java)
Although Rest.li has many more features that can be leveraged when creating the server and client, most of your focus will usually be on defining data models and implementing resource classes that provide and/or manipulate the data.
To learn more about Rest.li, proceed to the more complex examples in the source code, and read the Rest.li User’s Guide.
- Dynamic Discovery (D2)
- Data Schema and Templates
-
Rest.li
- Server
- Client
- Projections
- Tools
- FAQs