Learn how to perform server-side operations using GraphQL with a complete reference implementation that uses the MySQL database.
In this guide we will develop an Olympic Medals application that demonstrates how to integrate a GraphQL endpoint with AG Grid's Server-Side Row Model. Specifically it will show how data can be lazy-loaded as required, even when performing group, filter, sort operations when working with large datasets.
The reference implementation covered in this guide is for demonstration purposes only. If you use this in production it comes with no warranty or support.
The source code can be found here: https://github.com/ag-grid/ag-grid-server-side-graphql-example.
Overview
In recent years GraphQL has become a popular alternative to REST when fetching data for clients. Familiarity with GraphQL is assumed, however this Introduction to GraphQL should provide all the necessary background information to follow this guide.
One of the main benefits of GraphQL is the ability to expose a single endpoint and schema which maps to numerous data sources. However in our Olympic Medals application we will keep things simple by using just a single MySQL datasource.
In our application, the GraphQL endpoint will be hosted using a web server comprised of Node.js running Express.js. An overview of technologies used in this guide is illustrated in the diagram below:
We will now proceed to install and run the application before going through the implementation details.
Download and Install
Clone the example project using:
git clone https://github.com/ag-grid/ag-grid-server-side-graphql-example.git
Navigate into the project directory:
cd ag-grid-server-side-graphql-example
Install project dependencies and build project using:
yarn install
Database Setup
Download and install the database as per the MySQL Download documentation.
Create a database with the name 'sample_data'
. Then run the following script to create the table olympic_winners
and populate it with data via the MySQL command line:
mysql -u root -p -D sample_data < ./data/olympic_winners.sql
That's it! We are now ready to run and explore the application.
Running the application
To run the application execute the following from the command line:
yarn start
Then point your browser to http://localhost:4000/
Defining the GraphQL schema
To keep things simple, our schema will just contain a single entity OlympicWinner
.
// server/schema.js
type OlympicWinner {
athlete: String
country: String
age: Int
sport: String
year: Int
gold: Int
silver: Int
bronze: Int
}
A single rows
query is also defined along with its supported input types and enums:
// server/schema.js
type Query {
rows(
startRow: Int,
endRow: Int,
sorting: [SortModel],
rowGroups: [RowGroup],
groupKeys: [String]
): [OlympicWinner]!
}
input SortModel {
colId: String
sort: String
}
input RowGroup {
colId: String
aggFunc: String
}
The input types defined in the schema directly map to the IServerSideGetRowsRequest. We will discuss these mappings in detail in the following sections.
The corresponding rows
resolver function is implemented as follows:
// server/schema.js
import { fetchRows } from './olympicService';
const resolvers = {
Query: {
rows: (obj, args) =>
new Promise((resolve, reject) => {
const resultCallback = (err, results) => err ? reject(err) : resolve(results);
fetchRows(args, resultCallback);
}).then(rows => rows)
},
};
The OlympicService
simply takes the query arguments and uses dynamic SQL techniques to construct the corresponding SQL queries. The implementation details will be omitted from this guide but can be examined in the project repository.
The GraphQL schema is created using the makeExecutableSchema
helper function from the graphql-tools
package, by combining the schema typeDefs
along with the corresponding resolvers
package as follows:
// server/schema.js
const schema = makeExecutableSchema({
typeDefs,
resolvers,
});
export default schema;
GraphQL Endpoint
Hosting our GraphQL endpoint is done with the help of the express-graphql
npm package. It is supplied with the schema we defined above.
// server/server.js
import express from 'express';
import graphqlHTTP from 'express-graphql';
import schema from './schema';
const app = express();
app.use('/graphql', graphqlHTTP({ schema: schema, graphiql: true }));
app.listen(4000, () => {
console.log('Started on localhost:4000');
});
Notice that we have supplied the option: graphiql: true
to enable the GraphiQL client, which is a useful tool for testing queries during development, and is available at: http://localhost:4000/graphql.
Server-Side Datasource
In order to fetch data for the Server-Side Row Model we must implement the IServerSideDatasource
, which contains a single method getRows(params)
which accepts request params from the grid.
To retrieve data from our GraphQL endpoint we will use the Apollo client. The response is then passed back to the grid via the params.successCallback(rows, lastRow)
as shown below:
// client/serverSideDatasource.js
class ServerSideDatasource {
constructor(gridOptions) {
this.gridOptions = gridOptions;
this.client = new ApolloClient({ uri: 'http://localhost:4000/graphql/' });
}
getRows(params) {
const columns = this.gridOptions.columnDefs;
// query GraphQL endpoint
this.client.query(query(params.request, columns))
.then(response => {
const rows = response.data.rows;
// determine last row to size scrollbar and last block size correctly
let lastRow = -1;
if (rows.length <= this.gridOptions.cacheBlockSize) {
lastRow = params.request.startRow + rows.length;
}
// pass results to grid
params.successCallback(rows, lastRow);
})
.catch(err => {
console.error(err);
params.failCallback()
});
}
}
The IServerSideGetRowsRequest
supplied in the params
is simply mapped to our GraphQL queries input params as shown below:
// client/serverSideDatasource.js
const query = (request, columns) => {
return {
query: gql`
query GetRows(\$start: Int, \$end: Int, \$sortModel: [SortModel], \$groups: [RowGroup], \$groupKeys: [String]) {
rows(
startRow: \$start,
endRow: \$end,
sorting: \$sortModel,
rowGroups: \$groups,
groupKeys: \$groupKeys
) {
\${getFields(columns)}
}
}
`,
variables: {
start: request.startRow,
end: request.endRow,
sortModel: mapSortModel(request),
groups: mapGroups(request),
groupKeys: mapGroupKeys(request)
},
}
};
const getFields = columnDefs => {
return columnDefs.map(colDef => colDef.field).join();
};
const mapGroups = request => {
return request.rowGroupCols.map(grp => {
return { colId: grp.field }
});
};
const mapGroupKeys = request => {
return request.groupKeys.map(key => key.toString());
};
const mapSortModel = request => {
return request.sortModel.map(srt => {
return { colId: srt.colId, sort: srt.sort }
});
};
Note that we are using the Apollo graphql-tag package to help create the GraphQL AST.
The ServerSideDatasource
is then registered with the grid via the grid API as follows:
// client/index.js
const datasource = new ServerSideDatasource(gridOptions);
api.setGridOption('serverSideDatasource', datasource);
Conclusion
In this guide we presented a reference implementation for integrating the Server-Side Row Model with GraphQL server hosted in Node and connected to a MySQL database. This included all necessary configuration and install instructions.
A high level overview was given to illustrate the problem this approach solves before providing details of how to achieve the following server-side operations:
- Infinite Scrolling
- Sorting
- Grouping