Shakir

Posted on Feb 17, 2023 • Updated on Feb 18, 2023

Query HarperDB's REST API via Apollo GraphQL

#apolloserver #graphql #harperdb #rest

Introduction

Hi there 👋, in this post, we shall launch an Apollo server with node, and perform some read & write operations from the Apollo studio sandbox to a HarperDB instance. Having some graphql fundamentals would be beneficial to understand better, though some parts of the code would be explained.

Studio

I have an account in HarperDB studio and have setup an organisation and a free trier instance there. Once logged in to the instance, the config tab would give the instance credentials we would need to connect from our code.

Note that the studio credentials(email/password) are different from the instance credentials(username/password). You can have more than one instance in the studio. You can have only one free tier instance though across organisations.

Copy the instance url and the basic token from the config shown in the image above, as we would need those while sending API calls.

Clone

Clone the code from GitHub.

$ git clone git@github.com:networkandcode/fruits-apollo-hdb.git

Dependencies

The dependencies for the code are as follows.

  "dependencies": {
    "@apollo/datasource-rest": "^5.0.2",
    "@apollo/server": "^4.3.3",
    "dotenv": "^16.0.3",
    "graphql": "^16.6.0"
  }

We can install these.

$ npm i

About the packages above:

@apollo/datasource-rest is used to make rest api calls from apollo to endpoints such as HarperDB's instance url.
@apollo/server is used to launch the apollo server itself.
dotenv is used to read env vars.
graphql is the core graphql library.

You may refer to this guide for more info.

Variable

Add an .env file, we just need one variable.

$ cat .env
HDB_INSTANCE_URL=https://<instance-name>.harperdbcloud.com

Start

There is a start script with invokes the index file.

$ cat package.json| grep start
    "start": "node index.js"

Good to start the server

$ npm start

> server@1.0.0 start
> node index.js

🚀  Server ready at: http://localhost:4000/

Apollo studio

Once the server is started we should be able to see the sandbox studio on the browser at http://localhost:4000/.

Token

Let's set the authorisation header, you may paste the basic token obtained from HarperDB studio here.

We are setting this token in the server context.

    const token = req.headers.authorization;

Which would be passed to HarperDB while the REST API call is being made.

    willSendRequest(_path, request) {
      request.headers['authorization'] = this.token;
    };

Code

Let's see what code files we have and their purpose.

$ ls *.js
datasource.js   index.js        resolvers.js    schema.js

datasource.js is where we are making calls to HarperDB via REST API.
index.js has code that wraps the schema and resolvers in the server and starts it.
resolvers.js contains resolvers that resolves all of the queries and mutations defined in schema.js by sending calls to HarperDB API defined in datasource.js
schema.js contains our graphql schema that has built in types Query and Mutation as well as other user defined types and inputs.

Schema

Our graphql schema is a collection of type definitions. And hence it's common to use typeDefs as our schema variable.

$ cat schema.js 
const typeDefs = `
  input CreateTableBody {
    schema: String!
    table: String!
    hash_attribute: String!
  }

  input FruitInput {
    name: String!
    "calories per 100 gm"
    calories: Int!
  }

  type Query {
    fruits(schema: String!, table: String!): [Fruit]
    fruit(schema: String!, table: String!, name: String!): [Fruit]
  }

  type Mutation {
    createSchema(schema: String!): ApiResponse!
    createTable(body: CreateTableBody!): ApiResponse!
    insertRecords(schema: String!, table: String!, records: [FruitInput!]! ): ApiResponse!
  }

  type Fruit {
    id: ID!
    name: String!
    calories: Int!
  }

  type ApiResponse {
    status: Int!
    message: String!
  }
`;

export default typeDefs;

In the schema, there are two built in types Query and Mutation. Query is meant for read operations where as Mutation refers to operations that involve create, update or deletion of data.

In Query, we have defined two fields fruits and fruit. fruits takes two arguments schema and table, both are strings and are mandatory or non nullable as denoted with !. Both fruits and fruit fields return same type of data denoted by [Fruit], this indicates an array of records, where each record is of type Fruit, this is not a built in type like String or Int, hence we have defined it as type Fruit. The type definition for Fruit denotes it’s structure, it would have three fields id, name and calories which are of types ID, String and Int respectively, and all 3 fields are non nullable. To summarise, we can have two Query operations one is fruits and the other is fruit both return a list of fruits(records from HarperDB).

Like wise for Mutation, we have three fields createSchema, createTable and insertRecords with their respective arguments, and all of them would return the same type of response as denoted by ApiResponse, that would have only 2 fields status and message.

Note that when a field type is not built in, we would define it with type, like we have defined type Fruit and type ApiResponse in our schema. Likewise, when an argument type is not built in, we would delete it with input, like we have defined input CreateTableBody and FruitInput in our schema.

Datasource

Here, we create a new class by name HdpApi that inherits from RESTDataSource. Note that we obtain the baseURL from the env var.

The willSendRequest function is used to add the header while calls are being sent to the base url. There are just two functions we are defining here, as in HarperDB all the calls are of type POST, and there mainly two types of calls, one that sends SQL style statements and the other which they call as NoSQL operations.

$ cat datasource.js 
import { RESTDataSource } from '@apollo/datasource-rest'; 

class HdbApi extends RESTDataSource {
    baseURL = process.env.HDB_INSTANCE_URL;

    constructor(options) {
      super(options);
      this.token = options.token;
    };

    async sqlQuery(body) {
      // for read operations
      return await this.post(
        '',
        {
          body,
        }
      ).then((res) => {
        return res;
      })
    };

    async noSqlQuery(body) {
      return await this.post(
        '',
        {
          body,
        }
      ).then((res) => {
        const { message } = res;
        return {
          status: 200,
          message
        }
      }).catch((err) => {
        const { status, body } = err.extensions.response;
        const message = body.error;

        return {
          status,
          message
        }
      });
    };

    willSendRequest(_path, request) {
      request.headers['authorization'] = this.token;
    };

  };

  export default HdbApi;

Index

In the index file, we import the modules first. And then, we import the schema, resolvers and our datasource. We use dotenv to read the var defines in .env.

We then create an Apollo server instance that takes two arguments: schema and resolvers.

We start the server finally, and we give options such as the listening port, and the context.

$ cat index.js 
import { ApolloServer } from '@apollo/server';
import { startStandaloneServer } from '@apollo/server/standalone';
import dotenv from 'dotenv';

import typeDefs from './schema.js';
import resolvers from './resolvers.js';
import HdbApi from './datasource.js';

dotenv.config();
console.log(process.env)

const server = new ApolloServer({
  typeDefs,
  resolvers,
});

const { url } = await startStandaloneServer(server, {
  listen: { port: 4000 },
  context: async({ req }) => {
    const { cache } = server;
    const token = req.headers.authorization;
    return {
      dataSources: {
        hdbApi: new HdbApi({ cache, token }),
      }
    }
  }
});

console.log(`🚀  Server ready at: ${url}`);

The context returns a dataSources dictionary that has a hdpApi key in it, and this points to a new HdpApi object which is defined in the datasource.

We can refer to this context in the resolvers.

Resolvers

There are 2 main resolvers for the built in types Query and Mutation. Inside each resolver, we have a function for each field inside the type. In our schema we have defines two types fruits and fruit, hence there are two such functions inside the Query resolver too. Similarly we have three functions for the Mutations: createSchema, createTable and insertRecords.

What these functions return will come as the result in the Apollo Studio for our GraphQL operation. The return statements are referring to contextValue which is the context function we defined in index. So, the resolvers are able to use the context defined in the server, which subsequently points to the api calls we defined in the datasource.

Note that there are four arguments for each function: parent, args, contextValue and info. We would only need the 2nd and 3rd args for this exercise though. We have already seen about contextValue above, and args refer to the variables we set while running an operation in the Apollo studio.

$ cat resolvers.js 
const resolvers = {
    Query: {
      fruits: (_, args, contextValue) => {
        const { schema, table } = args;
        const body = {
          "operation": "sql",
          "sql": `SELECT * FROM ${schema}.${table}`,
        }

        return contextValue.dataSources.hdbApi.sqlQuery(body);
      },
      fruit: (_, args, contextValue) => {
        const { schema, table, name } = args;
        const body = {
          "operation": "sql",
          "sql": `SELECT * FROM ${schema}.${table} where name = "${name}"`
        };

        return contextValue.dataSources.hdbApi.sqlQuery(body);
      },
    },
    Mutation: {
      // There are four args parent, args, contextValue and info
      createSchema: (_, { schema }, contextValue) => {
        const body = {
          operation: "create_schema",
          schema,
        };

        return contextValue.dataSources.hdbApi.noSqlQuery(body);
      },
      createTable: (parent, { body }, contextValue, info) => {
        body = {
          ...body,
          operation: "create_table",
        }

        return contextValue.dataSources.hdbApi.noSqlQuery(body);
      },
      insertRecords: (parent, { schema, table, records }, contextValue, info) => {
        const body = {
          operation: "insert",
          schema,
          table,
          records
        }

        return contextValue.dataSources.hdbApi.noSqlQuery(body);
      }
    }
  };

  export default resolvers;

Operations

Ok so all the setup is done. We are good to go with the Query / Mutation operations. Let's start with Mutations.

Create schema

Let's try creating a schema in HarperDB with the mutation in Apollo GraphQl. Make a note that this schema is not the GraphQL schema, it's the schema in HarperDB.

Building the operation and variables is easy, you just need to click on the plus sign next to the operation and field.

We can validate this in the browse section of HarperDB studio.

If we try to run the mutation again on Apollo studio, we should see an error message that says the schema already exists.

Create table

The schema is created, we can now try to add a table in this schema.

The operation is ready however we need to fill the data for the body variable, for which we can click on the argument.

We should be able to see all the input data fields defined for the argument. We can add them all with the plus button.

The variable should be populated for us with null fields.

We can replace null with the actual values.

We can run the operation and see the response.

If you try again, you should see an error message.

Add entries to table

The operation in this case would be:

mutation Mutation($schema: String!, $table: String!, $records: [FruitInput!]!) {
  insertRecords(schema: $schema, table: $table, records: $records) {
    message
    status
  }
}

The variables would be:

  "schema": "myschema",
  "table": "fruits",
  "records": [
    {
      "name": "Apple",
      "calories": 52
    },
    {
      "name": "Banana",
      "calories": 89
    }
  ]
}

And the response as follows, after running the mutation:

{
  "data": {
    "insertRecords": {
      "message": "inserted 2 of 2 records",
      "status": 200
    }
  }
}

Retrieve records

Let's try a query operation this time, for retrieving all records from the table.

The operation is:

query Fruits($schema: String!, $table: String!) {
  fruits(schema: $schema, table: $table) {
    calories
    id
    name
  }
}

The variables are:

{
  "schema": "myschema",
  "table": "fruits"
}

And the result of the query operation would be:

{
  "data": {
    "fruits": [
      {
        "calories": 52,
        "id": "3963a29c-d696-44ae-a3d8-e11de48bf339",
        "name": "Apple"
      },
      {
        "calories": 89,
        "id": "eec06bc5-85cf-48eb-87d2-89a25fd9f3c1",
        "name": "Banana"
      }
    ]
  }
}

Retrieve selective records

And one final query to retrieve selective records.
The query is:

query Query($schema: String!, $table: String!, $name: String!) {
  fruit(schema: $schema, table: $table, name: $name) {
    calories
    id
    name
  }
}

Variables:

{
  "schema": "myschema",
  "table": "fruits",
  "name": "Apple"
}

And result of the query:

{
  "data": {
    "fruit": [
      {
        "calories": 52,
        "id": "3963a29c-d696-44ae-a3d8-e11de48bf339",
        "name": "Apple"
      }
    ]
  }
}

Summary

Thus we were able to access the Apollo studio on the browser and send queries and mutations to HarperDB. HarperDB is considering GraphQL functionality on their roadmap. Check out their Feedback Board and give it an upvote if you think it would be helpful!

Feel free to ask questions if the flow is not clear, and correct if there are any mistakes. Thank you for reading !!!

Image credit: unsplash

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