Tutorial: Amazon OpenSearch Service Resolvers - Amazon AppSync
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Tutorial: Amazon OpenSearch Service Resolvers

Amazon AppSync supports using Amazon OpenSearch Service from domains that you have provisioned in your own Amazon account, provided they don’t exist inside a VPC. After your domains are provisioned, you can connect to them using a data source, at which point you can configure a resolver in the schema to perform GraphQL operations such as queries, mutations, and subscriptions. This tutorial will take you through some common examples.

For more information, see our JavaScript resolver function reference for OpenSearch.

Create a new OpenSearch Service domain

To get started with this tutorial, you need an existing OpenSearch Service domain. If you don’t have one, you can use the following sample. Note that it can take up to 15 minutes for an OpenSearch Service domain to be created before you can move on to integrating it with an Amazon AppSync data source.

aws cloudformation create-stack --stack-name AppSyncOpenSearch \ --template-url https://s3.us-west-2.amazonaws.com/awsappsync/resources/elasticsearch/ESResolverCFTemplate.yaml \ --parameters ParameterKey=OSDomainName,ParameterValue=ddtestdomain ParameterKey=Tier,ParameterValue=development \ --capabilities CAPABILITY_NAMED_IAM

You can launch the following Amazon CloudFormation stack in the US-West-2 (Oregon) Region in your Amazon account:

Configure a data source for OpenSearch Service

After the OpenSearch Service domain is created, navigate to your Amazon AppSync GraphQL API and choose the Data Sources tab. Choose Create data source and enter a friendly name for the data source such as “oss”. Then, choose Amazon OpenSearch domain for Data source type, choose the appropriate Region, and you should see your OpenSearch Service domain listed. After selecting it, you can either create a new role, and Amazon AppSync will assign the role-appropriate permissions, or you can choose an existing role, which has the following inline policy:

{ "Version": "2012-10-17", "Statement": [ { "Sid": "Stmt1234234", "Effect": "Allow", "Action": [ "es:ESHttpDelete", "es:ESHttpHead", "es:ESHttpGet", "es:ESHttpPost", "es:ESHttpPut" ], "Resource": [ "arn:aws:es:REGION:ACCOUNTNUMBER:domain/democluster/*" ] } ] }

You’ll also need to set up a trust relationship with Amazon AppSync for that role:

{ "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Principal": { "Service": "appsync.amazonaws.com" }, "Action": "sts:AssumeRole" } ] }

Additionally, the OpenSearch Service domain has its own Access Policy that you can modify through the Amazon OpenSearch Service console. You must add a policy similar to the one below with the appropriate actions and resources for the OpenSearch Service domain. Note that the Principal will be the Amazon AppSync data source role, which can be found in the IAM console if you let said console create it.

{ "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Principal": { "AWS": "arn:aws:iam::ACCOUNTNUMBER:role/service-role/APPSYNC_DATASOURCE_ROLE" }, "Action": [ "es:ESHttpDelete", "es:ESHttpHead", "es:ESHttpGet", "es:ESHttpPost", "es:ESHttpPut" ], "Resource": "arn:aws:es:REGION:ACCOUNTNUMBER:domain/DOMAIN_NAME/*" } ] }

Connecting a resolver

Now that the data source is connected to your OpenSearch Service domain, you can connect it to your GraphQL schema with a resolver as shown in the following example:

type Query { getPost(id: ID!): Post allPosts: [Post] } type Mutation { addPost(id: ID!, author: String, title: String, url: String, ups: Int, downs: Int, content: String): AWSJSON } type Post { id: ID! author: String title: String url: String ups: Int downs: Int content: String }

Note that there is a user-defined Post type with a field of id. In the following examples, we assume there is a process (which can be automated) for putting this type into your OpenSearch Service domain, which would map to a path root of /post/_doc where post is the index. From this root path, you can perform individual document searches, wildcard searches with /id/post*, or multi-document searches with a path of /post/_search. For example, if you have another type called User, you can index documents under a new index called user, then perform searches with a path of /user/_search.

From the Schema editor in the Amazon AppSync console, modify the preceding Posts schema to include a searchPosts query:

type Query { getPost(id: ID!): Post allPosts: [Post] searchPosts: [Post] }

Save the schema. In the Resolvers pane, find searchPosts and choose Attach. Choose your OpenSearch Service data source and save the resolver. Update your resolver's code using the snippet below:

import { util } from '@aws-appsync/utils' /** * Searches for documents by using an input term * @param {import('@aws-appsync/utils').Context} ctx the context * @returns {*} the request */ export function request(ctx) { return { operation: 'GET', path: `/post/_search`, params: { body: { from: 0, size: 50 } }, } } /** * Returns the fetched items * @param {import('@aws-appsync/utils').Context} ctx the context * @returns {*} the result */ export function response(ctx) { if (ctx.error) { util.error(ctx.error.message, ctx.error.type) } return ctx.result.hits.hits.map((hit) => hit._source) }

This assumes that the preceding schema has documents that have been indexed in OpenSearch Service under the post field. If you structure your data differently, you’ll need to update accordingly.

Modifying your searches

The preceding resolver request handler performs a simple query for all records. Suppose you want to search by a specific author. Furthermore, suppose you want that author to be an argument defined in your GraphQL query. In the Schema editor of the Amazon AppSync console, add an allPostsByAuthor query:

type Query { getPost(id: ID!): Post allPosts: [Post] allPostsByAuthor(author: String!): [Post] searchPosts: [Post] }

In the Resolvers pane, find allPostsByAuthor and choose Attach. Choose the OpenSearch Service data source and use the following code:

import { util } from '@aws-appsync/utils' /** * Searches for documents by `author` * @param {import('@aws-appsync/utils').Context} ctx the context * @returns {*} the request */ export function request(ctx) { return { operation: 'GET', path: '/post/_search', params: { body: { from: 0, size: 50, query: { match: { author: ctx.args.author } }, }, }, } } /** * Returns the fetched items * @param {import('@aws-appsync/utils').Context} ctx the context * @returns {*} the result */ export function response(ctx) { if (ctx.error) { util.error(ctx.error.message, ctx.error.type) } return ctx.result.hits.hits.map((hit) => hit._source) }

Note that the body is populated with a term query for the author field, which is passed through from the client as an argument. Optionally, you could use prepopulated information, such as standard text.

Adding data to OpenSearch Service

You may want to add data to your OpenSearch Service domain as the result of a GraphQL mutation. This is a powerful mechanism for searching and other purposes. Because you can use GraphQL subscriptions to make your data real-time, it can serve as a mechanism for notifying clients of updates to data in your OpenSearch Service domain.

Return to the Schema page in the Amazon AppSync console and select Attach for the addPost() mutation. Select the OpenSearch Service data source again and use the following code:

import { util } from '@aws-appsync/utils' /** * Searches for documents by `author` * @param {import('@aws-appsync/utils').Context} ctx the context * @returns {*} the request */ export function request(ctx) { return { operation: 'PUT', path: `/post/_doc/${ctx.args.id}`, params: { body: ctx.args }, } } /** * Returns the inserted post * @param {import('@aws-appsync/utils').Context} ctx the context * @returns {*} the result */ export function response(ctx) { if (ctx.error) { util.error(ctx.error.message, ctx.error.type) } return ctx.result }

Like before, this is an example of how your data might be structured. If you have different field names or indices, you need to update the path and body. This example also shows how to use context.arguments, which can also be written as ctx.args, in your request handler.

Retrieving a single document

Finally, if you want to use the getPost(id:ID) query in your schema to return an individual document, find this query in the Schema editor of the Amazon AppSync console and choose Attach. Select the OpenSearch Service data source again and use the following code:

import { util } from '@aws-appsync/utils' /** * Searches for documents by `author` * @param {import('@aws-appsync/utils').Context} ctx the context * @returns {*} the request */ export function request(ctx) { return { operation: 'GET', path: `/post/_doc/${ctx.args.id}`, } } /** * Returns the post * @param {import('@aws-appsync/utils').Context} ctx the context * @returns {*} the result */ export function response(ctx) { if (ctx.error) { util.error(ctx.error.message, ctx.error.type) } return ctx.result._source }

Perform queries and mutations

You should now be able to perform GraphQL operations against your OpenSearch Service domain. Navigate to the Queries tab of the Amazon AppSync console and add a new record:

mutation AddPost { addPost ( id:"12345" author: "Fred" title: "My first book" content: "This will be fun to write!" url: "publisher website", ups: 100, downs:20 ) }

You’ll see the result of the mutation on the right. Similarly, you can now run a searchPosts query against your OpenSearch Service domain:

query search { searchPosts { id title author content } }

Best practices

  • OpenSearch Service should be for querying data, not as your primary database. You may want to use OpenSearch Service in conjunction with Amazon DynamoDB as outlined in Combining GraphQL Resolvers.

  • Only give access to your domain by allowing the Amazon AppSync service role to access the cluster.

  • You can start small in development, with the lowest-cost cluster, and then move to a larger cluster with high availability (HA) as you move into production.