Tutorial: Creating a search application with Amazon OpenSearch Service

To create the deployment package

1. Open a command prompt and create a my-opensearch-function project directory. For example, on macOS:

   mkdir my-opensearch-function

2. Navigate to the my-sourcecode-function project directory.

   cd my-opensearch-function

3. Copy the contents of the following sample Python code and save it in a new file named opensearch-lambda.py. Add your Region and host endpoint to the file.

   import boto3
   import json
   import requests
   from requests_aws4auth import AWS4Auth
   
   region = '' # For example, us-west-1
   service = 'es'
   credentials = boto3.Session().get_credentials()
   awsauth = AWS4Auth(credentials.access_key, credentials.secret_key, region, service, session_token=credentials.token)
   
   host = '' # The OpenSearch domain endpoint with https:// and without a trailing slash
   index = 'movies'
   url = host + '/' + index + '/_search'
   
   # Lambda execution starts here
   def lambda_handler(event, context):
   
       # Put the user query into the query DSL for more accurate search results.
       # Note that certain fields are boosted (^).
       query = {
           "size": 25,
           "query": {
               "multi_match": {
                   "query": event['queryStringParameters']['q'],
                   "fields": ["title^4", "plot^2", "actors", "directors"]
               }
           }
       }
   
       # Elasticsearch 6.x requires an explicit Content-Type header
       headers = { "Content-Type": "application/json" }
   
       # Make the signed HTTP request
       r = requests.get(url, auth=awsauth, headers=headers, data=json.dumps(query))
   
       # Create the response and add some extra content to support CORS
       response = {
           "statusCode": 200,
           "headers": {
               "Access-Control-Allow-Origin": '*'
           },
           "isBase64Encoded": False
       }
   
       # Add the search results to the response
       response['body'] = r.text
       return response

4. Install the external libraries to a new package directory.

   pip3 install --target ./package boto3
   pip3 install --target ./package requests
   pip3 install --target ./package requests_aws4auth

5. Create a deployment package with the installed library at the root. The following command generates a my-deployment-package.zip file in your project directory.

   cd package
   zip -r ../my-deployment-package.zip .

6. Add the opensearch-lambda.py file to the root of the zip file.

   cd ..
   zip my-deployment-package.zip opensearch-lambda.py

1. Navigate to the Lambda console at https://console.aws.amazon.com/lambda/home. On the left navigation pane, choose Functions.

2. Select Create function.

3. Configure the following fields:

   • Function name: opensearch-function

   • Runtime: Python 3.9

   • Architecture: x86_64

   Keep all other default options and choose Create function.

4. In the Code source section of the function summary page, choose the Upload from dropdown and select .zip file. Locate the my-deployment-package.zip file that you created and choose Save.

5. The handler is the method in your function code that processes events. Under Runtime settings, choose Edit and change the handler name according to the name of the file in your deployment package where the Lambda function is located. Since your file is named opensearch-lambda.py, rename the handler to opensearch-lambda.lambda_handler. For more information, see Lambda function handler in Python.

1. Navigate to the API Gateway console at https://console.aws.amazon.com/apigateway/home. On the left navigation pane, choose APIs.

2. Locate REST API (not private) and choose Build.

3. On the following page, locate the Create new API section and make sure New API is selected.

4. Configure the following fields:

   • API name: opensearch-api

   • Description: Public API for searching an Amazon OpenSearch Service domain

   • Endpoint Type: Regional

5. Choose Create API.

6. Choose Actions and Create Method.

7. Select GET in the dropdown and click the checkmark to confirm.

8. Configure the following settings, then choose Save:

1. Choose Actions and Deploy API.

2. For Deployment stage choose New Stage and name the stage opensearch-api-test.

3. Choose Deploy.

4. Configure the following settings in the stage editor, then choose Save Changes:

1. Navigate to the OpenSearch Dashboards URL for the domain.

2. From the main menu, choose Security, Roles, and select the link to all_access, the role you need to map the Lambda role to.

3. Choose Mapped users, Manage mapping.

4. Under Backend roles, add the Amazon Resource Name (ARN) of the Lambda role. The ARN should take the form of arn:aws:iam::123456789123:role/service-role/opensearch-lambda-role-1abcdefg.

5. Select Map and confirm the user or role shows up under Mapped users.

To test the web application

1. Download sample-site.zip, unzip it, and open scripts/search.js in your favorite text editor.

2. Update the apigatewayendpoint variable to point to your API Gateway endpoint and add a backslash to the end of the given path. You can quickly find the endpoint in API Gateway by choosing Stages and selecting the name of the API. The apigatewayendpoint variable should take the form of https://some-id.execute-api.us-west-1.amazonaws.com/opensearch-api-test/.

3. Open index.html and try running searches for thor, house, and a few other terms.

   

1. Enable CORS on the GET resource. Under Advanced, set Access-Control-Allow-Credentials to 'true'.

2. Redeploy your API in API Gateway (Actions, Deploy API).

3. Delete and re-add your Lambda function trigger. Add re-add it, choose Add trigger and create the HTTP endpoint that invokes your function. The trigger must have the following configuration:

   Trigger	API	Deployment Stage	Security
   API Gateway	opensearch-api	opensearch-api-test	Open