Gatsby Plugin Azure Search
Gatsby plugin to ingest data into Microsoft Azure Cognitive Search.
Overview
There are 2 parts of implementing a search feature for your site. The indexing (writing) part and the querying (reading) part. The indexing part push data into some search back end, the querying part reads from the search back end via its APIs then presents the result on the front end.
This plugin handles only the indexing part, using Azure Cognitive Search as the back end service.
How to use
Install the plugin.
npm install --save gatsby-plugin-azure-search dotenv
Create an .env
file in the root directory of gatsby, same level as gatsby-config.js
. Do not commit this file.
AZURE_SEARCH_SERVICE_NAME=X
AZURE_SEARCH_ADMIN_KEY=X // Note: we need "admin key" instead of "query key"
It is recommended to use dotenv for security reasons. If your Gatsby repository is always private, you can hard-code the credentials in gatsby-config.js
at your own risk.
Add configuration in gatsby-config.js:
require('dotenv').config({
path: `.env`,
});
module.exports = {
plugins: [
{
resolve: `gatsby-plugin-azure-search`,
options: {
verbose: false, // default: false
serviceName: process.env.AZURE_SEARCH_SERVICE_NAME, // required
apiKey: process.env.AZURE_SEARCH_ADMIN_KEY, // required
indexConfig: { // required. refer to azure documentation
name: ``, // required. the plugin upserts the index, no need to create it in advance
fields: [], // required
suggesters: [], // optional
scoringProfiles: [], // optional
analyzers: [], // optional
charFilters: [], // optional
tokenizers: [], // optional
tokenFilters: [], // optional
defaultScoringProfile: '', // optional
corsOptions: { // optional
allowedOrigins: [],
maxAgeInSeconds: 300,
},
encryptionKey: {}, // optional
},
queries: [], // required. details in next section.
},
}
]
}
For indexConfig
, refer to the official Azure documentation.
You may also refer to example
folder for how I configured the plugin in my blog.
Assume the configuration is correct, your gatsby site should be indexed to Azure search every time it is built. You can verify the generated search index in Azure console.
Query Configuration
You can provide multiple graphql queries for ingestion, but for now all generated documents will be ingested into the same index.
Each query object specifies a required graphql query
and an optional transformer
function.
The transformer function operates on the raw graphql query output as an array, and returns the transformed indexable documents as an array.
The transformed document must match exactly as defined in the index’s fields
configuration. Including extra keys will result in bad request errors from Azure.
Sample query:
const sampleQuery = {
query: `{
allWordpressPost(
filter: {
status: { eq: "publish" }
}
) {
edges {
node {
slug
date
title
content
excerpt
categories {
name
}
tags {
name
}
}
}
}
}`,
transformer: ({ data }) => {
return data.allWordpressPost.edges.map(edge => {
return {
...edge.node,
permalink: `https://artifact.me/${edge.node.slug}`,
content: (edge.node.content || '').replace(/(<([^>]+)>)/ig,""),
excerpt: (edge.node.excerpt || '').replace(/(<([^>]+)>)/ig,"").substring(0, 200) + '...',
categories: (edge.node.categories || []).map(c => c.name),
tags: (edge.node.tags || []).map(t => t.name),
};
});
},
};