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119 lines
3.5 KiB
ReStructuredText
119 lines
3.5 KiB
ReStructuredText
.. meta::
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:description: Use serverless functions with Hasura event triggers
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:keywords: hasura, docs, event trigger, serverless function
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.. _triggers_serverless:
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Using serverless functions
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==========================
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.. contents:: Table of contents
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:backlinks: none
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:depth: 1
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:local:
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Introduction
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------------
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You can use serverless functions along with event triggers to design an async business workflow without
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having to manage any dedicated infrastructure.
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As Hasura event triggers can deliver database events to any webhook, serverless functions can be perfect candidates
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for their handlers.
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Why use serverless functions?
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-----------------------------
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1. Cost effectiveness.
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2. No infra management.
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3. Async business logic.
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Examples
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--------
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You can find a bunch of examples for various serverless cloud providers in this repo:
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https://github.com/hasura/graphql-engine/tree/master/community/boilerplates/event-triggers.
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For example: update related data on a database event
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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In this example we make a note taking app. Whenever a user updates their note, we want to store a revision of that
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note in a separate table.
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You can find the complete example at:
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https://github.com/hasura/graphql-engine/tree/master/community/boilerplates/event-triggers/aws-lambda/nodejs6/mutation.
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Let's consider the following simplified schema for the above:
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.. code-block:: SQL
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notes (
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id INT PRIMARY KEY,
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note TEXT
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)
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note_revision (
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id INT PRIMARY KEY,
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note TEXT,
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note_id INT FOREIGN KEY REFERENCES notes(id),
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update_at TIMESTAMP DEFAULT now()
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)
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Whenever an update happens to the ``notes`` table, we want to insert a row into the ``note_revision`` table.
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For this we :ref:`setup an event trigger <create_trigger>` on ``UPDATE`` to the ``notes`` table which calls an
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AWS Lambda function. The AWS Lambda function itself uses a GraphQL mutation to insert a new row into the
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``note_revision`` table. As the :ref:`event trigger payload <trigger_payload>` in case of updates gives us both the old and
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the new data, we can store the old note data in our revision table.
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Our AWS Lambda code looks like this:
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.. code-block:: javascript
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// Lambda which gets triggered on insert, and in turns performs a mutation
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const fetch = require('node-fetch');
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const adminSecret = process.env.ADMIN_SECRET;
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const hgeEndpoint = process.env.HGE_ENDPOINT;
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const query = `
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mutation updateNoteRevision ($noteId: Int!, $data: String!) {
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insert_note_revision (objects: [
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{
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note_id: $noteId,
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note: $data
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}
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]) {
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affected_rows
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}
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}
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`;
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exports.handler = (event, context, callback) => {
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let request;
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try {
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request = JSON.parse(event.body);
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} catch (e) {
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return callback(null, {statusCode: 400, body: "cannot parse hasura event"});
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}
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const response = {
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statusCode: 200,
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body: "success"
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};
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const qv = {noteId: request.event.data.old.id, data: request.event.data.old.note};
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fetch(hgeEndpoint + '/v1/graphql', {
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method: 'POST',
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body: JSON.stringify({query: query, variables: qv}),
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headers: {'Content-Type': 'application/json', 'x-hasura-admin-secret': adminSecret},
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})
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.then(res => res.json())
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.then(json => {
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console.log(json);
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callback(null, response);
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});
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};
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