Create a derivation with flowctl
Once you're familiar with creating a basic Data Flow, you can take things a step further and transform your data with derivations.
A derivation is a kind of Flow collection that results from the transformation of one or more other collections. This transformed stream of data keeps the order of the source data intact, and can then be materialized to an outside system or further transformed with another derivation. When you master derivations, you unlock the full flexibility and power of your Data Flows.
Prerequisites
A Flow account and access to the web app. If you don't have an account yet, go to the web app to register for a free trial.
An existing Flow collection. Typically, you create this through a capture in the Flow web application. If you need help, see the guide to create a Data Flow.
Getting Started
To create a derivation, navigate to the Collections page in Flow, click on the NEW TRANSFORMATION button. This brings up a Derive A New Collection pop-up window.
Deriving a new collection consists of three steps:
Step 1: Select source collections: In the Available Collections dropdown, select the collection you want to derive.
Step 2: Transformation Language: There are two language options to select: SQL and TypeScript.
Step 3: Write transformations: Give your derived collection a name. Then click the PROCEED TO GITPOD button.
This opens up GitPod in another tab, where an environment is already set up for you.
GitPod Setup
Flow integrates with GitPod so you can leverage the full capabilities of SQLite. GitPod is free to use. It is an online Integrated Development Environment (IDE) that provides a complete development environment that can be accessed through a web browser, with all the necessary tools and dependencies pre-installed.
In GitPod, you will set up your derivation's schema specs in the flow.yaml file. The tutorial here walks through several examples on how to fill out flow.yaml depending on your use case.
Authentication
When connecting to GitPod, you will have already authenticated Flow, but if you leave GitPod opened for too long, you may have to reauthenticate Flow.
To authorize flowctl:
Go to the CLI-API tab of the web app and copy your access token.
Run
flowctl auth token --token <paste-token-here>
on the Terminal tab in GitPod.
Add a SQL derivation
In the Flow UI Derive A New Collection screen, select SQL as your transformation language.
In GitPod, locate the specification YAML file for the collection you want to transform.
In your working directory, you'll see a top-level file called
flow.yaml
. Within a subdirectory that shares the name of your Data Flow, you'll find a secondflow.yaml
— this contains the collection specification.Open the specification file
flow.yaml
.It will look similar to the following. (This example uses the default collection from the Hello World test capture, available in the web app):
collections:
#The Hello World capture outputs a collection called `greetings`.
namespace/data-flow-name/greetings:
schema:
properties:
count:
type: integer
message:
type: string
required:
- count
- message
type: object
key:
- /count
derive:
using:
sqlite:
migrations:
- greetings.migrations.0.sql
transforms:
#The transform name can be anything you'd like.
- name: greetings-by-dozen
#Paste the full name of the source collection.
source: namespace/data-flow-name/greetings
#The lambda holds your SQL transformation statement(s). You can either place your SQL directly here or in the separate lambda file.
lambda: greetings.lambda.greetings-by-dozen.sqlFill out the schema specs, key, sqlite migration, transform name, source, and lambda. This tutorial walks through several examples on how to fill out flow.yaml depending on your use case.
See also Lambdas and Migrations for additional details.
Your SQL statements are evaluated with each source collection document. Here is an example of what the output document from a derivation would look like given an input document and SQL lambda.
Preview the derivation
Type this command on the Terminal tab in GitPod to preview the derivation.
flowctl preview --source flow.yaml --interval 200ms | jq -c 'del(._meta)'
Publish the derivation from GitPod
Publish the catalog.
flowctl catalog publish --source flow.yaml
Updating an existing derivation
Derivations are applied on a go-forward basis only.
If you would like to make an update to an existing derivation (for example, adding columns to the derived collection), you can add a new transform by changing the name of your existing transform to a new name, and at the same time updating your lambda.
From the platform's perspective, this is equivalent to deleting the old transform and adding a new one. This will backfill over the source collection again with the updated SQL statement.
Transform with a TypeScript module
Using GitPod
In the Flow UI Derive A New Collection screen, select TypeScript as your transformation language.
In GitPod, locate the .ts file to put in your transformation logic. It will look similar to the following:
import { IDerivation, Document, Register, GreetingsByDozenSource } from 'flow/namespace/data-flow-name/dozen-greetings';
// Implementation for derivation flow.yaml#/collections/namespace~1data-flow-name~1dozen-greetings/derivation.
export class Derivation implements IDerivation {
greetingsByDozenPublish(
_source: GreetingsByDozenSource,
_register: Register,
_previous: Register,
): Document[] {
throw new Error("Not implemented");
}
}
Using local terminal
If you are writing a derivation using TypeScript from your local terminal rather than GitPod, follow the steps below:
Generate the TypeScript module from the newly updated specification file.
flowctl typescript generate --source ./path-to/your-file/flow.yaml
The TypeScript file you named has been created and stubbed out. You only need to add the function body.
Open the new TypeScript module. It will look similar to the following:
import { IDerivation, Document, Register, GreetingsByDozenSource } from 'flow/namespace/data-flow-name/dozen-greetings';
// Implementation for derivation flow.yaml#/collections/namespace~1data-flow-name~1dozen-greetings/derivation.
export class Derivation implements IDerivation {
greetingsByDozenPublish(
_source: GreetingsByDozenSource,
_register: Register,
_previous: Register,
): Document[] {
throw new Error("Not implemented");
}
}Remove the underscore in front of
source
and fill out the function body as required for your required transformation. For more advanced transforms, you may need to activateregister
andprevious
by removing their underscores. Learn more about derivations and see examples.This simple example rounds the
count
field to the nearest dozen.import { IDerivation, Document, Register, GreetingsByDozenSource } from 'flow/namespace/data-flow-name/dozen-greetings';
// Implementation for derivation namespace/data-flow-name/flow.yaml#/collections/namespace~1data-flow-name~1dozen-greetings/derivation.
export class Derivation implements IDerivation {
greetingsByDozenPublish(
source: GreetingsByDozenSource,
_register: Register,
_previous: Register,
): Document[] {
let count = source.count;
let dozen = count / 12;
let dozenround = Math.floor(dozen)
let out = {
dozens: dozenround,
...source
}
return [out]
}
}Save the file.
Optional: add a test to the
flow.yaml
file containing your collections. This helps you verify that your data is transformed correctly.collections:
{...}
tests:
namespace/data-flow-name/divide-test:
- ingest:
collection: namespace/data-flow-name/greetings
documents:
- { count: 13, message: "Hello #13" }
- verify:
collection: namespace/data-flow-name/dozen-greetings
documents:
- { dozens: 1, count: 13, message: "Hello #13"}
Publish the derivation in local terminal
Author your draft. This adds the changes you made locally to the draft on the Estuary servers:
flowctl draft author --source flow.yaml
Note that the file source is the top level
flow.yaml
in your working directory, not the file you worked on. This fileimports
all others in the local draft, so your changes will be included.Run generic tests, as well as your custom tests, if you created any.
flowctl draft test
Publish the draft to the catalog.
flowctl draft publish
The derivation you created is now live and ready for further use. You can access it from the web application and materialize it to a destination, just as you would any other Flow collection.