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What is a Data Pipeline?

A Data Pipeline or in short just Pipeline in PIPEFORCE is a YAML script which describes the flow of data from one endpoint to another. Between these endpoints, the data can be enriched, transformed, cleansed and so on, so it becomes compatible between these integration endpoints.

Such a pipeline consists typically of one or more so called Commands to reach these goals. A command is a server-side task.

Here is an example of such a pipeline YAML script which simply downloads a JSON document and stores it in the attached cloud storage:

pipeline:
  - http.get: https://somedomain.tld/rest/contracts
  - drive.save: contracts.json 

In the web portal of the enterprise version of PIPEFORCE there is also a no code editor so you can design such pipelines via drag & drop:

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What is a Command?​

A Command in PIPEFORCE is a server-side operation, which covers a single operation. It can be executed remotely via HTTP. It takes an optional input body, optional parameters, processes a certain task, and finally produces an optional output which is the response to the caller. Here is an example of a command URL which can be called via HTTP GET request:

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You can find a all built-in commands in the commands reference.

Command Name​

Each command has a unique name which is always written in lower case and follows the dot.notation. Here are some examples of valid command names in dot notation:

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Command Alias

Besides the default command name, a command can also have one or more aliases. These are alternative names which can be used the same way as the default names. For example the command mail.send has also the alias mail. Both can be used the same way for sending emails since they point to the same command implementation.

For list of the alias names of a command, see the command documentation.

Command Parameters​

Commands can have zero to many parameters. Whereas each parameter is a name-value pair. The parameters can be passed in different ways to the command, depending on the execution context you're working in. See Executing a Command below.

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pipeline:
  - log:
      message: {"key": "value"}

Default Command Parameter (short form)

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It depends on the command whether it supports a default parameter or not. See in the command docs to find out. The default parameters are marked with (default).

Limitations

Default parameter value can only be primitive

The values of a default parameter can only be primitives like string, number or boolean. It cannot be a JSON object or array. If you need to pass a JSON, pass it as string if the command supports this. In most cases the command will auto-convert from string to JSON if required. For example:

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Mixing default and ordinary parameters not allowed

Note that mixing the default parameter with ordinary parameters is not possible since YAML specification is not allowing this:

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Executing a Command​

A single Command can be executed by sending it as HTTP GET or POST request using the endpoint /api/v3/command. The full url structure of this endpoint is always like this:

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HTTP GET​

Here is an example to execute the log command as HTTP GET request, and set its message parameter to a string value using a HTTP request parameter:

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See HTTP Execution Reference for an summary of all supported HTTP options here.

HTTP POST​

Here is an example to execute a single command as HTTP POST request, and set the message parameter to a log command using a HTTP POST data body in curl:

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See HTTP Execution Reference for an summary of all supported HTTP options here.

CLI​

You can also use the PIPEFORCE CLI in order to execute a single Command. Here is an example to call the log command and set the message parameter accordingly:

pi command log message=HELLO

Body​

Also see: Pipeline Body.

Beside parameters, a command can also consume and produce a body, similar to a HTTP POST request and response.

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See HTTP Execution Reference for an summary of all supported HTTP options here.

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Pipeline

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in Detail​

Two or more Commands can be chained to a flow, called a Pipeline. If such a pipeline gets executed, each command in it will be executed one after another, whereas the output message of the first command will become the input message of the next command, and so on:

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By default, the message output (= body) of the first command (datetime in this example) will automatically become the input message (= body) of the next command (log in this example). Therefore no declaration and exchange of variables is required here. The exchange of body data between commands is implicitly.

Parameters​

In case you need to configure a command by specifying parameters for it in a pipeline, you can do so by writing them below the command as name-value-pairs with an additional tab indent or a at least two spaces as indent (see YAML specification for this):

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pipeline:
  - datetime:
      format: "dd-MM-YYYY"
  - log

Multi-line parameters

Parameters can also be multiple lines long:

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There are much more options on how to format line breaks in YAML. For full details, see the YAML specification: https://yaml.org/spec/1.2.2/

JSON Parameters​

Furthermore, it is possible to specify a JSON as parameter, like this example shows:

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As you can see, there is no need to escape or convert the JSON to a string. It can be placed as JSON 1:1 inside the YAML.

PEL Parameters

Beside static string values it is also possible to pass dynamic values to the parameters. This is done by using a Pipeline Expression. For example:

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For more information about Pipeline Expressions, see section: Pipeline Expression Language (PEL)

Executing a Pipeline​

Execute by HTTP request

Executing a Pipeline with HTTP is simple:

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See HTTP Execution Reference for an summary of all supported HTTP options.

Sending the Body Message with HTTP​

You can also send the pipeline body in an HTTP request. See this example:

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BODY: Hello World!

Execute in Portal​

The portal offers an advanced online editor with syntax highlighting, code completion and debugging support, where you can write pipelines and execute them online. This is the easiest and most preferred way to ad-hoc execute and test your pipelines. Here you can see a simple pipeline after its ad-hoc execution in the online editor:

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Execute in CLI​

Another approach to execute a pipeline is by using the CLI: Command Line Interface (CLI).

Execute local pipeline file​

Lets assume you have a local pipeline YAML stored at src/global/app/myapp/pipeline/test.pi.yaml inside of your PIPEFORCE workspace, then you can execute it via this CLI call (the path must start with src/):

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Execute persisted remote pipeline​

In case you have stored your pipeline at server side in the Property Store, then you can execute it using this call (the path must start with global/):

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This command searches for a property in the property store with path global/app/myapp/pipeline/test and executes it. Finally, it sends any result back to your terminal.

Pipeline Sections​

Every pipeline YAML script may consist of four main sections:

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All sections except pipeline are optional in a pipeline script. Even if not explicitly defined in the pipeline script, each scope exists implicitly. That means, you can access it and read / set values from / on it without declaring it in the pipeline. For example, by using a pipeline expression (PE).

headers​

The headers section is optional. A header is a name-value pair to define "global configuration" hints and configurations for the given pipeline. Only text is allowed as content i.e. no complex objects like JSON. It is not meant to be changed during pipeline processing, even this is possible for rare cases.

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You can read and set values in the headers section using the Pipeline Expression Language (PEL).

vars​

The vars section is optional and contains transient variables as name value pairs. It is meant as a transient scope for states during the pipeline processing.

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You can access values in the vars scope using the Pipeline Expression Language (PEL).

pipeline​

The pipeline section is mandatory and lists all commands which must be executed in given order.

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You can set dynamic parameter values on commands using the Pipeline Expression Language (PEL).

body​

The body section is optional. It defines a single object to be used as “data pool” or transformation data during the pipeline processing.

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You can access values in the body scope using the Pipeline Expression Language (PEL).

Pipeline as JSON​

Sometimes it is necessary to use JSON as the pipeline definition language instead of YAML. Let's assume a pipeline written in YAML like this:

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Pipeline as URI​

Beside YAML and JSON, a third option to define a pipeline is possible: Using a pipeline uri which is an inline version of a pipeline. This is handy in case you must define a pipeline as a “one-liner”.

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Auto-completion support​

In order to enable auto-completion support for your pipeline YAML scripts in your local development editor, you need an editor which supports YAML schema validation. Then, you can have auto-completion which shows all available commands and their parameters:

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Auto-completion in IntelliJ​

To enable auto-completion in IntelliJ, open preferences and navigate to JSON Schema Mappings:

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A YAML pipeline script should always end in suffix .pi.yaml which stands for stands for pipeline scripts written in YAML.

Auto-completion in Visual Studio Code​

If you want to also enable code-completion for your pipeline yaml files in your VS Code editor, you need to install the YAML language support plugin from Red Hat first: https://marketplace.visualstudio.com/items?itemName=redhat.vscode-yaml

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A local YAML pipeline script should always end in suffix .pi.yaml which stands for pipeline scripts written in YAML.

Auto-completion in the Portal​

The built-in online workbench and the playground in the PIPEFORCE portal supports pipeline script completion out-of-the box.

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