What is a composed task?

A composed task is a directed graph where each node of the graph is a task application. Spring Cloud Data Flow lets you create a composed task through its browser-based UI, its shell, or its RESTful API. In this section, we show you how you can create and manage composed tasks.

Composed Task 101

Before going into how to create and manage composed tasks, we need to discuss a scenario where we want to launch a sequence of task definitions.
For this discussion, suppose we want to launch task definitions identified as task-a, task-b, and task-c. For example, we launch task-a, and, if task-a has completed successfully, we want to launch task-b. Once task-b has completed successfully, we want to launch task-c. In this case, the graph would look like the following image:

Composed Task Graph

The preceding diagram can be expressed by using Spring Cloud Data Flow's task definition DSL, as follows:

task-a && task-b && task-c

The && in the preceding DSL states that the task definition to the left of the && must complete successfully before the next task definition in the flow can be launched.

Once the preceding composed task definition is created, you can launched it in the same way you would a regular task definition. Behind the scenes, Spring Cloud Data Flow launches the Composed Task Runner application to manage the execution of the composed task graph. It does this by parsing the Spring Cloud Data Flow task definition and then makes RESTful API calls back to the Spring Cloud Data Flow server to launch the task definitions. As each task completes, it launches the next task definition. In the following sections, we show you how to create your own composed task graphs, to explore the various ways you can create a composed task flow.

Configuring Spring Cloud Data Flow Launch Composed Tasks

As discussed earlier, the Composed-Task-Runner is an application that manages the execution of the tasks in a composed task graph. So, before creating composed tasks, we need to configure Spring Cloud Data Flow to launch the Composed Task Runner properly.

Configuring Data Flow to Launch the Composed Task Runner

When launching a composed task, Spring Cloud Data Flow passes properties to the Composed-Task-Runner so that it can execute the directed graph properly. To do this, you must configure Spring Cloud Data Flow's dataflow.server.uri property so that Composed Task Runner can make the RESTful API calls to the correct SCDF Server:

  • dataflow.server.uri: The URI of the Spring Cloud Data Flow Server that is used by the Composed Task Runner to execute its RESTful API calls. It defaults to https://localhost:9393.
  • spring.cloud.dataflow.task.composedtaskrunner.uri: Establishes where Spring Cloud Data Flow obtains the Composed Task Runner artifact. By default, Spring Cloud Data Flow retrieves the artifact from Maven Central for the local and Cloud Foundry platforms. For Kubernetes, it obtains the artifact from DockerHub.

spring.cloud.dataflow.task.composed.task.runner.uri has been deprecated as of Spring Cloud Data Flow 2.7.0 in favor of spring.cloud.dataflow.task.composedtaskrunner.uri.

  • spring.cloud.dataflow.task.composedtaskrunner.imagePullSecret: If running within Kubernetes and the Composed Task Runner image resides in a repository that requires authentication, you can configure a secret that contains the credentials to use when pulling the image. The property value is the name of the configured secret that must be created first. Follow the Pull an Image from a Private Registry guide to create the secret.
  • maximumConcurrentTasks - Spring Cloud Data Flow lets a user limit the maximum number of concurrently running tasks for each configured platform to prevent the saturation of IaaS/hardware resources. The default limit is set to 20 for all supported platforms. If the number of concurrently running tasks on a platform instance is greater than or equal to the limit, the next task launch request fails, and an error message is returned through the RESTful API, the Shell, and the UI. You can configure this limit for a platform instance by setting the corresponding deployer property to the number maximum number of concurrent tasks:

    spring.cloud.dataflow.task.platform.<platform-type>.accounts[<account-name>].deployment.maximumConcurrentTasks`

    The <account-name> is the name of a configured platform account (default if no accounts are explicitly configured). The <platform-type> refers to one of the currently supported deployers: local, cloudfoundry, or kubernetes.

Changing this property will require Spring Cloud Data Flow to be restarted.

Registering Sample Applications

Before you work with the composed task samples below, you must first register the sample applications that are used in the examples. So, for this guide, you need to re-register the timestamp application multiple times with the following names: task-a, task-b, task-c, task-d, task-e, and task-f.

Spring Cloud Data Flow supports Maven, HTTP, file, and Docker resources for local deployments. For local, we use the Maven resource. The URI for a Maven artifact is generally of the form maven://<groupId>:<artifactId>:<version>. The Maven URI for the sample application is as follows:

maven://org.springframework.cloud.task.app:timestamp-task:2.1.0.RELEASE

The maven: protocol specifies a Maven artifact, which is resolved by using the remote and local Maven repositories configured for the Data Flow server. To register an application, click the Applications tab on the left side of the page. Select Add Applications and Register one or more applications. For task-a fill in the form, as shown in the following image, and click Register the application(s).

Register the  transition sample

Repeat this registration for task-a, task-b, task-c, task-d, task-e, and task-f while using the same URI: maven://org.springframework.cloud.task.app:timestamp-task:2.1.0.RELEASE.

Spring Cloud Data Flow supports Maven, HTTP, and Docker resources for local deployments. For Cloud Foundry, we use an HTTP (actually, HTTPS) resource. The URI for an HTTPS resource is of the form https://<web-path>/<artifactName>-<version>.jar. Spring Cloud Data Flow then pulls the artifact from the HTTPS URI.

The HTTPS URI for the sample application is as follows:

https://repo.spring.io/libs-snapshot/org/springframework/cloud/task/app/timestamp-task/2.1.0.RELEASE/timestamp-task-2.1.0.RELEASE.jar

To register an application, click the Applications tab on the left side of the page. Select Add Applications and Register one or more applications. Fill in the form, as shown in the following image, and click Register the application(s).

Register the transition sample Repeat this registration for task-a, task-b, task-c, task-d, task-e, and task-f while using the same URI:

https://repo.spring.io/libs-snapshot/org/springframework/cloud/task/app/timestamp-task/2.1.0.RELEASE/timestamp-task-2.1.0.RELEASE.jar`

Spring Cloud Data Flow supports Docker resources for Kubernetes deployments. The URI for a Docker image is the form docker:<docker-image-path>/<imageName>:<version> and is resolved by using the Docker registry configured for the Data Flow task platform and image pull policy.

The Docker URI for the sample app is as follows:

docker:springcloudtask/timestamp-task:2.1.0.RELEASE

To register an application, click the Applications tab on the left side of the page. Select Add Applications and Register one or more applications. Fill in the form, as shown in the following image, and click Register the application(s).

Register the transition sample

Repeat this registration for task-a, task-b, task-c, task-d, task-e, and task-f while using the same URI: docker:springcloudtask/timestamp-task:2.1.0.RELEASE.

If Maven Central or DockerHub cannot be reached for a given Spring Cloud Data Flow deployment a different URI can be specified to retrieve the Composed Task Runner using the spring.cloud.dataflow.task.composed.task.runner.uri property.

The Transition Sample Project

To explore some of the flows that are available through a composed task diagram, we need an application that lets us configure its exit status at startup time. This transition-sample gives us the ability to explore various flows through a composed task diagram.

Getting the Transition Sample Project from Github

We need to pull the project from Github:

  1. Open a terminal session.
  2. Choose a working directory where you want to clone the project.
  3. From the working directory, run the following git command:

    git clone https://github.com/spring-cloud/spring-cloud-dataflow-samples.git
  4. Go into the spring-cloud-dataflow-samples/transition-sample directory

    cd spring-cloud-dataflow-samples/transition-sample

Building the Transition Sample Project

To build the application, use the following command:

./mvnw clean install

To build the Docker image, use the following command:

./mvnw dockerfile:build

Registering the Transition Sample

For local deployments, Spring Cloud Data Flow supports Maven, HTTP, file, and Docker resources. For this example, we use the Maven resource. The URI for a Maven artifact is generally of the form maven://<groupId>:<artifactId>:<version>. The Maven URI for the sample application is as follows:

maven://io.spring:transition-sample:1.0.0.BUILD-SNAPSHOT

The maven: protocol specifies a Maven artifact, which is resolved by using the remote and local Maven repositories configured for the Data Flow server. To register an application, click the Applications tab on the left side of the page. Select Add Applications and Register one or more applications. Fill in the form, as shown in the following image, and click Register the application(s).

Register the  transition sample

Spring Cloud Data Flow supports Maven, HTTP, and Docker resources for local deployments. For this example, we use an HTTP (actually, HTTPS) resource. The URI for an HTTPS resource is of the form https://<web-path>/<artifactName>-<version>.jar. Spring Cloud Data Flow then pulls the artifact from the HTTPS URI.

The HTTPS URI for the sample app is as follows:

http://<path to your jar>:transition-sample:1.0.0.BUILD-SNAPSHOT

To register an application, click the Applications tab on the left side of the page. Select Add Applications and Register one or more applications. Fill in the form, as shown in the following image, and click Register the application(s).

Register the transition sample

Spring Cloud Data Flow supports Docker resources for Kubernetes deployments. The URI for a Docker image is of the form docker:<docker-image-path>/<imageName>:<version> and is resolved by using the Docker registry configured for the Data Flow task platform and image pull policy.

The Docker URI for the sample app is as follows:

docker:springcloud/transition-sample:latest

To register an application, click the Applications tab on the left side of the page. Select Add Applications and Register one or more applications. Fill in the form, as shown in the following image, and click Register the application(s).

Register the transition sample

Building a Composed Task

This section explores the three foundation structures supported by Spring Cloud Data Flow:

  • Conditional Execution
  • Transitional Execution
  • Split Execution

Conditional Execution

Conditional execution is expressed by using a double ampersand symbol &&. This lets each task in the sequence be launched only if the previous task successfully completed.

Create Conditional Execution Composed Task Definition

To create your conditional execution by using the Spring Cloud Data Flow UI, click the Tasks tab on the left hand side of the dashboard and then press the CREATE TASK button at the top of the page. Now copy the following expression and paste it in the text box located at the top of the page:

task-a && task-b

You can see the graph appear in the dashboard, as the following image shows: Conditional Execution Flow

In the preceding example, note that we used task-a and task-b labels. This is necessary because we use two timestamp applications in the same graph.

Now press the Create Task button at the bottom of the page. A dialog asks you to Confirm Task Creation. To do so, enter conditional-execution as the composed task name in the Name field and click the Create the task button, as the following image shows: Conditional Execution Create

Now the Task Definition page is displayed, and you can see that three task definitions were created, as the following image shows: Conditional Execution Task Definition Listing

  1. The conditional-execution task definition is the Composed-Task-Runner application that manages the execution of the directed-graph.
  2. The conditional-execution-task-a is the task definition that represents the task-a app defined in the DSL you entered earlier.
  3. The conditional-execution-task-b is the task definition that represents the task-b app defined in the DSL you entered earlier.

Launch Conditional Execution Composed Task Definition

To launch the composed task, click the dropdown icon to the left of the task definition named conditional-execution and select the Launch option, as the following image shows: Conditional Execution Task Definition Launch Now the task launch page appears. Since we are using app defaults, we merely need to press the LAUNCH TASK button, as the following image shows: Conditional Execution Task Definition Launch When the composed task called conditional-execution is launched, it launches the task called conditional-execution-task-a, and, if it completes successfully, the task called conditional-execution-task-b is launched. If conditional-execution-task-a fails, conditional-execution-task-b does not launch.

Check the Status of the Conditional Execution Composed Task Definition

Now that we have executed the conditional-execution task definition, we can check the task execution status. To do so, click the Executions tab on top of the Tasks page. From here, we can see that the conditional-execution (Composed-Task-Runner) successfully launched each of the child apps (conditional-execution-task-a and conditional-execution-task-b), as the following image shows: Conditional Execution Flow

Transitional Execution

Transitions let you specify the branch of a tree you want the flow to follow. A task transition is represented by the following symbol ->. To demonstrate, we create a basic transition graph.

Create Basic Transition Task Definition

To create a basic transition by using the Spring Cloud Data Flow UI, click the Tasks tab on the left side of the dashboard and then press the CREATE TASK button at the top of the page. Now copy the following expression and paste it in the text box located at the top of the page:

transition-sample 'FAILED' -> task-a 'COMPLETED' -> task-b

It should look like the following: Transition Execution Flow

You can use Spring Cloud Data Flow UI's drag and drop capabilities to draw the graph vs. using the DSL.

Now that the graph is rendered, we can dig into the details. The first application to be launched is transition-sample. Since transition-sample is a Spring Cloud Task application, Spring Cloud Task records the exit message to the database at the end of the execution. This message will have one of the following values:

  • COMPLETED: The task completed successfully.
  • FAILED: The task failed during its execution.
  • A custom exit message: A Spring Cloud Task application can return a custom exit message, as discussed in the Spring Cloud Task documentation.

Once the transition-sample application's execution is complete, the composed task runner checks the exit message for transition-sample and then evaluates which of the paths it should take. In our case, its has two paths (as denoted by the -> operator).

  • FAILED: If transition-sample returns FAILED, the timestamp app labeled task-a is executed.
  • COMPLETED: If transition-sample returns COMPLETED, the timestamp app labeled task-b is executed.

Now press the Create Task button at the bottom of the page. Now a dialog asks you to Confirm Task Creation. To do so, enter basictransition as the composed task name in the Name field and click the Create the task button, as the following image shows: Transition Execution Flow

Launch the Composed Task Definition

Now we can launch our composed task a couple of times so that we can exercise its paths through the tree.

First, we can see what happens if we set the exit message to FAILED. To do so, select the basictransition Composed Task Runner to be executed, as the following image shows: Transition Execution Flow Launch Now, from the task launch page, populate the page with the following:

First set the interval between checks for the composed task runner to 1000 milliseconds. This is done by clicking the EDIT button on the CTR properties under the Global column as shown below: Transition Execution Set Interval Time Prop Now enter 1000 in the interval-time-between-checks field Transition Execution Set Interval Time Prop Set Click the UPDATE button.

Now let's set the transition app to return an exit message of FAILED. This is done by clicking the EDIT button on the Application properties under the transition-sample column. Once the update dialog appears enter FAILED into the exit-message row as shown below: Transition Execution app Prop Set

Click the UPDATE button.

Now Click the LAUNCH TASK button. Now that it has been executed, we can verify that the FAILED path was actually followed. We can do so by clicking the Task executions tab on the left side of the task page: Transition Execution Flow Launch-List

Doing so shows us that the Composed Task Runner controlling the composed task execution basic-transition was launched and that transition-sample was launched. From there, the FAILED branch was executed, as denoted by basictransition-task-a was launched.

Now relaunch the Composed Task Runner and set the exit-message to COMPLETED to exercise the other branch. To do so, select the basictransition to be executed, as the following image shows: Transition Execution Flow Launch

This is done by clicking the EDIT button on the Application properties under the transition-sample column. Once the update dialog appears enter COMPLETED into the exit-message row as shown below: Transition Execution app Prop Set

Click the UPDATE button.

Click the LAUNCH TASK button.

Now that it has been executed, we can verify that the COMPLETED path was followed. You can do so by pressing the Task executions tab on the left side of the page: Transition Execution Flow Launch-CompleteList

Are There More States to a Transition?

Now what happens if I were to enter FOO for the exit message?

To do so, select the basictransition Composed Task Runner to be executed, as the following image shows: Transition Execution Flow Launch Once the launch page appears click the EDIT button on the Application properties under the transition-sample column. Once the update dialog appears enter FOO into the exit-message row as shown below:

Transition Execution Flow Launch-Config-FOO Click the UPDATE button.

Click the LAUNCH TASK button.

Now that it has been executed, we can verify that path FOO was actually followed. To do so, click the Task executions tab on the left side of the page: Transition Execution Flow Launch-FOO-LIST

In this case, we see that the composed task ended with merely running the Composed Task Runner and the transition sample. This was because FOO was not targeted. How would we handle that -- that is, have a path for COMPLETED, FAILED, and everything else?

In this case, we would want to create another composed task by using a wild card.

To create your basic transition by using the Spring Cloud Data Flow UI, click the Tasks tab on the left side of the dashboard and then press the CREATE TASK button at the top of the page. Now copy the following expression and paste it in the text box at the top of the page:

transition-sample 'FAILED' -> task-a 'COMPLETED' -> task-b '*' -> task-c

It should look like the following: Transition Execution Foo_Flow Now press the Create Task button at the bottom of the page. Now a dialog asks you to Confirm Task Creation. To do so, enter anothertransition as the composed task name in the Name field and click the Create the task button, as the following image shows: Transition Execution Foo_Flow_Create

To do so, select the anothertransition Composed Task Runner to be executed, as the following image shows: Transition Execution Flow Launch-Another From the task launch page, populate the page with the following:

Arguments:

--increment-instance-enabled=true
--interval-time-between-checks=1000

Parameters:

app.anothertransition.transition-sample.taskapp.exitMessage=FOO

Once the launch page appears click the EDIT button on the Application properties under the transition-sample column. Once the update dialog appears enter FOO into the exit-message row as shown below:

Transition Execution Flow Launch-Config-FOO Click the UPDATE button.

Click the LAUNCH TASK button.

Now verify that path FOO was actually followed. To do so, click the Executions tab at the top of the task page: Transition Execution Flow Launch-FOO-success-LIST

In this case, we see that the wildcard catches all other exit messages. We can verify by seeing that anothertransition-task-c was launched.

Split Execution

What if we want to execute multiple tasks at the same time? The Composed Task DSL supports the concept of a split, to let you do just that. The task definition DSL supports a concept of a split that lets you launch multiple task apps at the same time. Each split contains a list of tasks that are contained within the less than < and greater than > symbol and delimited by twp pipe symbols (||).
For example, if we wanted to launch three tasks at the same time, the DSL would look like:

<task-a || task-b || task-c>

Now we can create a composed task that contains both a split and a transition, to show the possibilities. To create your split graph sample by using the Spring Cloud Data Flow UI, click the Tasks tab on the left-hand side of the dashboard and then click the CREATE TASK button at the top of the page. Now copy the expression below and paste it in the text box at the top of the page:

<task-a || task-b || task-c>  && transition-sample 'FAILED' -> task-d 'COMPLETED' -> task-e '*' -> task-f

It should look like the following: Transition Execution Split_Flow Now click the Create Task button at the bottom of the page. Now a dialog asks you to Confirm Task Creation. To do so, enter splitgraph as the composed task name in the Name field and press the Create the task button, as the following image shows: Transition Execution Split_Flow_Create

Select the splitgraph Composed Task Runner to be executed, as the following image shows: Transition Execution Flow SplitLaunch From the task launch page let's configure the composed task runner. This is done by clicking the EDIT button on the CTR properties under the Global column as shown below: Transition Execution Set Interval Time Prop Now:

  • Enter 1000 in the interval-time-between-checks field
  • Enter 4 into thread-core-pool-size field
  • Enter true into closecontext-enabled field

It should look something like below: Transition Execution Set Interval Time Prop Set Click the UPDATE button.

Click the EDIT button on the Application properties under the transition-sample column. Once the update dialog appears enter FOO into the exit-message row as shown below:

Transition Execution Flow Launch-Config-FOO Click the UPDATE button.

Click the LAUNCH TASK button.

Verify that all tasks were launched and that the path FOO was actually followed. To do so, click the Task executions tab on the left side of the task page: Transition Execution Flow Launch-split-LIST

In this example, we see that splitgraph-task-a, splitgraph-task-b, and splitgraph-task-c were fired simultaneously before CTR launched our transition app. We also added a new argument: --split-thread-core-pool-size=4. It basically states that the composed task runner can run four apps simultaneously.

Arguments and Properties

Again, what is all that stuff I put in the command line? So, for this example we wanted to show how to use both command line arguments and properties. We used the arguments to establish the properties for the Composed Task Runner:

  1. interval-time-between-checks=1000 states that the Composed Task Runner will wait one second between checks to make sure that a task is complete (the default is 10 seconds).
  2. split-thread-core-pool-size=4 states that we want up to four simultaneous tasks to run at the same time.
  3. closecontext-enabled=true states that we want the Spring context to close when the Composed Task Runner.

When using split you must set the spring.cloud.task.closecontext-enabled property as shown above.

Configuring Your Split

In the example shown in the preceding section, we configured the behavior of our split in the composed task by using the spring.cloud.task.closecontext-enabled and split-thread-core-pool-size properties. You can also use the following properties when you use splits:

  • spring.cloud.task.closecontext-enabled: When using splits, this property is required to be set to true because, otherwise, the context does not close (because threads were allocated to support the split).
  • split-thread-core-pool-size: Establishes the initial number of threads required for the splits in the composed task. Each task app contained in a split requires a thread in order to execute. (Defaults to 1)
  • split-thread-max-pool-size: The maximum number threads to be allocated.
  • split-thread-queue-capacity: The number of tasks that should be enqueued if all threads are in use before a new thread is allocated.

Basic Split Sizing

The simplest configuration for splits is to set the split-thread-core-pool-size property. You want to look at your graph and count the split that has the largest number of task apps. This is the number of threads you need. To set the thread count, use the split-thread-core-pool-size property (defaults to 1). So, for example, a definition like: <AAA || BBB || CCC> && <DDD || EEE> would require a split-thread-core-pool-size of 3. This is because the largest split contains three task apps. A count of 2 would mean that AAA and BBB would run in parallel, but CCC would wait until either AAA or BBB finished. Then DDD and EEE would run in parallel.

Restarting Composed Task Runner when task app fails

Composed tasks in Spring Cloud Data Flow let you re-launch the failed composed task in cases where a task app fails. A task app in the workflow is considered failed when the application returns a non-zero exitCode.

Detecting a failed composed task

Once a composed task is launched, an application named Composed Task Runner manages the execution of the composed task. Since the Composed Task Runner is built using Spring Batch, Spring Cloud Data Flow uses the Job Executions page to track the success or failure of a composed task's execution.

In the case that the composed task job that manages the workflow fails, the associated exit code of the Command Line Runner will be 0. This is the default boot behavior for batch jobs. However, if you require an exit code of 1 if the composed job fails, then set the spring.cloud.task.batch.fail-on-job-failure property for the composed task runner to true.

Example

In the following example, we have a simple conditional execution composed task:

task-a && task-b && task-c

Assume we have created a composed task named my-composed-task and that we now want to launch it by using the UI:

  1. Launch it by pressing the play button, as the following image shows: Restart Composed Task
  2. When the launch page appears press the LAUNCH TASK button.
  3. Once my-composed-task has completed executing, we can see that task-b was marked ERROR, meaning the application returned a non-zero exitCode. We can verify this by clicking the Executions tab at the top of the page and viewing the task executions. Note that my-composed-task-task-b has been marked with an exit code of 1. This means that this task app returned a non-zero exit code, which stopped the composed task execution.
    Restart_Composed_Task_Failed_Child Once we have resolved the problem that caused the failure, we can restart my-composed-task and the composed task runner identifies the task app that failed and re-runs it and then continues executing the DSL from that point.
  4. Press the Jobs tab located on the left side of the page.
  5. Now press the dropdown button by the failed my-composed-task and select Restart the job, as the following image shows: Restart Composed Task Job
  6. Once the composed task completes, we see a new job for my-composed-task that shows a status of COMPLETED. Restart Composed Task Complete
  7. Now click the Tasks tab to the left of the page and, when the Task Definition page appears, click the Executions tab at the top. Notice that you have two Composed Task Runs. The first is the failed composed task execution where task-b failed. Then, on the second execution, we see that my-composed-task Composed Task Runner started the graph at the failed task app (task-b) and completed the composed task, as the following image shows: Restart Composed Task Execution

Passing Properties

Spring Cloud Data Flow lets you pass both application and deployment properties to Composed Task Runner and to the task apps in the graph.

Passing Properties to Tasks in the Graph

You can set properties for a task in the graph in two ways:

  • Setting the property in the task definition.
  • Setting the property at composed task launch time.

Setting property in the task definition

You can set a property when writing a composed task definition. You can do so by adding adding the -- token followed by the property to the right of the task application name in the composed task definition. The following example shows how to do so:

task-a --myproperty=value1 --anotherproperty=value2 && task-b --mybproperty=value3

In the preceding example, task-a has two properties set, and task-b has a single property set.

Setting Property at Composed Task Launch Time

As demonstrated in the previous sections both deployment and application properties can be set using the builder tab on the task launch page. However, if you wish to set these properties using text you can click the Freetext tab.

Three components make up the property:

  • Property Type: Tells Spring Cloud Data Flow whether the property is either a deployment or an app type.

    • Deployment properties: Instructions to the deployer responsible for deploying the task app.
    • App properties: Properties passed directly the task app.
  • Task App Name: The label or the name of the application to which the property should be applied.
  • Property Key: The key of the property that is to be set.

The following example sets a myproperty property for a task app named task-a in a composed task named my-composed-task for the following dsl:

task-a && task-b

It would look something like the following: Property Diagram

Similarly if we want to pass a deployer property, the format would remain the same except that the property type would deployer. For example, we need to set the kubernetes.limits.cpu for task-a:

    deployer.task-a.kubernetes.limits.cpu=1000m

Launching a composed task and setting both app and deployer properties would be done in the following way by using Freetext tab on the UI:

  1. Launch the composed task, as the following image shows, by pressing the Launch selection next to the composed task definition that needs to be launched: Specify Which Composed Task to Launch
  2. Set the properties as follows in the Properties text box: Launch the Composed Task
  3. Now press the LAUNCH TASK button.

Properties set at launch time have a higher precedence than those set at task definition. For example, if property myproperty has been set in the composed task definition and at launch time, the value set at launch time will be used.

Passing Properties to Composed Task Runner

Three components make up the property:

  • Property Type: Tells Spring Cloud Data Flow whether the property is either a deployment or a app type.

    • Deployment properties: Instructions to the deployer responsible for deploying the task app.
    • App properties: Properties passed directly to the task app.
  • Composed Task Application Name: The name of the composed task runner app.
  • Property Key: The key of the property that is to be set.

We can launch a composed task in which we want to pass the following properties to the Composed Task Runner:

  • increment-instance-enabled: An app property that lets a single Composed Task Runner instance be re-executed without changing the parameters.
  • kubernetes.limits.cpu: A deployer property that sets the Kubernetes CPU limit for the composed task runner. Launching a composed task and setting both app and deployer properties for the Composed Task Runner is done in the following way by using the UI:
  • Launch a composed task, as the following image shows, by pressing the play button next to the composed task definition that needs to be launched: Specify Which Composed Task to Launch
  • Set the properties in the properties text box, as the following image shows: Launch the Composed Task
  • Press the LAUNCH TASK button.

Launching Composed Task using RESTful API

In this section, we provide an example of how to create and launch a composed-task.

For this example, we want to create a composed task my-composed-task with the following composed task definition:

task-a && task-b

Using curl, the command would look like:

curl 'http://localhost:9393/tasks/definitions' --data-urlencode "name=my-composed-task" --data-urlencode "definition=task-a && task-b"

The response from the Spring Cloud Data Flow Server looks something like:

HTTP/1.1 200
Content-Type: application/hal+json
Transfer-Encoding: chunked
Date: Fri, 17 Jan 2020 16:19:04 GMT

{"name":"my-composed-task","dslText":"task-a && task-b","description":"","composed":true,"lastTaskExecution":null,"status":"UNKNOWN","_links":{"self":{"href":"http://localhost:9393/tasks/definitions/my-composed-task"}}}

To verify that the my-composed-task composed task, was created we can execute a curl list:

curl 'http://localhost:9393/tasks/definitions?page=0&size=10&sort=taskName' -i -X GET

The response from the Spring Cloud Data Flow Server looks something like:

HTTP/1.1 200
Content-Type: application/hal+json
Transfer-Encoding: chunked
Date: Fri, 17 Jan 2020 16:24:39 GMT

{"_embedded":{"taskDefinitionResourceList":[{"name":"my-composed-task","dslText":"task-a && task-b","description":"","composed":true,"lastTaskExecution":null,"status":"UNKNOWN","_links":{"self":{"href":"http://localhost:9393/tasks/definitions/my-composed-task"}}},{"name":"my-composed-task-task-a","dslText":"task-a","description":null,"composed":false,"lastTaskExecution":null,"status":"UNKNOWN","_links":{"self":{"href":"http://localhost:9393/tasks/definitions/my-composed-task-task-a"}}},{"name":"my-composed-task-task-b","dslText":"task-b","description":null,"composed":false,"lastTaskExecution":null,"status":"UNKNOWN","_links":{"self":{"href":"http://localhost:9393/tasks/definitions/my-composed-task-task-b"}}}]},"_links":{"self":{"href":"http://localhost:9393/tasks/definitions?page=0&size=10&sort=taskName,asc"}},"page":{"size":10,"totalElements":3,"totalPages":1,"number":0}}

We can launch my-composed-task with the following properties for task-a:

  • app.task-a.my-prop=good
  • app.task-b.my-prop=great

Run the following curl command to launch the task:

curl 'http://localhost:9393/tasks/executions' -i -X POST -d 'name=my-composed-task&properties=app.task-a.my-prop=good,%20app.task-b.my-prop=great'

The response from the Spring Cloud Data Flow Server looks something like:

HTTP/1.1 201
Content-Type: application/json
Transfer-Encoding: chunked
Date: Fri, 17 Jan 2020 16:33:06 GMT

To verify that the my-composed-task composed task was executed, we can execute a curl list:

curl 'http://localhost:9393/tasks/executions?page=0&size=10' -i -X GET

The response from the Spring Cloud Data Flow Server looks something like:

HTTP/1.1 200
Content-Type: application/hal+json
Transfer-Encoding: chunked
Date: Fri, 17 Jan 2020 16:35:42 GMT

{"_embedded":{"taskExecutionResourceList":[{"executionId":285,"exitCode":0,"taskName":"my-composed-task-task-b","startTime":"2020-01-17T11:33:24.000-0500","endTime":"2020-01-17T11:33:25.000-0500","exitMessage":null,"arguments":["--spring.cloud.task.parent-execution-id=283","--spring.cloud.data.flow.platformname=default","--spring.cloud.task.executionid=285"],"jobExecutionIds":[],"errorMessage":null,"externalExecutionId":"my-composed-task-task-b-217b8de4-8877-4350-8cc7-001a4347d3b5","parentExecutionId":283,"resourceUrl":"URL [file:////Users/glennrenfro/project/spring-cloud-dataflow-samples/pauseasec/target/pauseasec-1.0.0.BUILD-SNAPSHOT.jar]","appProperties":{"spring.datasource.username":"******","my-prop":"great","spring.datasource.url":"******","spring.datasource.driverClassName":"org.mariadb.jdbc.Driver","spring.cloud.task.name":"my-composed-task-task-b","spring.datasource.password":"******"},"deploymentProperties":{"app.task-b.my-prop":"great"},"taskExecutionStatus":"COMPLETE","_links":{"self":{"href":"http://localhost:9393/tasks/executions/285"}}},{"executionId":284,"exitCode":0,"taskName":"my-composed-task-task-a","startTime":"2020-01-17T11:33:15.000-0500","endTime":"2020-01-17T11:33:15.000-0500","exitMessage":null,"arguments":["--spring.cloud.task.parent-execution-id=283","--spring.cloud.data.flow.platformname=default","--spring.cloud.task.executionid=284"],"jobExecutionIds":[],"errorMessage":null,"externalExecutionId":"my-composed-task-task-a-0806d01f-b08a-4db5-a4d2-ab819e9df5df","parentExecutionId":283,"resourceUrl":"org.springframework.cloud.task.app:timestamp-task:jar:2.1.0.RELEASE","appProperties":{"spring.datasource.username":"******","my-prop":"good","spring.datasource.url":"******","spring.datasource.driverClassName":"org.mariadb.jdbc.Driver","spring.cloud.task.name":"my-composed-task-task-a","spring.datasource.password":"******"},"deploymentProperties":{"app.task-a.my-prop":"good"},"taskExecutionStatus":"COMPLETE","_links":{"self":{"href":"http://localhost:9393/tasks/executions/284"}}},{"executionId":283,"exitCode":0,"taskName":"my-composed-task","startTime":"2020-01-17T11:33:12.000-0500","endTime":"2020-01-17T11:33:33.000-0500","exitMessage":null,"arguments":["--spring.cloud.data.flow.platformname=default","--spring.cloud.task.executionid=283","--spring.cloud.data.flow.taskappname=composed-task-runner"],"jobExecutionIds":[75],"errorMessage":null,"externalExecutionId":"my-composed-task-7a2ad551-a81c-46bf-9661-f9d5f78b27c4","parentExecutionId":null,"resourceUrl":"URL [file:////Users/glennrenfro/project/spring-cloud-task-app-starters/composed-task-runner/apps/composedtaskrunner-task/target/composedtaskrunner-task-2.1.3.BUILD-SNAPSHOT.jar]","appProperties":{"spring.datasource.username":"******","spring.datasource.url":"******","spring.datasource.driverClassName":"org.mariadb.jdbc.Driver","spring.cloud.task.name":"my-composed-task","composed-task-properties":"app.my-composed-task-task-a.app.task-a.my-prop=good, app.my-composed-task-task-b.app.task-b.my-prop=great","graph":"my-composed-task-task-a && my-composed-task-task-b","spring.datasource.password":"******"},"deploymentProperties":{"app.composed-task-runner.composed-task-properties":"app.my-composed-task-task-a.app.task-a.my-prop=good, app.my-composed-task-task-b.app.task-b.my-prop=great"},"taskExecutionStatus":"COMPLETE","_links":{"self":{"href":"http://localhost:9393/tasks/executions/283"}}}]},"_links":{"self":{"href":"http://localhost:9393/tasks/executions?page=0&size=10"}},"page":{"size":10,"totalElements":3,"totalPages":1,"number":0}}```

Configuring Composed Task Runner

This section describes how to configure a composed task runner.

Launching a Composed Task When Security is Enabled

As a user, you have three options for how to launch a composed task when Spring Cloud Data Flow authentication is enabled:

  • Basic authentication: Authentication using username and password.
  • User-configured access token: When launching a composed task, provide the token you wish to use at launch time by setting the dataflow-server-access-token property.
  • Data Flow-provided user token: If the dataflow-server-use-user-access-token property is set to true, Spring Cloud Data Flow auto-populates the dataflow-server-access-token property with the access token of the current logged in user.
  • Client Credentials: When launching a composed task, obtain access token via client credentials.

Basic Authentication

This example launches a composed task where the user provides the username and password. To do so:

  1. Launch a composed task, as the following image shows, by clicking the Launch selection next to the composed task definition to launch: Set User Access Token
  2. Now, from the task launch page, populate the dataflow-server-username and dataflow-server-password fields. This is done by clicking the EDIT button on the CTR properties under the Global column as shown below: Transition Execution Set Interval Time Prop Now enter the dataflow-server-username and dataflow-server-password in the appropriate fields Launch Task
  3. Click the UPDATE button.
  4. Click the LAUNCH TASK button to launch the composed task.

Using Your Own Access Token

If the composed task needs to be launched with a specific access token, pass the token by using the dataflow-server-access-token property. To do so:

  1. Launch a composed task, as the following image shows, by clicking the Launch selection next to the composed task definition to launch: Set User Access Token
  2. Now, from the task launch page, populate the dataflow-server-use-user-access-token field. This is done by clicking the EDIT button on the CTR properties under the Global column as shown below: Transition Execution Set Interval Time Prop
  3. Now enter the dataflow-server-access-token in the appropriate field. Set User Access Token
  4. Click the LAUNCH TASK button to launch the composed task.

User Access Token

In this example, we will launch a composed task where the dataflow-server-use-user-access-token is set to true. To do so:

  1. Launch a composed task, as the following image shows, by pressing the Launch selection next to the composed task definition to launch: Set User Access Token
  2. Now, from the task launch page, select Freetext Now enter the dataflow-server-use-user-access-token in the arguments field as follow: Launch Task
  3. Click the UPDATE button.
  4. Click the LAUNCH TASK button to launch the composed task.

Client Credentials

If the composed task needs to obtain its access token from an OAuth authentication service, use the following properties:

  • oauth2ClientCredentialsClientId
  • oauth2ClientCredentialsClientSecret
  • oauth2ClientCredentialsTokenUri
  • oauth2ClientCredentialsScopes

To do so:

  1. Launch a composed task, as the following image shows, by clicking the Launch selection next to the composed task definition to launch: Set User Access Token
  2. Now, from the task launch page, populate the OAuth client credential properties. This is done by clicking the EDIT button on the CTR properties under the Global column as shown below: Transition Execution Set Interval Time Prop
  3. Now enter the oauth2ClientCredentialsClientId, oauth2ClientCredentialsClientSecret, oauth2ClientCredentialsTokenUri, and oauth2ClientCredentialsScopes in the appropriate fields. Set User Access Token
  4. Click the LAUNCH TASK button to launch the composed task.

NOTE: When using client credentials specifically the OAuth2 Client Id, the following properties are ignored: dataflowServerUsername, dataflowServerPassword, and dataflowServerAccessToken.

Configure the URI for Composed Tasks

When you launch a composed task, Spring Cloud Data Flow launches the Composed Task Runner application to manage the execution of the composed task graph. It does so by parsing the Spring Cloud Data Flow task definitions and then makes RESTful API calls back to the Spring Cloud Data Flow server to launch the task definitions. As each task completes, it launches the next task definition. To set the URI that Composed Task Runner uses to make RESTful API calls, you need to set the SPRING_CLOUD_DATAFLOW_SERVER_URI property in Spring Cloud Data Flow server. The next two listings show how to do so:

  • Kubernetes specification for Spring Cloud Data Flow Server
apiVersion: apps/v1
kind: Deployment
metadata:
  ...
spec:
  ...
  template:
    ...
    spec:
      containers:
        env:
        ...
        - name: SPRING_CLOUD_DATAFLOW_SERVER_URI
          value: '<URI to your SCDF Server>'
        ...
  • Cloud Foundry Manifest for Spring Cloud Data Flow Server
---
applications:
  ...
  env:
    ...
    SPRING_CLOUD_DATAFLOW_SERVER_URI: <URI to your SCDF Server>
  services:
    ...