This repository includes a sub directory per bucket, in which a metadata file centralizes object-related-information: bucket name, object name, object kind,.. If the "studio_template" section is specified, the object/workflow is also considered as a studio template.

The aim of this project is to centralize all proactive workflows and other related objects (scripts, images, etc). The workflows from the ProActive Examples project are pushed to Catalog storage inside proactive.

Please run next command: gradlew clean zip or gradlew clean build This will generate the proactive-examples.zip file inside project's build folder.

Copy the genarated proactive-examples.zip file to your Scheduler_Distribution_Path/samples directory. Start your proactive distribution. From this point everything should work ok. During scheduling startup: the proactive-examples.zip archive will be extracted to proactive-examples folder. On the next step the special groovy script will automatically push the workflows from proactive-examples folder to Catalog storage. If you need to retest the extracting and loading of proactive-examples, please remove proactive-examples folder. Also to test the filling of catalog storage don't forget to clean database.

1) Scheduler_Distribution_Path is the path to your local Proactive distribution folder. You need to `cd` to this folder.
2) rm -fr samples/proactive-examples*
3) rm -fr data/*
4) you need to `cd` into your locally cloned proactive-examples project folder
5) ./gradlew clean zip
6) cp build/proactive-examples.zip Scheduler_Distribution_Path/samples/
7) go back to Scheduler_Distribution_Path and start proactive-server
8) ./Scheduler_Distribution_Path/bin/proactive-server

1. Create a folder with the desired package name (e.g. TextAnalysis).

2. Add a METADATA.json file into the package (e.g. TextAnalysis/METADATA.json).

3. Insert the following JSON structure into the METADATA.json file:

{
	"metadata": {
		"slug": "textanalysis",
		"name": "Text Analysis",
		"short_description": "Text analysis with machine learning and deep learning on Docker",
		"author": "ActiveEon's Team",
		"tags": ["Samples", "Machine Learning", "Text Analysis", "Big Data", "Analytics", "Deep Learning"],
		"version": "1.0"
	},
	"catalog" : {
		"bucket" : "machine-learning",
		"objects" : [
			{
				"name" : "text_analysis",
				"metadata" : {
					"kind": "Workflow/standard",
					"commitMessage": "First commit",
					"contentType": "application/xml"
				},
				"file" : "resources/catalog/text_analysis.xml"
			}
		]
	}
}

3.1) Update the metadata fields:

• • metadata->slug - compact name of the package.
• • metadata->name - name of the package.
• • metadata->short_description - short description of the package.
• • metadata->tags - key works of the package.

3.2) Update the catalog fields:

• • catalog->bucket - Set the name of the bucket(s) for this package. A package can be installed in one or multiple buckets. Therefore, the bucket name can be a String value as in the example above (i.e "Machine_Learning") or a JSON array value as in ["Bucket_1","Bucket_2","Bucket_X"].
• • catalog->objects - Add an object of each workflow of the package.

An example of a catalog object that represents a workflow:

{
				"name" : "text_analysis",
				"metadata" : {
					"kind": "Workflow/standard",
					"commitMessage": "First commit",
					"contentType": "application/xml"
				},
				"file" : "resources/catalog/text_analysis.xml"
			}

• • object->name - Name of the workflow.
• • object->file - Relative path of the XML file of the workflow.

4. Add the XML file(s) of the workflow(s) into resources/catalog/ inside your package folder (e.g. TextAnalysis/resources/catalog/text_analysis.xml).

5. By default all new buckets will be added after all existing buckets inside catalog. So no need by default to add bucket name to ordered_bucket_list file.

But if you need to have strict order of buckets, then please update ordered_bucket_list by adding the package name (order by name). The whole list should be stored as 1 line without any spaces or end line character.

6. Update build.gradle by finding task zip (type: Zip) function and adding an include for your package (e.g. include 'TextAnalysis/**'). Example:

task zip (type: Zip){
    archiveName="proactive-examples.zip"
    destinationDir = file('build/')
    from '.'
    include 'AWS/**'
    include 'Clearwater/**'
    include 'CloudAutomationTemplate/**'
    include 'Cron/**'
    include 'DockerBasics/**'
    include 'DockerSwarm/**'
    include 'Email/**'
    include 'FileFolderManagement/**'
    include 'FinanceMonteCarlo/**'
    include 'GetStarted/**'
    include 'HDFS/**'
    include 'HDFSOrchestration/**'
    include 'ImageAnalysis/**'
    include 'JobAnalysis/**'
    include 'LogAnalysis/**'
    include 'MLBasics/**'
    include 'MLNodeSource/**'
    include 'OpenStack/**'
    include 'RemoteVisualization/**'
    include 'Spark/**'
    include 'SparkOrchestration/**'
    include 'Storm/**'
    include 'TextAnalysis/**'
    include 'TriggerTemplate/**'
    include 'TwitterApi/**'
    include 'WebNotification/**'
    include 'ordered_bucket_list'
}

All the workflows added in proactive-examples project have to follow the next rules:

. Every single workflow of packages distributed by Activeeon (as all the workflows from proactive-examples), MUST HAVE a Workflow Generic Information "workflow.icon" with a meaningful Icon . URL of this icon MUST reference a local file . If a workflow has a single task, this task MUST HAVE a Task Generic Information "task.icon" with the same icon as the Workflow

• In case if workflow is not corresponding to specified rules: the test inside the proactive-examples project will fail.

That's all!