The support for Apache Atlas has been added to Talend MapReduce Jobs and Spark Jobs.
If you are using Hortonworks Data Platform V2.4 onwards to run your Jobs and Apache Atlas has been installed in your Hortonworks cluster, you can make use of Atlas to trace the lineage of given data flow to discover how this data was generated by a MapReduce or Spark Job, including the components used in this Job and the schema changes between the components.
If you are using Hortonworks Data Platform V2.4, the Studio supports Atlas 0.5 only; if you are using Hortonworks Data Platform.V2.5, the Studio supports Atlas 0.7 only.
For example, assume that you have designed the following Spark Batch Job and you want to generate lineage information about it in Atlas:
In this Job, tRowGenerator is used to generate the input data, tMap and tSortRow to process the data and the other components to output data into different formats.
You need to proceed as follows:
Click Run to open its view and then click the Spark configuration tab (For a MapReduce Job, the tab to be used is Hadoop configuration).
From the Distribution list, select Hortonworks and from the Version list, select Hortonworks Data Platform V2.5.0 for example.
Then the Use Atlas check box is displayed.
With this option activated, you need to set the following parameters:
Atlas URL : enter the location of the Atlas to be connected to. It is often http://name_of_your_atlas_node:port
In the Username field and the Password field, enter the authentication information for access to Atlas.
Set Atlas configuration folder : if your Atlas cluster contains custom properties such as SSL or read timeout, select this check box, and in the displayed field, enter a directory in your local machine, then place the atlas-application.properties file of your Atlas in this directory. This way, your Job is enabled to use these custom properties.
You need to ask the administrator of your cluster for this configuration file. For further information about this file, see the Client Configs section in Atlas configuration.
Die on error: select this check box to stop the Job execution when Atlas-related issues occur, such as connection issues to Atlas.
Otherwise, leave it clear to allow your Job to continue to run.
Till now, the connection to Atlas has been set up. The time when you run this Job, the lineage will be automatically generated in Atlas.
Note that you still need to configure the other parameters in the Spark configuration tab in order to successfully run the Job. For further information, see the example for a Spark Batch Job in the Getting Started Guide of the Studio.
When the execution of the Job is done, perform a search in Atlas for the lineage information written by this Job and read the lineage there.
In Atlas, the lineage written by a Job consists of two types of entities:
the Job itself
the components in the Job that are using data schemas, such as tRowGenerator or tSortRow. The connection or configuration components such as tHDFSConfiguration are not taken into account since these components do not use schemas.
So the example Job generates 6 entities: one for the Job and five for the components, and automatically adds three different tags to these entities:
Talend for all the entities generated by the Job
TalendComponent for all the component entities.
TalendJob for all the Job entities.
You can directly click one of these tags in Atlas to display the corresponding entities.
For example, you can click TalendJob to show a list of Job entities logged in Atlas and select a Job to see the lineage information of this Job. The following image shows how the data flow is handled in the Job used as example: