Hello Dataset- Installation- Github

torresal edited this page on May 24, 2018 · 8 revisions

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Integrating a "Hello World" Dataset Type

For definitions of terminology used, please refer to our terminology reference.

In this tutorial, we continue where we left off in integrating our first job type, Hello World. We will update our job type to generate a HySDS dataset that will be automatically ingested and catalogued into the system.

  1. On the mozart instance, navigate to the hello_world repository

    cd ~/mozart/ops/hello_world
  2. We need to author a dataset ID scheme according to the HySDS dataset specification. In this tutorial, we will use the following dataset ID scheme

    hello_world-product-<year><month><day>T<hour><minute><second>Z-<hash>

    where <year> will be replaced by a fictional observation year and likewise for <month><day><hour><minute><second> and <hash>. An example instance of this dataset ID would be

    hello_world-product-20170901T000102.021Z-a3d0x
  3. Edit the script that runs our job type

    and add code to create an instance of our dataset. The script should look like this

    Access the documentation on the specifications for the HySDS dataset JSON file and metadata JSON file for more detail. Finally, commit your change and push the update

    If your jenkins job for the master branch of your hello_world repo was configured correctly, the git push should have kicked off a rebuild of the container. If not, navigate to your ciinstance (e.g. http://:8080) and manually schedule a build

  4. Test the script by running it

    You should see the dataset directory you just created sitting there in your directory. Ensure that the fake_data.dat and the HySDS dataset and metadata JSON files were generated

  5. Now let's try to ingest this new dataset into our catalog

    You should've gotten an error that the data was not recognized

  6. Let's configure our new dataset so that it can be recognized by our HySDS cluster. Since we want to ensure all nodes in our cluster is able to recognize this new dataset, we need to make updates to the datasets.json file in ~/.sds/files. Still on mozart

    edit the datasets.json file

    and add the following dataset configuration below the dumby-product configuration

    and save.

  7. Run the following fabric command to push the update you made to the datasets.jsontemplate on mozart

    You should have output similar to the following

  8. Now let's try to ingest this new dataset into our catalog

  9. Verify that your new dataset was published to your HySDS cluster. Open up a browser and point it to your grq instance's tosca (Dataset FacetSearch) interface (e.g. https:///search). On the left panel you should see your new dataset type listed under the "dataset" facet showing 1 result

    Click on "hello_world-product" under the "dataset" facet and your result set should be constrained now to just the dataset you just ingested

  10. Now that we've verified that the new dataset is recognized by the system, let's push the updates to the rest of the system. On mozart

That's it!

Congratulations, you've integrated a new dataset type into your HySDS cluster.

To configure Autoscaling groups for your HySDS cluster, continue on to Create-AWS-Autoscaling-Group-for-Verdi.

To configure a staging area for your HySDS cluster, continue on to Create-AWS-Resources-for-Staging-Area.

 

 


 

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