Big data support is highly experimental. Eventually this content will move to the Installation Guide.
Various components need to be installed and configured for big data support.
Data Capture Module (DCM) is an experimental component that allows users to upload large datasets via rsync over ssh.
Installation instructions can be found at https://github.com/sbgrid/data-capture-module . Note that a shared filesystem between Dataverse and your DCM is required. You cannot use a DCM with non-filesystem storage options such as Swift.
Once you have installed a DCM, you will need to configure two database settings on the Dataverse side. These settings are documented in the Configuration section of the Installation Guide:
This will allow your Dataverse installation to communicate with your DCM, so that Dataverse can download rsync scripts for your users.
The rsync script can be downloaded from Dataverse via API using an authorized API token. In the curl example below, substitute $PERSISTENT_ID with a DOI or Handle:
curl -H "X-Dataverse-key: $API_TOKEN" $DV_BASE_URL/api/datasets/:persistentId/dataCaptureModule/rsync?persistentId=$PERSISTENT_ID
Once the user uploads files to a DCM, that DCM will perform checksum validation and report to Dataverse the results of that validation. The DCM must be configured to pass the API token of a superuser. The implementation details, which are subject to change, are below.
The JSON that a DCM sends to Dataverse on successful checksum validation looks something like the contents of checksumValidationSuccess.json below:
{
"status": "validation passed",
"uploadFolder": "OS7O8Y",
"totalSize": 72
}
Here’s the syntax for sending the JSON.
curl -H "X-Dataverse-key: $API_TOKEN" -X POST -H 'Content-type: application/json' --upload-file checksumValidationSuccess.json $DV_BASE_URL/api/datasets/:persistentId/dataCaptureModule/checksumValidation?persistentId=$PERSISTENT_ID
Install Flask.
Download and run the mock. You will be cloning the https://github.com/sbgrid/data-capture-module repo.
If you see an error about not having Flask installed, install it as explained below.
On Mac, you can install Flask with:
On Ubuntu/Debian, you can install Flask with:
Once you have Flask installed, try running the dev mock script again:
This should spin up the DCM mock on port 5000.
Add Dataverse settings to use mock (same as using DCM, noted above):
At this point you should be able to download a placeholder rsync script. Dataverse is then waiting for new from the DCM about if checksum validation has succeeded or not. First, you have to put files in place, which is usually the job of the DCM. You should substitute “X1METO” for the “identifier” of the dataset you create. You must also use the proper path for where you store files in your dev environment.
Now the files are in place and you need to send JSON to Dataverse with a success or failure message as described above. Make a copy of doc/sphinx-guides/source/_static/installation/files/root/big-data-support/checksumValidationSuccess.json and put the identifier in place such as “X1METO” under “uploadFolder”). Then use curl as described above to send the JSON.
The following low level command should only be used when troubleshooting the “import” code a DCM uses but is documented here for completeness.
curl -H "X-Dataverse-key: $API_TOKEN" -X POST "$DV_BASE_URL/api/batch/jobs/import/datasets/files/$DATASET_DB_ID?uploadFolder=$UPLOAD_FOLDER&totalSize=$TOTAL_SIZE"
Info for configuring the RSAL Mock: https://github.com/sbgrid/rsal/tree/master/mocks
Also, to configure Dataverse to use the new workflow you must do the following (see also the section below on workflows):
curl -X PUT -d 'http://<myipaddr>:5050' http://localhost:8080/api/admin/settings/:RepositoryStorageAbstractionLayerUrl
Edit internal-httpSR-workflow.json and replace url and rollbackUrl to be the url of your RSAL mock.
curl http://localhost:8080/api/admin/workflows -X POST --data-binary @internal-httpSR-workflow.json -H "Content-type: application/json"
curl http://localhost:8080/api/admin/workflows
curl http://localhost:8080/api/admin/workflows/default/PrePublishDataset -X PUT -d 2
curl http://localhost:8080/api/admin/workflows/default/PrePublishDataset
curl -X DELETE http://localhost:8080/api/admin/workflows/default/PrePublishDataset
In order to see the rsync URLs, you must run this command:
curl -X PUT -d 'rsal/rsync' http://localhost:8080/api/admin/settings/:DownloadMethods
TODO: Document these in the Installation Guide once they’re final.
To specify replication sites that appear in rsync URLs:
curl http://localhost:8080/api/admin/settings/:ReplicationSites -X PUT -d "dv.sbgrid.org:Harvard Medical School:USA,sbgrid.icm.uu.se:Uppsala University:Sweden,sbgrid.ncpss.org:Institut Pasteur de Montevideo:Uruguay,sbgrid.ncpss.org:Shanghai Institutes for Biological Sciences:China"
In the GUI, this is called “Local Access”. It’s where you can compute on files on your cluster.
curl http://localhost:8080/api/admin/settings/:LocalDataAccessPath -X PUT -d "/programs/datagrid"
Dataverse can perform two sequences of actions when datasets are published: one prior to publishing (marked by a PrePublishDataset trigger), and one after the publication has succeeded (PostPublishDataset). The pre-publish workflow is useful for having an external system prepare a dataset for being publicly accessed (a possibly lengthy activity that requires moving files around, uploading videos to a streaming server, etc.), or to start an approval process. A post-publish workflow might be used for sending notifications about the newly published dataset.
Workflow steps are created using step providers. Dataverse ships with an internal step provider that offers some basic functionality, and with the ability to load 3rd party step providers. This allows installations to implement functionality they need without changing the Dataverse source code.
Steps can be internal (say, writing some data to the log) or external. External steps involve Dataverse sending a request to an external system, and waiting for the system to reply. The wait period is arbitrary, and so allows the external system unbounded operation time. This is useful, e.g., for steps that require human intervension, such as manual approval of a dataset publication.
The external system reports the step result back to dataverse, by sending a HTTP POST command to api/workflows/{invocation-id}. The body of the request is passed to the paused step for further processing.
If a step in a workflow fails, Dataverse make an effort to roll back all the steps that preceeded it. Some actions, such as writing to the log, cannot be rolled back. If such an action has a public external effect (e.g. send an EMail to a mailing list) it is advisable to put it in the post-release workflow.
Tip
For invoking external systems using a REST api, Dataverse’s internal step provider offers a step for sending and receiving customizable HTTP requests. It’s called http/sr, and is detailed below.
A Dataverse instance stores a set of workflows in its database. Workflows can be managed using the api/admin/workflows/ endpoints of the Native API. Sample workflow files are available in scripts/api/data/workflows.
At the moment, defining a workflow for each trigger is done for the entire instance, using the endpoint api/admin/workflows/default/«trigger type».
In order to prevent unauthorized resuming of workflows, Dataverse maintains a “white list” of IP addresses from which resume requests are honored. This list is maintained using the /api/admin/workflows/ip-whitelist endpoint of the Native API. By default, Dataverse honors resume requests from localhost only (127.0.0.1;::1), so set-ups that use a single server work with no additional configuration.
Dataverse has an internal step provider, whose id is :internal. It offers the following steps:
A step that writes data about the current workflow invocation to the instance log. It also writes the messages in its parameters map.
{
"provider":":internal",
"stepType":"log",
"parameters": {
"aMessage": "message content",
"anotherMessage": "message content, too"
}
}
A step that pauses the workflow. The workflow is paused until a POST request is sent to /api/workflows/{invocation-id}.
{
"provider":":internal",
"stepType":"pause"
}
A step that sends a HTTP request to an external system, and then waits for a response. The response has to match a regular expression specified in the step parameters. The url, content type, and message body can use data from the workflow context, using a simple markup language. This step has specific parameters for rollback.
{
"provider":":internal",
"stepType":"http/sr",
"parameters": {
"url":"http://localhost:5050/dump/${invocationId}",
"method":"POST",
"contentType":"text/plain",
"body":"START RELEASE ${dataset.id} as ${dataset.displayName}",
"expectedResponse":"OK.*",
"rollbackUrl":"http://localhost:5050/dump/${invocationId}",
"rollbackMethod":"DELETE ${dataset.id}"
}
}
Available variables are: