Advanced Installation
Advanced installations are not officially supported but here we are at least documenting some tips and tricks that you might find helpful. You can find a diagram of an advanced installation in the Preparation section.
Contents:
Multiple App Servers
You should be conscious of the following when running multiple app servers.
Only one app server can be the dedicated timer server, as explained in the Dataverse Installation Application Timers section of the Admin Guide.
When users upload a logo or footer for their Dataverse collection using the “theme” feature described in the Dataverse Collection Management section of the User Guide, these logos are stored only on the app server the user happened to be on when uploading the logo. By default these logos and footers are written to the directory
/usr/local/payara5/glassfish/domains/domain1/docroot/logos
.When a sitemap is created by an app server it is written to the filesystem of just that app server. By default the sitemap is written to the directory
/usr/local/payara5/glassfish/domains/domain1/docroot/sitemap
.If Make Data Count is used, its raw logs must be copied from each app server to single instance of Counter Processor. See also :MDCLogPath section in the Configuration section of this guide and the Make Data Count section of the Admin Guide.
Dataset draft version logging occurs separately on each app server. See Edit Draft Versions Logging section in Monitoring of the Admin Guide for details.
Password aliases (
dataverse.db.password
, etc.) are stored per app server.
Detecting Which App Server a User Is On
If you have successfully installed multiple app servers behind a load balancer you might like to know which server a user has landed on. A straightforward solution is to place a file called host.txt
in a directory that is served up by Apache such as /var/www/html
and then configure Apache not to proxy requests to /host.txt
to the app server. Here are some example commands on RHEL/derivatives that accomplish this:
[root@server1 ~]# vim /etc/httpd/conf.d/ssl.conf
[root@server1 ~]# grep host.txt /etc/httpd/conf.d/ssl.conf
ProxyPassMatch ^/host.txt !
[root@server1 ~]# systemctl restart httpd.service
[root@server1 ~]# echo $HOSTNAME > /var/www/html/host.txt
[root@server1 ~]# curl https://dataverse.example.edu/host.txt
server1.example.edu
You would repeat the steps above for all of your app servers. If users seem to be having a problem with a particular server, you can ask them to visit https://dataverse.example.edu/host.txt and let you know what they see there (e.g. “server1.example.edu”) to help you know which server to troubleshoot.
Please note that Network Ports under the Configuration section has more information on fronting your app server with Apache. The Shibboleth section talks about the use of ProxyPassMatch
.
Licensing
Dataverse allows superusers to specify the list of allowed licenses, to define which license is the default, to decide whether users can instead define custom terms, and to mark obsolete licenses as “inactive” to stop further use of them. These can be accomplished using the native API and the :AllowCustomTermsOfUse setting. See also Configuring Licenses.
Standardizing Custom Licenses
In addition, if many datasets use the same set of Custom Terms, it may make sense to create and register a standard license including those terms. Doing this would include:
Creating and posting an external document that includes the custom terms, i.e. an HTML document with sections corresponding to the terms fields that are used.
Defining a name, short description, URL (where it is posted), and optionally an icon URL for this license.
Using the Dataverse API to register the new license as one of the options available in your installation.
Using the API to make sure the license is active and deciding whether the license should also be the default.
Once the license is registered with Dataverse, making an SQL update to change datasets/versions using that license to reference it instead of having their own copy of those custom terms.
The benefits of this approach are:
usability: the license can be selected for new datasets without allowing custom terms and without users having to cut/paste terms or collection administrators having to configure templates with those terms
efficiency: custom terms are stored per dataset whereas licenses are registered once and all uses of it refer to the same object and external URL
security: with the license terms maintained external to Dataverse, users cannot edit specific terms and curators do not need to check for edits
Once a standardized version of you Custom Terms are registered as a license, an SQL update like the following can be used to have datasets use it:
UPDATE termsofuseandaccess
SET license_id = (SELECT license.id FROM license WHERE license.name = '<Your License Name>'), termsofuse=null, confidentialitydeclaration=null, t.specialpermissions=null, t.restrictions=null, citationrequirements=null, depositorrequirements=null, conditions=null, disclaimer=null
WHERE termsofuseandaccess.termsofuse LIKE '%<Unique phrase in your Terms of Use>%';
Optional Components
Standalone “Zipper” Service Tool
As of Dataverse Software 5.0 we offer an experimental optimization for the multi-file, download-as-zip functionality.
If this option (:CustomZipDownloadServiceUrl
) is enabled, instead of enforcing the size limit on multi-file zipped
downloads (as normally specified by the option :ZipDownloadLimit
), we attempt to serve all the files that the user
requested (that they are authorized to download), but the request is redirected to a standalone zipper service running
as a cgi-bin executable under Apache. This moves these potentially long-running jobs completely outside the Application Server (Payara), and prevents worker threads from becoming locked serving them. Since zipping is also a CPU-intensive task, it is possible to have
this service running on a different host system, freeing the cycles on the main Application Server. (The system running
the service needs to have access to the database as well as to the storage filesystem, and/or S3 bucket).
Please consult the README at scripts/zipdownload in the Dataverse Software 5.0+ source tree for more information.
To install:
Follow the instructions in the file above to build
zipdownloader-0.0.1.jar
. Please note that the package name and the version were changed as of the release 5.10, as part of an overall cleanup and reorganization of the project tree. In the releases 5.0-5.9 it existed under the nameZipDownloadService-v1.0.0
. (A pre-built jar file was distributed under that name as part of the 5.0 release on GitHub. Aside from the name change, there have been no changes in the functionality of the tool).Copy it, together with the shell script
cgi-bin/zipdownload
to thecgi-bin
directory of the chosen Apache server (/var/www/cgi-bin
standard).Make sure the shell script (
zipdownload
) is executable, and edit it to configure the database access credentials. Do note that the executable does not need access to the entire Dataverse installation database. A security-conscious admin can create a dedicated database user with access to just one table:CUSTOMZIPSERVICEREQUEST
.
You may need to make extra Apache configuration changes to make sure /cgi-bin/zipdownload
is accessible from the outside.
For example, if this is the same Apache that’s in front of your Dataverse installation Payara instance, you will need to
add another pass through statement to your configuration:
ProxyPassMatch ^/cgi-bin/zipdownload !
Test this by accessing it directly at <SERVER URL>/cgi-bin/download
. You should get a 404 No such download job!
.
If instead you are getting an “internal server error”, this may be an SELinux issue; try setenforce Permissive
.
If you are getting a generic Dataverse collection “not found” page, review the ProxyPassMatch
rule you have added.
To activate in your Dataverse installation:
curl -X PUT -d '/cgi-bin/zipdownload' http://localhost:8080/api/admin/settings/:CustomZipDownloadServiceUrl
Installing External Metadata Exporters
As of Dataverse Software 5.14 Dataverse supports the use of external Exporters as a way to add additional metadata export formats to Dataverse or replace the built-in formats. This should be considered an experimental capability in that the mechanism is expected to evolve and using it may require additional effort when upgrading to new Dataverse versions.
This capability is enabled by specifying a directory in which Dataverse should look for third-party Exporters. See dataverse.spi.exporters.directory.
See Metadata Export Formats for details about how to develop new Exporters.
An minimal example Exporter is available at https://github.com/gdcc/dataverse-exporters. The community is encourage to add additional exporters (and/or links to exporters elsewhere) in this repository. Once you have downloaded the dataverse-spi-export-examples-1.0.0.jar (or other exporter jar), installed it in the directory specified above, and restarted your Payara server, the new exporter should be available.
The example dataverse-spi-export-examples-1.0.0.jar replaces the JSON
export with a MyJSON in <locale>
version
that just wraps the existing JSON export object in a new JSON object with the key inputJson
containing the original
JSON.(Note that the MyJSON in <locale>
label will appear in the dataset Metadata Export download menu immediately,
but the content for already published datasets will only be updated after you delete the cached exports and/or use a
reExport API call (see Batch Exports Through the API).)