After creating the post Pluggable databases for apache karaf applications I posted a link to the blog post in the karaf user mailing list, and the immediate response was, “why didn’t I just pax-jdbc-config instead?“.
The answer to that is that I didn’t know about pax-jdbc-config. I started using pax-jdbc in the summer of 2016, and started using apache karaf in the autumn of 2016 and pax-jdbc-config didn’t exist then (or at least: not as complete and usable as it became in 2017), and any announcement that has gone past since then, has not registered.
But I completely agree with the sentiment expressed in the pax-jdbc-config wiki page:
For some cases you want the actual DataSource available as a service in OSGi. Most tutorials show how to do this using blueprint to create a DataSource and publish it as a service. The problem with this approach is that you have to create and deploy a blueprint file for each DataSource and the blueprint is also Database specific.
So I decided to try pax-jdbc-config out.
First out was the sonar-collector. This is the smallest web application I have, that is using JDBC and liquibase. Properly speaking, it isn’t a web application, but it uses web application technology. It is a single servlet that serves as a webhook that sonarqube can call after completing analysis of a software project, and records some key sonarqube metrics in a single database table. The purpose of sonar-collector was to be able to aggregate statistics over time to be able to show a gradual improvement of a set of applications. I.e. to show that each release was a little bit better instead of a little bit worse, according to the metrics. And since sonarqube by itself didn’t save those metrics in an easily accessible form, we started out by manually collecting metrics, applications, versions and dates in a spread sheet.
Since collecting numbers manually and punching them back into a different program is boring, I looked into what possibilities there were to extract the numbers from sonarqube. And I found that the simplest way to collect them was to collect them each the time sonarqube completed an analysis. So sonar-collector is a single servlet implemented as an OSGi declarative services component, that registers as a servlet OSGi service with the OSGi web whiteboard, and on each invocation collects the metrics of the sonar analysis invoking the servlet, and writes the metrics as a new row in a database table.
The first version of sonar-collector used PostgreSQL and was pretty much tied to PostgreSQL, even though it didn’t do anything PostgreSQL specific: the liquibase schema setup and the single insert statement should work fine on any DBMS supported by liquibase (basicallly all of the DBMSes supported by JDBC), and JDBC.
The reason the first version of sonar-collector was tied to PostgreSQL, was that it had no way to qualify what DataSourceFactory the component should receive. And since sonar-collector’s karaf feature loaded and started the PostgreSQL DataSourceFactory (by having the postgresql JDBC driver as a compile scope maven dependency), PostgreSQL was pretty much all it got.
The changes to adapt sonar-collector to using pax-jdbc-config, were:
- Removal of all of the Java code and tests releated to connecting to a JDBC source
- Changing the DS injection of an unqualified DataSourceFactory OSGi sevice, with an application specific DataSource OSGi service
- Add the default pax-jdbc-configuration to the template feature.xml file
What didn’t need to be changet was the way the sonar-collector runs liquibase. The servlet ran the liquibase scripts from the servlet DS component activate method, since this method only will be called when a valid, working, connected DataSource is available.
How much code actually was removed was a bit of an eye opener, because I did think of the JDBC connection code as “a little bit of boilerplate, but not all that much”. But if you try to make configuration option configuration robust, and then try to get a good test coverage of the code, handling all sorts of exceptions, then you end up with quite a few lines of java code.
In any case, I was satisfied with the end result: I removed a lot of Java code, and ended up with a sonar-collector that can use any RDBMS that is supported by JDBC to store the results.
The next candidate for switching to pax-jdbc-config was authservice.
Authservice is a webapp, that:
- Can provide nginx with forms-based authentication
- Can provide other webapps with apache shiro-based authentication and role-based authorization
- A JDBC user/role/permission database with:
- a react-redux based administration user interface
- “self-service” web pages (static HTML styled with bootstrap) for letting users change their passwords, name and email
- an OSGi service other webapps can use to get information from the user database and modify the user database
In theory the JDBC based user database could be swapped with an LDAP service, using an LDAP realm and wrapping the UserManagementService over admin operations, and be used with both the admin UIs of authservice and other webapps using authservice, without any of them feeling any difference. We’ll see if we ever get there.
The authservice webapp has two databases:
- a derby in-memory database initialized with dummy data, and used for unit tests, integration tests, and for demonstrating the application
- a PostgreSQL database for use by the application in production
Three bundles of authservice were related to database connection and setup:
- an OSGi library bundle containing the liquibase scripts for the database schema as classpath resources and some code to load and run the scripts (in OSGi, code that wishes to load resources from the classpath, needs to reside in the same bundle as the resources)
- a bundle with a DS component expecting a DataSourceFactory OSGi service injection, creating an in-memory derby database, setting up the schema and adding dummy data, and finally exposing an AuthserviceDatabaseService OSGi service
- a bundle with a DS component expecting a PostgreSQL specific DataSourceFactory OSGi service injection, connecting to a PostgreSQL server, setting up the schema and adding some initial data (currently none here)
The OSGi library bundle could be left as it was.
The changes to adapt authservice to pax-jdbc-config, was:
- Rename the bundles to something more describing
- Rename the DS components to something more describing, remove all of the JDBC connection setup code, remove the schema setup code from the activate method, and expose the PreHook OSGi service:
- Add a feature pax-jdbc-config config to the template feature.xml files:
After the changes the application consisted of the same number of OSGi bundles, but now the application is no longer tied to derby and PostgreSQL, but can be configured at runtime to use different DBMSes.
The final application to modify, was an application called “ukelonn”, which was used to register performed household chores, and payment of the resulting allowance.
The application was similar in structure to the authservice application. Like authservice. the allowance application has both a derby test database and a PostgreSQL production database. And also like authservice, the allowance application uses liquibase to create the schemas and populate the database with initial data.
However, it had a complicating factor that was that ukelonn’s application specific DatabaseService subtype, was also used to return DBMS specific SQL for PostgreSQL and derby for aggregating over years and months.
Using aggregating over years as an example (i.e. use the simplest query as the example), in derby it looked like this:
select sum(t.transaction_amount), YEAR(t.transaction_time) from transactions t join transaction_types tt on tt.transaction_type_id=t.transaction_type_id join accounts a on a.account_id=t.account_id where tt.transaction_is_work and a.username=? group by YEAR(t.transaction_time) order by YEAR(t.transaction_time)
and in the PostgreSQL it looked like this:
select sum(t.transaction_amount), extract(year from t.transaction_time) as year from transactions t join transaction_types tt on tt.transaction_type_id=t.transaction_type_id join accounts a on a.account_id=t.account_id where tt.transaction_is_work and a.username=? group by extract(year from t.transaction_time) order by extract(year from t.transaction_time)
The difference in SQL syntax was handled by letting the derby DatabaseService and the PostgreSQL DatabaseService return different strings from the sumOverYearQuery() method, and a grouping over year and month, was handled in the same way in the sumOverMonthQuery() method.
I pondered various ways of doing this, including creating two extra bundles to be able to provide this for derby and PostgreSQL, but that would have meant that any new DBMS introduced would need to get its own bundle, and that would raise the threshold for actually using a different DBMS considerable.
The solution I landed on was to let liquibase create different views depending on the DBMS used, and then do a select over the view in the business logic class.
The changes to adapt ukelonn to pax-jdbc-config, then was:
- Add the new DBMS specific views
- Change the business logic to use the new views instead of asking the database service for the queries to use
- Rename the database service bundles to something more describing for liquibase hooks
- Rename the DS components for the database services to something more describing for liquibase hooks, expose the PreHook OSGi service and remove the JDBC connection code:
- Add pax-jdbc-config based features to the feature repositories of the test and production liquibase hooks
- Use the pax-jdbc-config based features when composing the application
- Using pax-jdbc-config allows me to use different DBMSes than the default derby and PostgreSQL DBMSes, without changing any Java code: I need to add the JDBC driver for the RDBMS and need to change the pax-jdbc-config configuration to use the correct DataSourceFactory and set the JDBC connection properties (url, username and password)
- Replacing the old way of setting up databases with pax-jdbc-config let me remove a lot of Java code, both actual code for doing the JDBC connections, and probably three times as much code for the unit tests of the JDBC connection code
- Using liquibase to set up different views for different DBMSes where the syntax varies was a lot cleaner and easier to test than the previous approach (i.e. having the DatabaseService implementations return different SQL strings for different databases)