In the early days of the Pyrseas project, I read about some open source projects being abandoned due to their developers losing interest or perhaps becoming involved elsewhere and thought to myself “That could never happen to me.”
Sadly, this blog has remained silent for over two years, and I haven’t done substantive development work since last September.
Still, some remain interested in Pyrseas, if gauged by the latest two issues: inquiring about consolidating/updating our documentation and porting dbtoyaml/yamltodb to other databases. So it’s appropriate that we discuss in what directions the project may turn.
Some background first.
Pyrseas was born from my experience with making structural changes to SQL databases, version control systems, the typical incompatibility between the two and the solution suggested by Andromeda.
Andromeda had a fairly simple concept: describe your database using YAML and use that to drive the process of generating SQL to make structural modifications (also, use the YAML spec to produce a basic CRUD app to make content changes—see Part 3).
The Pyrseas innovation was: rather than manually edit a YAML spec, why not create it from the Postgres catalogs? In addition, instead of using the information_schema catalog views so that the process could be nominally portable to a few other SQL databases, we opted to query the internal catalogs directly.
The Imaginarium of Peter Eisentraut
In response to a post regarding another tool that diff’d database versions, Core Team member Peter Eisentraut commented that something that “doesn’t support all PostgreSQL features” is not helpful “to help you manage your database upgrades, because it might miss important details.”
That made us reconsider the scope of Pyrseas which initially was to be limited to tables, views and perhaps functions. We decided to address the vast array of Postgres features and some releases later we managed to achieve that goal, for the most part.
A post about the proper place of business logic then led to a collaboration with Roger Hunwicks to augment the Pyrseas tools. Another discussion with Josep Martínez resulted in a preliminary capability to copy predefined data into the database.
Lilo & Sqitch (or Is diffing database versions sufficient?)
Although my Pyrseas development activity has been limited recently, I’ve continued to use Pyrseas to assist in my DBA and database development tasks. I’ve thus come to the conclusion that: no, in the most general case, diffing database versions is not sufficient to manage structural changes.
A simple example based on my original proof-of-concept schema can serve to validate this assertion. Suppose we wanted to modify the release_year column to release_date and use a DATE datetype. The RENAME may be made to work but the datatype change will require some specialized handling (e.g., an external script) that cannot be codified in a generalized “difference” approach.
When I first reviewed the other SQL schema versioning tools, Liquibase was the main exponent of the non-differencing camp (and it still seems to be going strong). About a year after that, David Wheeler came out with the first version of Sqitch and thanks to David I was able to experiment with it.
My main objection to Sqitch and Liquibase is that for the most common use cases, e.g., add a table, add a column, rewrite a view or function, etc., it seems unproductive for a DBA or developer to do the work more than once, i.e., in a development database, either via psql, using a design tool such as PgAdmin or, in some simple cases, even by editing the YAML spec directly. Recreating the SQL DDL and applying it –in the correct order– to another development, test or production database should be automated. The generated SQL should take into consideration the state of the target and, if it becomes necessary, should include generating SQL to backout changes, e.g., drop table, alter table drop column, etc., without any extra DBA or developer intervention.
My proposal to address the insufficiency of diffing database versions is to incorporate some of the ideas of the non-differencing approaches into yamltodb. The solution may be similar to what was done for dbaugment, i.e., add specialized scripts or configuration files that can control the additional processing. Admittedly, this is still very vague and will probably be third in terms of priorities, although I chose to discuss it first.