PostgreSQL and Jenkins

A lot of places use Jenkins nowadays, including where I now work and have previously worked. I enjoy working with Jenkins, and so I always wanted try out how this would work with PostgreSQL. Obviously, there would be some overlap with the build farm, but that's OK. The point of the build farm, after all, is to build things in many different ways to find potential problems, and this would just support that overall effort.

So I have set this up now: http://pgci.eisentraut.org/jenkins/

It's already been very helpful during the last couple of weeks that I've run this. The main point behind the effort is to automate things. These are things I do just about every day and won't have to anymore:

• build PostgreSQL
• check for compiler warnings
• run various test suites
• do this for all supported branches

These are things I do every couple of weeks and have now automated:

• check distribution building (make distcheck)
• test build of additional documentation formats
• cpluspluscheck
• check external web links in the documentation (The job for that currently appears to be reporting false positives. Use with caution.)
• test coverage reporting

Moreover, I have set up to build some extensions and external modules, which weren't regularly tested. (The build farm is making some efforts in this area, though.)

Actually, many of the checks I had set up immediately found problems: newly introduced compiler warnings, secondary documentation format builds broken, cpluspluscheck failing, broken links in the HTML documentation, various extensions no longer build with Postg reSQL 9.3devel.

But there is more cool stuff:

• There are various RSS feeds for all builds or failed buids.
• You can interact with the system on mobile devices. I use JenkinsMobi for iOS.
• You can get up to date documentation builds on a more predictable schedule.

The one thing (just about) it doesn't do is test operating system and CPU architecture portability. Jenkins comes from a Java background, where this isn't much of an issue, and so there isn't good built-in support for that sort of thing. But anyway, we have the build farm for that.

You can get the code at http://bitbucket.org/petere/pgci. The entire setup is automated with Puppet. You can fork it and set up your own (or send me your changes), or you can run it locally using Vagrant (which is what I do to test changes).

If you have any ideas, let me know (file an issue on Bitbucket). I have plans for a number of enhancements already, foremost pg_upgrade testing. Also, let me know if there are additional extensions you want tested. I have just put in a few I use myself at the moment, but other can easily be added.

Happy New Year!

psqlrc files

In PostgreSQL 9.2, you can use major-version-specific .psqlrc files, such as .psqlrc-9.2. PostgreSQL 9.2 also added the "include relative" command \ir to psql. Combining these two, you can set up psql initialization to take advantage of any new features you want without breaking the use of old psql releases.

For example, I'd like to set up psql to automatically use \x auto. But if I just put that into .psqlrc, older psql releases will complain about an unknown command. (I usually have multiple PostgreSQL versions installed, and I share dotfiles across hosts.) On the other hand, I don't want to have to duplicate the entire .psqlrc file to add one command, which is where \ir comes in.

Here is what I use, for example:

.psqlrc-9.2

\ir .psqlrc
\set QUIET yes
\set COMP_KEYWORD_CASE preserve-lower
\x auto
\unset QUIET

.psqlrc-9.3

\ir .psqlrc-9.2

pgxnclient supports tarballs and HTTP

Need to install a PostgreSQL server add-on module? The devel branch of pgxnclient now supports this type of thing:

pgxnclient install http://pgfoundry.org/frs/download.php/3274/plproxy-2.4.tar.gz

This downloads, unpacks, builds, and installs. And the module doesn't need to be on PGXN. And of course you don't have to use HTTP; a file system location will work as well. I think this can be very useful, especially during development, when not everything is available in packaged form, or even for deployment, if you don't want to bother packaging everything and have been installing from source anyway.

Funny version numbers

Often, I install a new Debian package using apt-get install, and as the progress output flies by, I wonder, Whoa!, should I really be using a piece of software with that version number?

It says a lot, after all. If I see

tool 2.4.1-2

then I (subconsciously) think, yeah, the upstream maintainers are obviously sane, the tool has been around for a while, they have made several major and minor releases, and what I'm using has seen about one round of bug fixing, and a minimal amount of tweaking by the Debian maintainer.

On the other hand, when I see

tool 7.0.50~6.5~rc2+0.20120405-1

I don't know what went on there. The original release version 7.0.50 was somehow wrong and had to be renamed 6.5? And then the 2nd release candidate of that? And then even that wasn't good enough, and some dated snapshot had to be taken?

Now, of course, there are often reasons for things like this, but it doesn't look good, and I felt it was getting out of hand a little bit.

I tried to look into this some more and find a regular expression for a reasonably sane version number. It's difficult. This is how far I've gotten: https://gist.github.com/3345974. But this still lists more than 1500 packages with funny version numbers. Which could be cause for slight concern.

Take a look at what this prints. You can't make some of that stuff up.

Tracing shell scripts with time stamps

A random tip for shell script hackers. You know that with set -x you can turn on tracing, so that every command is printed before being executed. In bash, you can also customize the output prefix by setting the PS4 variable. The default is PS4='+ '. Here is an example. I wanted to "profile" a deployment script, to see why it took so long. Ordinarily, I might have sprinkled it with date calls. Instead, I merely added

set -x
PS4='+\t '

near the top. \t stands for time stamp. (The script was already using bash explicitly, as opposed to /bin/sh.) That way, every line is prefixed by a time stamp, and the logs could easily be analyzed to find a possible performance bottleneck.

Base backup compression options

I've been looking at my PostgreSQL base backups. They are run using the traditional

tar -c -z -f basebackup.tar.gz $PGDATA/...

way (many details omitted). I haven't gotten heavily into using pg_basebackup yet, but the following could apply there just as well.

I had found some of the base backups to be pretty slow, so I dug a little deeper. I was surprised to find that the job was completely CPU bound. The blocking factor was the gzip process. So it was worth thinking about other compression options. (The alternative is of course no compression, but that would waste a lot of space.)

There are two ways to approach this:

• Use a faster compression method.

• Parallelize the compression.

For a faster compression method, there is lzop, for example. GNU tar has support for that, by using --lzop instead of -z. It gives a pretty good speed improvement, but the compression results are of course worse.

For parallelizing compression, there are parallel (multithreaded) implementations of the well-known gzip and bzip2 compression methods, called pigz and pbzip2, respectively. You can hook these into GNU tar by using the -I option, something like -I pigz. Alternatively, put them into a pipe after tar, so that you can pass them some options. Because otherwise they will bring your system to a screeching halt! If you've never seen a system at a constant 1600% CPU for 10 minutes, try these.

If you have a regular service window or natural slow time at night or on weekends, these tools can be quite useful, because you might be able to cut down the time for your base backup from, say 2 hours to 10 minutes. But if you need to be always on, you will probably want to qualify this a little, by reducing the number of CPUs used for this job. But it can still be pretty effective if you have many CPUs and want to dedicate a couple to the compression task for a while.

Personally, I have settled on pigz as my standard weapon of choice now. It's much faster than pbzip2 and can easily beat single-threaded lzop. Also, it produces standard gzip output, of course, so you don't need to install special tools everywhere, and you can access the file with standard tools in a bind.

Also, consider all of this in the context of restoring. No matter how you take the backup, wouldn't it be nice to be able to restore a backup almost 8 or 16 or 32 times faster?

I have intentionally not included any benchmark numbers here, because it will obviously be pretty site-specific. But it should be easy to test for everyone, and the results should speak for themselves.

My (anti-)take on database schema version management

There were a number of posts recently about managing schema versions and schema deployment in PostgreSQL. I have analyzed these with great interest, but I have concluded that they are all more or less significantly flawed. (Of course, most of these solutions do in fact work for someone, but they are not general enough to become canonical go-to solutions for this problem class, in my opinion.) I have developed a list of elimination criteria by which I can evaluate future developments in this area. So here are some of the things that I don't want in my schema version management system:

• Using schemas for distinguishing multiple versions (like this, but that's actually more about API versioning). That simply won't work for deploying objects that are not in schemas, such as casts, languages, extensions, and, well, schemas.

• Using extensions (like this). Well, this could work. But extensions by themselves do nothing about the core problem. They are just an SQL wrapper interface around upgrade scripts. You still need to write the upgrade scripts, order them, test them, package them. The extension mechanism might replace the, say, shell script that would otherwise run the upgrade files in a suitable order. Another issue is that extensions require access to the server file system. Changing this is being discussed as "inline extensions", but there is no consensus. This is a smaller problem, but it needs to be thought about. Also, I do need to support PostgreSQL 9.0 and earlier for little while more.

• Requiring naming each change (patch names, like this). Naming things is hard. Numbering things is easy. And how many good names are you going to still be able to come up with after 100 or so changes?

  Take a lesson from file version control systems: versions are numbers or, if it must be, hashes or the like (UUIDs have been suggested).

• Using a version control tool for tracking upgrade paths (like this). Sqitch, unlike the initial draft of this concept, doesn't actually require a version control tool for deployment, which wouldn't have worked for me, because what we ship is a tarball or a deb/rpm-type package. But it still requires you to maintain some kind of sanity in your version control history so that the tool can make sense out of it. That sounds fragile and inconvenient. The other choice appears to be writing the plan files manually without any VCS involvement, but then this loses much of the apparent appeal of this tool, and it's really no better than the "naming each change" approach mentioned above.

• Taking snapshots or the like of a production or staging or central development system. Production systems and staging systems should be off limits for this sort of thing. Central development systems don't exist, because with distributed version control, every developer has their own setups, branches, deployments, and world views.

  You could set it up so that every developer gets their own test database, sets up the schema there, takes a dump, and checks that in. There are going to be problems with that, including that dumps produced by pg_dump are ugly and optimized for restoring, not for developing with, and they don't have a deterministic output order.

• Storing the database source code in a different place or in a different manner than the rest of the source code. This includes using a version control system like mentioned above (meaning storing part of the information in the version control meta information rather than in the files that are checked into the version control system in the normal way), using a separate repository like Post Facto, or using something like the mentioned staging server.

  The source is the source, and it must be possible to check out, edit, build, test, and deploy everything in a uniform and customary manner.

• Allowing lattice-like dependencies between change sets (like most examples cited above). This sounds great on paper, especially if you want to support distributed development in branches. But then you can have conflicts, for example where two upgrades add a column to the same table. Depending on the upgrade path, you end up with different results. As your change graph grows, you will have an exploding number of possible upgrade paths that will need to be tested.

  There needs to be an unambiguous, canonical state of the database schema for a given source checkout.

• Requiring running through all the upgrade scripts for a fresh deployment (like this). There are two problems with this. First, it's probably going to be very slow. Fresh deployments need to be reasonably fast, because they will be needed for automated tests, including unit tests, where you don't want to wait for minutes to set up the basic schema. Second, it's inefficient. Over time, you might drop columns, add new columns, delete rows, migrate them to different tables, etc. If you run through all those upgrade scripts, then a supposedly fresh database will already contain a bunch of rubble, dropped attributes, dead rows, and the like.

  Therefore, the current version needs to be deployable from a script that will not end up replaying history.

• Using metalanguages or abstraction layers (like Pyrseas or Liquibase or any of the metaformats included in various web frameworks). It'd probably a good idea to check some of these out for simple applications. But my concern is whether using an abstraction layer would prevent me from using certain features. For example, look at the Pyrseas feature matrix. It's pretty impressive. But it doesn't support extensions, roles, or grants. So (going by that list), I can't use it. (It's being worked on.) And in a previous version, when I looked at it for a previous project, it didn't support foreign-data functionality, so I couldn't use it then either. And those are just the top-level things the author thought of. Actually, the Pyrseas author has gone through some effort to have almost complete coverage of PostgreSQL DDL features, so give this tool a try. But it won't be for everyone.

So, I'm going to keep looking.