Redesigning the Clouttery database

I spent the past week, the last one of my winter break, redesigning how the Clouttery server stores data.

The Clouttery server, which is written in Go, was using a simple key-value store (Bolt). I slowly came to the realization that some of the features on the roadmap would be kind of hard to implement using Bolt; that the nested buckets structure used with Bolt was too limiting, by forcing a hierarchy on the data, when sometimes it could be useful to interpret it in other ways. For example, sometimes it could be useful to look at all the battery log entries from all users; with the database structure I had, that required looking into each user’s bucket separately, and within those, into each device separately.

The databases course I took last semester forced me to get my hands very dirty with SQL, and after seeing the benefits, I decided to move to a relational database.

Another reason for moving was that Bolt can’t scale (no replication, it’s meant for use by a single app, like SQLite), and while the server software is not yet ready to be clustered, moving away from Bolt (and, in general, uncoupling the server from the database) is a giant step towards the goal of being able to scale the server to multiple nodes. I had known for long that I had to use something other than Bolt if I wanted to make the server distributed, I just wasn’t sure whether to move to a relational database, another barebones key-value store, or some amalgamation of solutions involving specialized time series databases or what-have-you.

The database can now be accessed transparently by multiple applications, which means that, for example, in case I want to do some complex analysis on the battery histories, I no longer have to stuff that code into the server. I can even use a language other than Go, like Python, which I really don’t like, but has many libraries for data analysis.

I tried to use CockroachDB (and I can’t stress the terribleness of that name enough). At some point, the server was mostly ready to work with it, and it was time to import the data from the Bolt database. My code migrated all data in a single transaction, that was rolled back in the case of errors – that way, as I stumbled upon problems and general incompleteness in my migration code, I did not have to be constantly dropping and recreating the database, as with every failure the database would be always supposedly in a pristine state, with all the empty tables waiting for data.

Let’s just say things were not as smooth as I was hoping. On my laptop with an aging but still plenty fast i7, 8 GB of RAM and a SSD, data would get into CockroachDB relatively fast… but no matter if the transaction was committed or rolled back, once I tried to perform any query – basically any query, even if just counting the amount of users (about 40), would make CockroachDB’s RAM usage skyrocket, to the point where the whole system just hanged for seconds at a time, due to how much swapping was going on.

So I decided to scrap CockroachDB and go with plain old PostgreSQL. Given that the SQL supported by the former is relatively similar to what PostgreSQL supports, changing the queries to work with Postgres was not too hard. The most annoying part is the lack of support of PostgreSQL for the UPSERT command, which in CockroachDB and other databases, behaves like a INSERT when there’s no uniqueness conflict, and like a UPDATE when there’s a conflict (in which case it will update all the other columns). I had about ten UPSERTs that had to be rewritten as INSERT … ON CONFLICT (…) DO UPDATE SET – followed by all the columns to update. Ugh.

Importing data into Postgres was noticeably faster than into CockroachDB, and most importantly everything kept working fine after about a million entries were in the battery history table. And yes, everything was still inserted in a single transaction.

I took the opportunity to perform some long-needed changes to the data types used by the server. Making sure Clouttery clients kept receiving data with the formats and semantics they were expecting was a bit of a challenge, but very easy in the grand scheme of things.

As a very nice bonus, the server now does transactions properly. Previously, for a single API or website request, multiple Bolt transactions could be made. If something went wrong with one of the latter transactions, that one would be rolled back and no more transactions would be performed, but the changes done by previous ones would stay – like most databases, Bolt doesn’t let you rollback a committed transaction. Obviously, this could result in an inconsistent state.

Now, and after changing most functions in the server code to accept what can be described as a “transaction node”, each API request, web console request, or admin command works in a single transaction. Either there’s no error and everything goes through, or everything is rolled back. No more inconsistent data. sqalx was the library used to implement this.

The changes were pushed to production about two hours ago – after extensive testing on the staging environment, which unfortunately didn’t catch all the bugs. To identify problems, there’s nothing like dozens of devices running different clients and submitting different data to your server…

A few hotfixes later, everything appears to be working fine, but I’ll be keeping a close eye on the logs where, hopefully, all errors are logged. I say “hopefully”, because during testing I found out that the error return values (in Go, errors are values) from some of my own functions were not being logged, and some were completely ignored…

It would be great if over the next few days users could pay a bit more attention to the behavior of Clouttery, namely making sure that battery histories are updating as they should, and that notifications are generated when they should, according to their settings.

I’m probably a bit too much proud of this – at least, until I find a horrendous bug. This is how things should have been from the start, but at the same time, when I started this project, I did not know enough about relational database design to even do a mediocre job. So I went the easy, “no SQL” route and just used Bolt, which allowed me to get to something that worked, relatively quickly. And now I’m glad I could turn it into something better after about 60 hours of work…

I barely have time to work on Clouttery, and it becomes less and less of a commercially viable project as time goes by. It’s one of those projects that seems to never leave Beta status, and not for good reasons. But oh boy, the things I learn…

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