Month: January 2011

A few months ago we added the implicit tracker:modified property to all resources. This property is an auto-increment. It used to be that the property was incremented on ~ each SQL update-query that happens. The value is stored per resource.

We are now changing this to be per transaction. A transaction in Tracker is one set of SPARQL-Update INSERT or DELETE queries. You can do inserts and deletes about multiple resources in one such sentence (a sentence can contain multiple space delimited Update queries). An exception is everything related to ontology changes. These ontology changes get the first increment as their value for tracker:modified. This is also for ontology changes that happen after the initial ontology transaction (at the first start, is this first transaction made). The exception is made for supporting future ontology changes and the possibly needed data conversions.

The per-resource tracker:modified value is useful for application’s synchronization purposes: you can test your application’s stored tracker:modified value against the always increasing (w. exception at int. overflow) Tracker’s tracker:modified value to know whether or not your version is older.

The reason why we are changing this to per-transaction is because this way we can guarantee that the value will be restored after a journal replay and/or a backup’s restore without having to store it in either the journal nor the backup. This means that we now guarantee the value being restored without having to change either the backup’s format nor the journal’s format.

Having a persistent journal we actually make a simple copy of the journal to deliver you a backup in a fast file-copy. But let this deception be known only by the people who care about the implementation. Sssht!

We’re already rotating and compressing the rotated chunks for reducing the journal size. We’re working on not journaling data that is embedded in local files this week. A re-index of that local file will re-insert the data anyway. This will significantly reduce the size of the journal too.

It has been a long time since we wrote propaganda about the Tracker project. That has a lot to do with both the holiday-season and the fact that we’re preparing for a stable release. This means that we are increasingly reluctant to new features.

We still made quite some progress, though. We for example ported almost everything from dbus-glib and dbus-1 to GDBus and GVariant. This was quite a work; next few weeks will be used for cleaning up and regression fixing. Jürg decided that it was more easy to simply port ~ all of tracker-store to Vala than to port tracker-store’s dbus-glib and dbus-1 C code to GDBus. This should please contributors who will now have a much more easy to understand codebase.

Tracker’s tracker-store is mostly an IPC layer above libtracker-data plus the signaling mechanism. The public libtracker-sparql is a API layer above the same private libtracker-data that protects you from doing things that you should not do. Like trying to do writes without going over the IPC layer.

This week we’re working on transient properties and adding tracker:modified to the journal and backup file. The tracker:modified property is an auto-incremented value. It’s useful for synchronization purposes. Right now when you replay the journal or restore a backup, we reset the count. This means that in between journal replays and/or backup restores you wont have the same tracker:modified values for your resources. This is what we are changing. We plan to restore the tracker:modified value during journal replay and backup-restore.

Transient properties are properties that are reset after restart of tracker-store (per Desktop session), they aren’t backed up (and therefor not restored either) and they aren’t journaled. They are useful for for example presence status of a contact.

The nice guys and girls at the QSparql team are working on a simple cursor that doesn’t do any buffering nor uses any threads. This is useful for Qt applications that want maximum performance while reading the results of a query.

Last week we introduced and ported to our newest location ontology, SLO.