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[Seif Lotfy <624310@xxxxxxxxxxxxxxxxxx>]

So i created a shitty extension too see how much memory consumption happens before things are sent over dbus.
The idea is I ask for ALL events directly from the engine, 10 seconds after zeitgeist starts
Here are my observations

find_eventids: starts with 16.8 MB and end up with 25.4 MB

find_events: starts with 16.8 MB and end up with 106.2 MB

I think for the first case we cant do much
However for the second case we need to reduce the memory footprint of the Event and Subject in our datamodel. Maybe by using the __slots__ 

I also wrote 2 scripts one in python and the other in Vala... Both connect to the DB and ask for all ids.
Observations are vala uses 6.6 MB and python 12.9...

Maybe we can write our own cursor around the sqlite in C and create
bindings for it to allow us to play with the memory and instead of
returning lists in fetchall we can make it return tuples


** Attachment added: "memory.py"
   https://bugs.launchpad.net/zeitgeist/+bug/624310/+attachment/2153964/+files/memory.py

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Extensions, which is the registrant for Zeitgeist Extensions.
https://bugs.launchpad.net/bugs/624310

Title:
  Large requests increase memory usage considerably

Status in Zeitgeist Framework:
  Confirmed
Status in Zeitgeist Extensions:
  New

Bug description:
  I'm seeing with standalone Sezen that after running it, mem usage of
  the zeitgeist-daemon process goes up from ~13MB to ~40MB, this is
  understandable as when Sezen is starting, it does one big query where
  it asks for everything grouped by most recent subjects and in my case
  this returns ~11 thousand events, so the extra 30MB can be explained
  by allocating memory for the DBus reply.

  Still, my question is whether Zeitgeist should be at mercy of the
  applications, where nothing prevents them from spiking the memory
  usage of the core process. (I already saw a couple of times zeitgeist
  using 80-100MB of memory on my system). Perhaps there's a way to tell
  python dbus to free its buffers?