As promised, here is another post describing what new tricks we’ve been teaching EDS (Evolution Data Server) this year at Openismus. We’ve come a long way on this, so first let me describe the major changes that we’ve made and then I’ll move on to show you the results.
Removing the BDB implementation and storing all contact data in the SQLite instead naturally makes queries faster, not to mention there is considerably less flash wear as we only have one DB persisting contact data now instead of two.
This has landed in EDS’s git master a couple of months ago and should be available in the next release. Summary Fields in EDS refer to the VCard fields for a given addressbook which should be elected for fast results.
This list has always been hard coded and tailored to the needs of the Evolution Mail client (the list basically consisted of the contact name fields plus a hand full of email fields which Evolution is accustomed to using). So we’ve now introduced a set of APIs which allow configuration of the summary fields of a given addressbook at addressbook creation time.
As a side effect of this, we now also support multi valued VCard attributes to be stored in the summary (i.e.
This has also landed in EDS master some time ago and will be available in the next EDS stable release.
Our fastest queries using the previously described configurable summary fields return in roughly 4-7 milliseconds. Custom – Built from our EDS 3.6 based work branch (called ‘openismus-work’) this build has Berkeley DB removed and configures the summary with a custom summary configuration. The red (DRA) line is EDS doing the same thing but avoiding the arduous tinkering with D-Bus messaging. Since we’ve configured EDS to optimize the phone number field of a given contact for prefix & suffix searches, we can now use phone number queries at reliable speed. The reason why this takes an extremely long time with EDS 3.6 is that the contacts have no quick search information ready at hand, this means we must iterate through all of the contacts in the Berkeley DB and parse the VCards for each, extract all of the phone numbers and compare one by one.

These are basically just memory usage snapshots taken over the course that the benchmarks run.
The “Custom” setup takes slightly more memory to run than EDS 3.6, this is presumably because we maintain more indexes with the SQLite version.
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She is a Globe prepaid subscriber since most of her classmates uses Globe, while my officemates, siblings, husband and I are all Smart subscribers. Over time some optimizations were made, originally an in-memory “summary” was maintained holding some of the contact data in order to speed up queries to the addressbook. Additionally we’ve also observed that the old BDB code fails (crashes, even) with an out of memory condition in some cases such as deleting more than 6400 contacts at once, this is all handled much cleaner using SQLite exclusively. They are stored separately in an SQLite table so that contacts can be queried without parsing the complete contact VCard data for every contact. This would of course be appropriate for an email client but falls short for applications that have different needs such as hand phones, which require extremely fast results for queries by phone number.
This allows us to choose which fields are stored in the summary and which of those fields should be indexed for extra fast retrieval.

Mathias foresaw that we would gain significant performance simply by delivering query results directly to the client instead of squishing them into the socket and pushing them arduously through the D-Bus byte by byte (or probably 8192 bytes at a time…).
Notice that for small addressbooks (less than 200 contacts) the results are similar to EDS Custom.
In other words you can again use EDS on your hand phone to implement your contacts database and kittens wont be sacrificed. Unsurprisingly, the Direct Read Access mode takes significantly more memory; this is because the direct read access mode uses two SQLite connections (one for the server and one for the client to make direct read calls). As a bonus, site members have access to a banner-ad-free version of the site, with print-friendly pages.Click here to learn more. My Ishi told me that since she is on a budget, and most of the time on unli-call and text she opt to txt and call peeps under the same network as her to maximize her load. I really have a little knowledge to which network my contacts in my list belongs, thanks to someone who has uploaded this picture in the FB {credits goes to you who created this very useful list}. This was eventually replaced with an SQLite implementation of the quick search “summary” data. I have to admit that I was a little sceptical about this change but after benchmarking the direct read access approach I was able to notice a serious performance gain. However with the customized summary fields we’ve also ensured that the SQLite indexes are getting used properly; this is what ensures the performance doesn’t degrade too much with larger addressbooks.
In the end that left us with a two step query for fetching contacts from the addressbook; an initial query to the SQLite to find any UID which match the query terms and then another query to the BDB fetching the actual VCard data for that contact.

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