Hi:
Congratulation and thank for tremendous efforts from the Objectify Team.
By the way, has any one attempted Objectify with possible very large
index of subscribers and publishers of web-hook pub-sub (Google
PubSubHubbub of Atom or short message twitter style).
Thanks
Duong BaTien
DBGROUPS and BudhNet
On Thu, 2010-03-25 at 13:45 -0700, Jeff Schnitzer wrote:
> Today we released Objectify v2.1, the latest version of our opensource
> replacement for JDO/JPA on the Google App Engine datastore.
>
> This version includes a major new feature, Partial Indexes. If you
> aren't sure what partial indexes are, the Wikipedia page
> (http://en.wikipedia.org/wiki/Partial_index) describes them so:
>
> "A partial index, also known as filtered index is a database index
> which has some condition applied to it such that it only includes a
> portion of the rows in the table. This can allow the index to remain
> small even though the table may be rather large, and have fairly
> extreme selectivity."
>
> Here is an example of an Objectify entity using partial indexes:
>
> public class Player {
> @Id Long id;
>
> // Simple conditions: IfFalse, IfTrue, IfZero, IfNull, etc
> @Unindexed(IfFalse.class) boolean admin;
>
> // Smarter - sensitive to the actual default value
> @Unindexed(IfDefault.class) Team team = Team.NOTCHOSEN;
>
> // You can make your own conditions
> @Unindexed(IfCustomCondition.class) Status status;
>
> static class IfCustomCondition extends ValueIf {
> public boolean matches(Status value) {
> return (value == Status.DEAD || value == Status.RETIRED);
> }
> }
> }
>
> Why should you care about optimizing indexes?
>
> All queries in the datastore require indexes, which are a sort of
> reverse-mapping from value to key. These indexes occupy space and
> consume cpu resources whenever an entity is written to the datastore.
> With the addition of just a few indexes, this cost quickly doubles or
> triples the cost of storing the original entity:
>
> * A basic entity with no indexes costs 48 api_cpu_ms to store.
> * Each single-property indexed field adds an additional 17 api_cpu_ms.
>
> This number appears stable and consistent; appengine seems to have a
> static formula for computing datastore costs. Storage size costs are
> harder to measure, but from watching mailing list traffic it seems
> quite easy to double or triple your storage size with unnecessary
> indexes.
>
> When should you care about optimizing indexes?
>
> * Removing unnecessary indexes will not make writes faster, it will
> make them /cheaper/. All indexes are written in parallel, so indexes
> do not add latency to writes. Instead, indexes add $ to the bill you
> get at the end of the week - and push you closer to your quota limits.
>
> * If your application has relatively small quantities of relatively
> static data, index optimization is probably pointless. On the other
> hand, if you have large data volumes or heavy write loads, you must
> carefully choose your indexes (or be very rich).
>
> Do I need partial indexes, as opposed to just declaring whole fields
> indexed or not?
>
> It depends on your dataset and your queries. In the Player example
> above, partial indexes can be extremely effective:
>
> * You only ever filter on the admin field for actual admins, and most
> players are not admins.
> * You only ever filter on the team field for players who have chosen
> a team, and the bulk of players are not associated with a team.
> * You only ever filter on the status field for players who have
> active statuses, and you have a large number of inactive players.
>
> Objectify's support for partial indexes also has the ability to
> determine index behavior based on "the whole entity". This allows you
> to perform certain kinds of limited multiple-property queries
> (including double inequality queries) without creating a
> multi-property index. As an example, it is very easy to model this
> index from the Wikipedia page:
>
> create index partial_salary on employee(age) where salary > 2100;
>
> An example of this is documented in the Objectify manual.
>
> Thanks,
> The Objectify Team
> Jeff, Scott, and Matt
>
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