Yes, the Query object is lazy. This is so that it's possible to allow
chaining of filters. It's actually a pretty powerful abstraction, but you do
need to realize that the Query isn't executed until the last possible
moment. When you store a Query object into Memcache, it hasn't executed yet.
On Sat, Nov 21, 2009 at 6:41 AM, dburns wrote:
> I thought I'd share this, since I'm sure there are others that have
> fallen into the same trap using this very common pattern (in this
> sample, Pix derives from db.Model; get_pics is called on every page
> load):
>
>def get_pics(self):
>pics = memcache.get("pics")
>if pics is None:
>pics = Pix.gql("LIMIT 100")
>memcache.add("pics", pics, 300) # Good for 5
> minutes
>return pics
>
> See the bug? Here, memcache is actually HURTING performance since the
> overhead of memcache is there but it saves nothing at all. The query
> is still executed on every page load when the calling code iterates
> through the result.
>
>
> http://code.google.com/appengine/docs/python/datastore/queryclass.html#Introduction
> mentions this by saying "creating a new iterator from the Query object
> will re-execute the query", but it doesn't highlight this pitfall.
> The issue here is that entities are not fetched on the Pix.gql line.
> Instead, that simply returns a Query object. The results are actually
> fetched when the calling code begins to iterate (in Python-speak, the
> __iter__() method on the Query is what actually fetches entities).
>
> To fix this, you'd change the gql line to :
>pics = list(Pix.gql("LIMIT 100"))
> Putting a list() around the Pix.gql forces the query to happen at that
> moment. Then the list of entities is stored in memcache, not the
> Query object itself.
>
> I'm not sure if this applies to the Java API too, but it's worth a
> heads-up.
>
> Comments welcome...
>
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>
--
Ikai Lan
Developer Programs Engineer, Google App Engine
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