Hey Ivo,

It seems odd that you'd see nothing for hot keys. I've emailed you to ask 
for your project ID, so feel free to reply to that email when you get a 
chance. 

In the meantime, I'm also curious about your observation of the key 
distribution. Could you possibly show some sample keys, 
sanitized/obfuscated for security, but which will still give an indication 
of what you mean by the key space not being properly distributed-into by 
NDB? If you like, you can also include the keys, without alteration, in 
your private email reply.

Of course, feel free to add any other useful information or any additional 
questions.

Cheers,

Nick
Cloud Platform Community Support

On Friday, March 3, 2017 at 6:00:20 AM UTC-5, Ivo Bellin Salarin wrote:
>
> Hi all,
>
> I have two questions concerning memcache and its performances.
>
> I was reading the page 
> https://cloud.google.com/appengine/articles/best-practices-for-app-engine-memcache#distribute_load_across_the_keyspace,
>  
> where I found
> *The Memcache viewer in the administration console displays a list of top 
> keys, which can be used to identify bottlenecks*
>
> In my administration console, this section is empty. (i.e. 'No hot keys')
> But yes, I am sure that there are hot keys, since among the stackdriver 
> insights I can see the following messages
> Slow memcache calls. Your app made 1 remote procedure calls to memcache 
> that took more than 50 ms and the slowest call took 66 ms. Consider 
> reducing the value of max_concurrent_requests for your app.
> 1) Thus, where can I find the hottest keys of my dedicated memcache?
>
> In the meanwhile, according to the messages I can find in StackDriver, the 
> longest (thus, probably, hottest) memcache.get(s) are made by ndb.get(). In 
> the code of ndb.get I can see that the cache keys are **not** distributed 
> across the keyspace (as recommended by the page above).
> I think that not using memcache (use_memcache=False) would be a worse 
> solution.
> 2) Is there a way to force a better key distribution for NDB, apart from 
> monkey patching 
> /gcloud/platform/google_appengine/google/appengine/ext/ndb/context.py::Context._memcache_prefix
>  
> with a time dependent % operation? :-)
>

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