Re: [google-appengine] At what point is querying down a hierarchical tree faster than querying through all the end nodes?

2015-08-18 Thread Sanket More
Hey Karl!

I definitely would leverage Google's API for this problem, but I actually 
was more interested in the approach for this hierarchical type of problem.
To flatten or not to flatten, that is the question!
But yes, APis would allow me to check for user error when it comes to 
cities and such.
I think my current format doesn't allow me to figure this out efficiently.
I would need to get the city, find neighbouring cities and then find 
restaurants in those cities.

Actually, I could submit their original query and ask some other api for 
nearby cities.
Once I got cities I could also run queries for the same restaurant name in 
those neighbouring cities.

Even better I think, would be when I create my restaurant information, I 
find the neighbouring cities using some other API, and create restauants 
there pointing back to the correct city...
For instance City 1 and City2 are close to each other.
When I put a restaurant via, Country, State, City1.Restaurant, I could also 
run a query through some other api for neighbouring cities.
Once I get that information I could put the restaurant information into, 
Country, State, City2, Restaurant.
Then if someone screws up and searches Country,State.City2.Restaurant 
instead of the correct City1 alternative, I would still be able to give 
them information that points back to the correct city.
This means extra time for creating data, but hopefully less for searching 
through it.

Thanks Karl!

On Monday, August 17, 2015 at 5:41:25 PM UTC-7, Karl MacMillan wrote:
>
>
>
> On Sunday, August 16, 2015, Sanket More > 
> wrote:
>
>> Hey Nick!
>>
>> After I submitted my question, I went through lots of information sources 
>> and gathered some information.
>> I feel like my question was based on many misconceptions about google app 
>> engine's datastore.
>>
>> I think I have a strategy for the restaurant problem.
>> The user will provide me with country, state, city and the restaurant 
>> name, And I will provide the user with location(s). 
>>
>> So all I really need is one specific entity and the response will simply 
>> be the information in that entity.
>> And, I don't really need to index country, state, city, and restaurant 
>> name with each other independently. I just need one string that holds the 
>> country state city and restaurant.
>> In fact, I think that string is unique.
>> So, I am thinking about having a restaurant kind with key string 
>> "country_state_city_restaurant"
>>
>> Once the user has finished submitting the form, I can get by 
>> "country_state_city_restaurant" and return some information to the user. 
>>
>> I wanted a smarter solution than this, because I feel that this solution 
>> won't scale well.
>> Furthermore, if I am flattening my tree structure like this, wouldn't gql 
>> be faster?
>>
>>
>> On Sunday, August 16, 2015 at 4:14:33 PM UTC-7, Nick wrote:
>>>
>>> The general rule is optimize for your primary use case, denormalise to 
>>> support others.
>>> In addition, enforce and support constraints In your code.
>>>
>>> If your primary case is restaurant search, embed and index all necessary 
>>> data. This will be the fastest solution and easiest to work with
>>>
>>> On Appengine extra data doesn't cost you unless it's indexed. There is a 
>>> careful balance between optimising for speed, cost and transactional 
>>> integrity. My advice is if this is your first go, expect to make mistakes 
>>> and to need to reengineer your data a couple of times. Make that process as 
>>> easy as possible.
>>>
>>>
> Just a suggestion - have you thought about letting the user query through 
> the Google maps or similar API to find the restaurants and then based on 
> those results returning information from your app? These location based 
> queries are hard - both technically and from matching the users 
> expectations. Especially as I'm betting that the city that a user thinks a 
> restaurant is located in often differs from official addresses, especially 
> in large cities.
>
> This strategy could let you both control the user experience and leverage 
> the hard work of others. 
>
> Karl
>  
>
>> -- 
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[google-appengine] Re: At what point is querying down a hierarchical tree faster than querying through all the end nodes?

2015-08-16 Thread Sanket More
Hey Nick!

After I submitted my question, I went through lots of information sources 
and gathered some information.
I feel like my question was based on many misconceptions about google app 
engine's datastore.

I think I have a strategy for the restaurant problem.
The user will provide me with country, state, city and the restaurant name, 
And I will provide the user with location(s). 
So all I really need is one specific entity and the response will simply be 
the information in that entity.
And, I don't really need to index country, state, city, and restaurant name 
with each other independently. I just need one string that holds the 
country state city and restaurant.
In fact, I think that string is unique.
So, I am thinking about having a restaurant kind with key string 
"country_state_city_restaurant"

Once the user has finished submitting the form, I can get by 
"country_state_city_restaurant" and return some information to the user. 

I wanted a smarter solution than this, because I feel that this solution 
won't scale well.
Furthermore, if I am flattening my tree structure like this, wouldn't gql 
be faster?


On Sunday, August 16, 2015 at 4:14:33 PM UTC-7, Nick wrote:
>
> The general rule is optimize for your primary use case, denormalise to 
> support others.
> In addition, enforce and support constraints In your code.
>
> If your primary case is restaurant search, embed and index all necessary 
> data. This will be the fastest solution and easiest to work with
>
> On Appengine extra data doesn't cost you unless it's indexed. There is a 
> careful balance between optimising for speed, cost and transactional 
> integrity. My advice is if this is your first go, expect to make mistakes 
> and to need to reengineer your data a couple of times. Make that process as 
> easy as possible.
>
>

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[google-appengine] At what point is querying down a hierarchical tree faster than querying through all the end nodes?

2015-08-16 Thread Sanket More
Hello! I am having so much trouble understanding datastore queries!
This is my problem.
I can't seem to figure out whether querying from the top of a tree down to 
a end node is faster than querying through all end nodes.
I don't care about write cost or about transactions, I just want to know 
what would be faster.

Here is an example of what I mean.
Lets say I have stored all the restaurants in a country through a database 
hierarchy.
Level 0 is the world.
Level 1 are the countries.
Level 2 are the states.
Level 3 are the cities
Level 4 are the restaurants

Now my users want to search for information about a particular restaurant 
and give me the country state city and restaurant name.

Would it be faster for me to save the country, state, city and restaurant 
at level 4 and then query through all restaurants for a match? OR
Would it be faster for me to search the country for all children states, 
pick the state I want, search the state for cities, pick the city I want, 
and essentially narrow it down to the restaurant?

Because I feel that with option one, I would end up linearly increasing the 
time my requests take and that's just not good.
And with option two, it feels like I would end up having to run multiple 
queries to find all the children of each level and then pick the child I 
want. Do I really need to run that many queries?

A perfect solution for me would be one query that allows me to search 
through the tree and get to the node I want. Is that possible?

Please respond even if I am unclear, I will appreciate literally any help 
you can give me.


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