Confused about Google App Engine and Google Docs options - google-app-engine

I want to use the Google App Engine to store my data and then query/display/ edit it using Google Spreadsheets as the user interface, with multiple concurrent users having their own view of the data. The problem I have now is that if I put everyone's data on the same Google Spreadsheet that everyone accesses, we can't each do sorting / filtering at the same time.
Is there a way to do this, and is it a good idea to build a simple system this way? I'll eventually need to query a series of Google Word Processor documents as well.
Can someone point me in the right direction on this or suggest other options?

I would ask what the advantage of doing something like this is as opposed to say hosting your application on Google App Engine and building a javascript front end with grids to help sort/filter and view data.
Anyway to answer your questions, you can build your interface over Google Spreadsheets using Google App Scripts. This will allow you to do things like authenticate your user, query, update and display data. If you want to merely display data it turns out that Google Spreadsheets has some built-in functions to do that.
Regarding consistency you should read up on GAE's Datastore as well as its features like transactions. The datastore is not an RDBMS, but is an object database which stores objects against keys. Again something to consider if you are planning to do a lot of data analysis and computation (summations, aggregations).
Overall I would recommend doing a rough design of your system without fixing on particular technologies (like GAE, and Google Spreadsheets). Once you identify what your key goals are for your application, then you can figure out which technologies and resources would make the most sense within your budget.

Related

Storing 100k map markers in App Engine

I'm designing yet another "Find Objects near my location" web site and mobile app.
My requirements are:
Store up to 100k objects;
Query for objects that are close to the point (my location, city, etc). And other search criteria (like object type);
Display results on the Google Maps with smooth performance.
Let user filter objects by object time.
I'm thinking about using Google App Engine for this project.
Could You recommend what would be the best data storage option for this?
And couple of words about dynamic data loading strategy.
I kinda feel overwhelmed with options at the moment and looking for hints where should I continue my research.
Thanks a lot!
I'm going to to assume that you are using the datastore. I'm not familiar with Google Cloud SQL (which I believe aims to offer MySQL-like features in the cloud), so I can't speak if it can do geospatial queries.
I've been looking into the whole "get locations in proximity of a location" problem for a while now. I have some good and bad news for you, unfortunately.
The best way to do the proximity search in the Google Environment is via the Search Service (https://developers.google.com/appengine/docs/python/search/ or find the JAVA link ). Reason being is that it supports a "Geopoint Field", and allows you to query in such a way.
Ok, cool, so there is support, right? However, "A query is complex if its query string includes the name of a geopoint field or at least one OR or NOT boolean operator". The free quota for Complex Search Queries are 100/day. Per 10,000 queries, it costs 60 cents. Depending on your application, this may be an issue.
I'm not too familar with the Google Maps API you might be able to pull off something like this :(https://developers.google.com/maps/articles/phpsqlsearch_v3)
My current project/problem involves moving locations, and not "static" ones (stores, landmarks,etc). I've decided to go with Amazon's Dynamodb and they have a library which supports geospatial indexing : http://aws.amazon.com/about-aws/whats-new/2013/09/05/announcing-amazon-dynamodb-geospatial-indexing/

What shall I use: Google Datastore or Cloud SQL?

I am developing a project on my Final year at uni and this will be an Android application.
Basically, the "company" updates the database with jobs to be done around the country. Its field workers will use the app to display the jobs available in their location. Workers then select the jobs they are committing to do and send the selection back to database.
I would like to use Google App Engine for that and I am just studying it at the moment.
I came across two methods how to store the data on GAE: Datastore and Cloud SQL.
Personally, I would like to use NoSql Datastore in order to experiment and learn it.
What would you suggest me to use for my use case?
What are the pros and cons of using both mentioned methods?
If I go with Google Datastore, is this guide good for me to start with? https://developers.google.com/appengine/docs/java/datastore/
I would say both will work. If you want to discover the Google Datastore then go for it.
But I would suggest you have a look at Objectify, this library is excellent to make you the things easier with this technology.
go with Google App engine Database. its very efficient to use. yes tat document is enough to start.

Geospatial Database Cloud Server

Are there any cloud hosting solutions for geospatial data? I am currently writing a directory style app where businesses can sign up and then users can find nearby ones.
I am considering Google App Engine for this, but from what I can tell the GeoModel code is quite expensive (up to tens of thousands of dollars a year) to run since Google updated the pricing of App Engine. It doesn't seem like App Engine's database is really suited to this kind of query (though the SQL solution may be an answer).
I was hoping to find a service where I could send off a HTTP request to add data (a business' id, name and icon url) to a database, and then another one to find a list of businesses that are nearby to a given point. A service is preferable as this is work done for a client and we would like the solution to be managed with as little interaction from us or the client needed as possible.
EDIT:
I just found cartodb.com which uses PostgreSQL and is reasonably priced. Are the any other alternatives?
The App Engine Search API (currently in Experimental) supports GeoPoints and geosearch, and is great for exactly the kind of query that you describe.
See the Google Developers Academy (GDA) App Engine Search API classes for a bit more info and an example as well.
http://www.iriscouch.com/ is a cloud-based host for CouchDB and they support the geocouch extensions for CouchDB to store geoJSON data and perform spatial queries.
We have decided to go with cartodb.com because it looks like they have a good price to ease of use ratio.
You mentioned going with CartoDB, which is a good choice with a nice UI.
Just adding, if you were just looking for a scalable backend, you could use StormDB. It is a cloud hosted SQL database with geospatial extensions. You data is automatically distributed amongst multiple nodes for write, read, and parallel query scalability.

Back up AppEngine database (Google cloud storage?)

I have an AppEngine application that currently has about 15GB of data, and it seems to me that it is impractical to use the current AppEngine bulk loader tools to back up datasets of this size. Therefore, I am starting to investigate other ways of backing up, and would be interested in hearing about practical solutions that people may have used for backing up their AppEngine Data.
As an aside, I am starting to think that the Google Cloud Storage might be a good choice. I am curious to know if anyone has experience using the Google Cloud Storage as a backup for their AppEngine data, and what their experience has been, and if there are any pointers or things that I should be aware of before going down this path.
No matter which solution I end up with, I would like a backup solution to meet the following requirements:
1) Reasonably fast to backup, and reasonably fast to restore (ie. if a serious error/data deletion/malicious attack hits my website, I don't want to have to bring it down for multiple days while restoring the database - by fast I mean hours, as opposed to days).
2) A separate location and account from my AppEngine data - ie. I don't want someone with admin access to my AppEngine data to necessarily have write/delete access to the backup data location - for example if my AppEngine account is compromised by a hacker, or if a disgruntled employee were to decide to delete all my data, I would like to have backups that are separate from the AppEngine administrator accounts.
To summarize, given that getting the data out of the cloud seems slow/painful, what I would like is a cloud-based backup solution that emulates the role that tape backups would have served in the past - if I were to have a backup tape, nobody else could modify the contents of that tape - but since I can't get a tape, can I store a secure copy of my data somewhere, that only I have access to?
Kind Regards
Alexander
There are a few options here, though none are (currently) quite what you're looking for.
With the latest release of version 1.5.5 of the SDK, we now support interfacing with Google Storage directly - you can see how, here. With this you can write data to Google Storage, but to the best of my knowledge there's no way to write a file that the app will then be unable to delete.
To actually gather the data, you could use the App Engine mapreduce API. It has built in support for writing to the App Engine blobstore; writing to Google Storage would require you to implement your own output writer, currently.
Another option, as WoLpH suggests, is to use the Datastore Admin tool to back up data to another app. With a little extra effort you could modify the remote_api stub to prohibit deletes to the target (backup) app.
One thing you should definitely do regardless is to enable two-factor authentication for your Google account; this makes it a lot harder for anyone to get control of your account, even if they discover your password.
The bulkloader is probably one of the fastest way to backup/restore your data.
The problem with the AppEngine is that you have to do everything through views. So you have the restrictions that views have... the result is that a fast backup/restore still has to use the same API's as the rest of your app. So the bulkloader (possibly with a few modifications) is definately your best option here.
Perhaps though... (haven't tried it yet), you can use the new Datastore Admin to copy the data to another app. One which only you control. That way you can copy it back from the other app when needed.

How to best deploy a single Google App Engine application to multiple region-specific subdomains?

I am trying to figure out the best way to deploy a single Google App Engine application across multiple regions.
The same code is to be used, but the stored data is specific to each region. Motivating examples are hyperlocal review sites, like yelp.com or urbanspoon, where restaurants and other businesses to review are specific to a region (e.g. boston.app.com, seattle.app.com).
A couple options include:
Create multiple GAE applications,
and duplicate the code across them.
Create a single GAE application, and store all data for all regions
in the same Datastore, with a region
identifier field for each model
delimiting the relevant region.
Some of the trade-offs:
Option 2 seems like it will be increasingly inefficient (space: replicating a region identifier for each record of every model; time: filtering/indexing on the identifier for every query).
Option 1 requires an app ID for every region, while GAE only allows 10 apps per account. Moreover, deploying the code across every region, as well as Datastore migration, seems like it could be a pain to manage.
In the ideal world, I would have a single application instance. From that instance, I could route between subdomains (like here), as well as have a separate Datastore for each subdomain. But I believe GAE only allows a single datastore per application.
Does anyone have ideas on the best way to solve this problem? Or options that I am not considering?
Thanks for your time!
I would recommend your approach #2. Storage space is cheap (and region codes are short), and datastore performance does not degrade with size, unlike most databases. Using a single app also makes for easier management and upgrades, and avoids any issues with the TOS (which prohibit sharding your app to avoid billing charges).
If you use source code revision control, then it is not too bad to push identical code into multiple apps. You could set a policy whereby only full-fledged tags are allowed to be pushed up to GAE. Another option is to make your application version the same as the revision number.
With App Engine, I (and I believe most others) always migrate data from within my model code. You can't easily do bulk migrations in GAE and the usual solution is to migrate data as you come across it in code. In this way, you can keep your models pretty much identical across applications.
Having said that, I would probably still go with a unified application. It's more future-proof. What if users want to join their L.A. identity and their New York identity? Or what if an advertiser offers you a sweet deal for you to run some marketing reports on your own data?
Finally, a few bytes of data doesn't matter so much on App Engine. As your site grows, you will very quickly discover that you will always be bumping into ceilings. GAE limits are extremely small compared to a traditional web server and so you will have to work within those limits anyway. For example, you can only fetch 1,000 records at a time. So your architecture will already support a piecemeal paging solution. So don't worry too much about an extra field or two in your record.

Resources