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Tip: If you have a Java app, you can use the Python bulkloader.py tool by installing the Java version of the remote_api handler, which is included with the Java runtime environment. The handler servlet class is com.google.apphosting.utils.remoteapi.RemoteApiServlet.

A query like this will use the merge join strategy by default. If it's too slow for the merge join strategy, you could have to build a custom index for it, which would indeed be 'exploding'  - each User entity would have len(friends)*len(likes) index entries.

Merge join queries - queries with multiple equality filters but no inequalities or sort orders - are a special case. They can be satisfied using the built in indexes and a merge join strategy, but they can also use a custom index. The production environment will use the index if it's present, and otherwise will do a merge join. Generally, a merge join works well, but there are situations in which it doesn't - in which case you may need to add an explicit index.

A query like this will use the merge join strategy by default. If it's too slow for the merge join strategy, you could have to build a custom index for it, which would indeed be 'exploding'  - each User entity would have len(friends)*len(likes) index entries.

Here is the approach I would probably take unless you have many hundreds of child tasks. I would keep a list of keys of all children of each project/task. (You can then do a db.get and get all immediate children with single call) and each child has a reference to it's parent. In addition in each item keep a list of all parents keys back to the root. That way you can search for all children in part of the tree/subtree (This approach is especially useful if you have multiple child types) as back ref sets are kind specific. Keep a  running count of complete children at each level, rather than trying to calculate the current state in a single big function,  (keep these subsidiary values up to date through tasks)

The next problem that arises is that if the database has grown too big, then the csv generation will be slow(as it has to jump a lot of times). So the next idea is , instead of generating all cursors in the main cgi , the main cgi generates only first few set of page links, and then triggers a task queue entry to continue from there. By the time the user would have read the first page and clicks on "next page", the task would have generated few more entries. As the set of cursors for pagination is in memcache, you can use it even in your first page, if you are using AJAX (guessing, not that sure.)

Tip: If the app creates a new object and gives it the same string ID as another object of the same kind (and the same entity group parent), saving the new object overwrites the other object in the datastore. To detect whether a string ID is already in use prior to creating a new object, you can use a transaction to attempt to get an entity with a given ID, then create one if it doesn't exist. See Transactions.

There are 4 types of primary key fields:

it could be implemented as follows: The developer creates a CName record from *.<developersAppSubDomain>.<developersDomain>.com to <appEngineAppId>.appspot.com (if wildcard CName values aren't available on the developer's DNS server, then the developer will have to create one entry per customer). When Google receives a request on the App Engine Server with an unknown host name such as <subdomain>.<customersDomain>.com, it does the CName look-up, until it finds a host name of the form <appEngineAppId>.appspot.com. It then sends the server request on to that App Engine application, ideally including the whole CName "chain" as a special CGI variable, so that the application can determine the user ID of the customer that owns the domain. (And if the App Engine server doesn't find a host name for an App Engine application, it returns 404.)

the necessary changes to appengine-web.xml to get Sitebricks to run in development mode:         <sessions-enabled>true</sessions-enabled>         <system-properties>                 <property name="java.util.logging.config.file" value="WEB-INF/logging.properties"/>                 <property name="mvel2.disable.jit" value="true"/>         </system-properties>

the necessary changes to appengine-web.xml to get Sitebricks to run in development mode:         <sessions-enabled>true</sessions-enabled>         <system-properties>                 <property name="java.util.logging.config.file" value="WEB-INF/logging.properties"/>                 <property name="mvel2.disable.jit" value="true"/>         </system-properties>

We had a GaeFlashCache built specifically for appengine. Try doing: bind(FlashCache.class).to(GaeFlashCache.class).in(Singleton.class);

the necessary changes to appengine-web.xml to get Sitebricks to run in development mode:         <sessions-enabled>true</sessions-enabled>         <system-properties>                 <property name="java.util.logging.config.file" value="WEB-INF/logging.properties"/>                 <property name="mvel2.disable.jit" value="true"/>         </system-properties>

In a relational world duplication is removed in order to prevent update anomalies. Error prevention is the driving force in relational modeling. Normalization is a kind of ethical system for data.

BigTable data ethics are more Mardi Gras than dinner with the in-laws. Data just wants to have fun. BigTable won’t stop you from hurting yourself. And to get the best results you may have to engage in some conventionally risky behaviors.

So the summary is: do not store nulls into Lists, otherwise you will get into a problem in future.

You should get prompted for authentication. Make sure remote_api is installed correctly on your server by visiting whatever you used for the --url argument in your browser. It should require you to log in then say "This request did not contain a necessary header"

you could leverage Entity's getProperties() method, in combination with JSON-lib's groovy-friendliness and ability to serialize maps as JSON. So, say you have an Entity: def person = new Entity("person") person.name = "Guillaume Laforge" def jsonString = person.properties as JSONObject Have a look at JSON-lib and the Entity JavaDoc. And I think it'll solve your problem pretty neatly!