Question: I'm planning to do some data mining on my django app which uses appengine for storing data, however, one of my tables stores images in two of it's columns, and because of that, it is gigabytes in size so it's far too slow to download every time I want to analyse new data. For data mining, I only care about the plan text columns in that table, how do I exclude those columns while exporting data to an csv file?

I'm aware that there is a "column\_list" for the csv connector for buildupload.yaml that you can specify to only include certain columns when exporting data, but it looks like it still downloads the entire table row before filtering out the columns when it's converting appengine's intermediate sqlite3 data file to csv.

For reference, I'm using the method described here to download my data <http://code.google.com/appengine/docs/python/tools/uploadingdata.html>, but I'm open to other solutions, preferably ones where I can automate this data export every few days.

Answer: 
You can't. The AppEngine datastore API, and the underlying GQL, only do two sorts of SELECT queries: `__key__` only, and all fields. There's no way of getting a subset of fields.
Kind of late here but all I did in a similar situation was delete the unwanted property from the automatically generated bulkloader.yaml file.

Here is an example using the [Google documentation](https://developers.google.com/appengine/docs/python/tools/uploadingdata?csw=1) to exclude the "account" property from the csv file. I use it for things like blobs and it works fine there too:

```
property_map:
- property: __key__
  external_name: key
  export_transform: transform.key_id_or_name_as_string
START DELETE
- property: account
  external_name: account
  # Type: Key Stats: 119 properties of this type in this kind.
  import_transform: transform.create_foreign_key('TODO: fill in Kind name')
  export_transform: transform.key_id_or_name_as_string
END DELETE
- property: invite_nonce
  external_name: invite_nonce
  # Type: String Stats: 19 properties of this type in this kind.

```