Projection Queries

Most Datastore queries return whole entities as their results, but often an application is actually interested in only a few of the entity's properties. Projection queries allow you to query the Datastore for just those specific properties of an entity that you actually need, at lower latency and cost than retrieving the entire entity.

Projection queries are similar to SQL queries of the form

SELECT name, email, phone FROM CUSTOMER

You can use all of the filtering and sorting features available for standard entity queries, subject to the limitations described below. The query returns abridged results with only the specified properties ( name , email , and phone in the example) populated with values; all other properties have no data.

Contents

1. Using projection queries in Python
2. Grouping
3. Limitations on projections
4. Projections and multiple-valued properties
5. Indexes for projections

Using projection queries in Python

Projection queries are supported by both Query and GqlQuery objects. Both classes require this import:

from google.appengine.ext import db

You specify a projection this way:

proj = db.Query(entity_name, projection=('property_1', 'property_2','property_n'))

proj = db.GqlQuery("SELECT property_1, property_2, property_n FROM entity_name")

You handle the results of these queries just as you would for a standard entity query: for example, by iterating over the results.

The following example queries for the title , read_path , and date_written properties of all EventLog entries, sorted in ascending order by date_written , and writes each property's value to the application log:

for proj in db.GqlQuery("SELECT title, read_path, date_written" +
                        "FROM EventLog" +
                        "ORDER BY date_written ASC"):
  logging.info(proj.title)
  logging.info(proj.read_path)
  logging.info(proj.date_written)

Grouping ^{(experimental)}

Projection queries can use the distinct keyword to ensure that only completely unique results will be returned in a result set. This will only return the first result for entities which have the same values for the properties that are being projected.

query = db.Query(projection=['A', 'B'], distinct=True).filter('B >', 1).order('-B, A')

Limitations on projections

Projection queries are subject to the following limitations:

• Only indexed properties can be projected.

  Projection is not supported for long text strings ( Text ), long byte strings ( Blob ), and other properties explicitly marked as unindexed.

• The same property cannot be projected more than once.

• Properties referenced in an equality ( = ) or membership ( IN ) filter cannot be projected.

  For example,

  SELECT A FROM kind WHERE B = 1
  

  is valid (projected property not used in the equality filter), as is

  SELECT A FROM kind WHERE A > 1
  

  (not an equality filter), but

  SELECT A FROM kind WHERE A = 1
  

  (projected property used in equality filter) is not.

• Results returned by a projection query cannot be saved back to the Datastore.

  Because the query returns results that are only partially populated, you cannot write them back to the Datastore.

Projections and multiple-valued properties

Projecting a property with multiple values will not populate all values for that property. Instead, a separate entity will be returned for each unique combination of projected values matching the query. For example, suppose you have an entity of kind Foo with two multiple-valued properties, A and B :

entity = Foo(A=[1, 1, 2, 3], B=['x', 'y', 'x'])

Then the projection query

SELECT A, B FROM Foo WHERE A < 3

will return four entities with the following combinations of values:

A = 1 , B = 'x'
A = 1 , B = 'y'
A = 2 , B = 'x'
A = 2 , B = 'y'

Indexes for projections

Projection queries require all properties specified in the projection to be included in a Datastore index . The App Engine development server automatically generates the needed indexes for you in the index configuration file, index.yaml , which is uploaded with your application.

One way to minimize the number of indexes required is to project the same properties consistently, even when not all of them are always needed. For example, these queries require two separate indexes:

SELECT A, B FROM Kind
SELECT A, B, C FROM Kind

However, if you always project properties A , B , and C , even when C is not required, only one index will be needed.

Converting an existing query into a projection query may require building a new index if the properties in the projection are not already included in another part of the query. For example, suppose you had an existing query like

SELECT * FROM Kind WHERE A > 1 ORDER BY A, B

which requires the index

Index(Kind, A, B)

Converting this to either of the projection queries

SELECT C FROM Kind WHERE A > 1 ORDER BY A, B
SELECT A, B, C FROM Kind WHERE A > 1 ORDER BY A, B

introduces a new property ( C ) and thus will require building a new index Index(Kind, A, B, C) . Note that the projection query

SELECT A, B FROM Kind WHERE A > 1 ORDER BY A, B

would not change the required index, since the projected properties A and B were already included in the existing query.

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Last updated May 30, 2014.