Project Query Results

Projections overview

What are projections:

  • A projection refers to the transformation of query results into a customized structure,
    modifying the shape of the data returned by the server.

  • Instead of retrieving the full document from the server and then picking relevant data from it on the client,
    you can request a subset of the data, specifying the document fields you want to get from the server.

  • The query can load related documents and have their data merged into the projection results.

  • Objects and arrays can be projected, fields can be renamed, and any calculations can be made within the projection.

  • Content from inner objects and arrays can be projected.
    An alias name can be given to the projected fields, and any calculations can be made within the projection.

When to use projections:

  • Projections allow you to tailor the query results specifically to your needs.
    Getting specific details to display can be useful when presenting data to users or populating user interfaces.
    Projection queries are also useful with subscriptions since all transformation work is done on the server side without having to send a lot of data over the wire.

  • Returning partial document data from the server reduces network traffic,
    as clients receive only relevant data required for a particular task, enhancing overall performance.

  • Savings can be significant if you need to show just a bit of information from a large document. For example:
    the size of the result when querying for all "Orders" documents where "Company" is "companies/65-A" is 19KB.
    Performing the same query and projecting only the "Employee" and "OrderedAt" fields results in only 5KB.

  • However, when you need to actively work with the complete set of data on the client side,
    then do use a query without a projection to retrieve the full document from the server.

Projections are not tracked by the session:

  • On the client side, the resulting projected entities returned by the query are Not tracked by the Session.

  • Any modification made to a projection entity will not modify the corresponding document on the server when save_changes is called.

Projections are the final stage in the query pipeline:

  • Projections are applied as the last stage in the query pipeline,
    after the query has been processed, filtered, sorted, and paged.

  • This means that the projection does Not apply to all the documents in the collection,
    but only to the documents matching the query predicate.

  • Within the projection you can only filter what data will be returned from the matching documents,
    but you cannot filter which documents will be returned. That has already been determined earlier in the query pipeline.

  • Only a single projection request can be made per query.
    Learn more in single projection per query.

The cost of projections:

  • Queries in RavenDB do not allow any computation to occur during the query phase.
    However, you can perform any calculations
  • inside the projection.

  • But while calculations within a projection are allowed, having a very complex logic can impact query performance.
    So RavenDB limits the total time it will spend processing a query and its projections.
    Exceeding this time limit will fail the query. This is configurable, see the following configuration keys:

Projection Methods


  • The most common way to perform a query with a projection is to use the select_fields or select_fields_query_data method.

  • You can specify what fields from the document you want to retrieve and even provide a complex expression.

Example - Projecting individual fields of the document:

class CompanyNameCityAndCountry:
    def __init__(self, name: str = None, city: str = None, country: str = None): = name = city = country

query_data = QueryData(["name", "", ""], ["name", "city", "country"])
results = list(
    session.query(object_type=Company).select_fields_query_data(CompanyNameCityAndCountry, query_data)

# Each resulting object in the list is not a 'Company' entity, it is a new object containing ONLY the
# fields specified in the query_data
from "Companies"
select Name, Address.City as City, Address.Country as Country

Example - Projecting arrays and objects:

class OrderShippingAddressAndProductNames:
    def __init__(self, ship_to: str = None, product_names: List[str] = None):
        self.ship_to = ship_to
        self.product_names = product_names

# Retrieve all product names from the Lines array in an Order document
query_data = QueryData(["ship_to", "lines[].product_name"], ["ship_to", "product_names"])

projected_results = list(
        OrderShippingAddressAndProductNames, query_data
// Using simple expression:
from "Orders"
select ShipTo, Lines[].ProductName as ProductNames

// Using JavaScript object literal syntax:
from "Orders" as x
select {
    ShipTo: x.ShipTo, 
    ProductNames: => y.ProductName)

Example - Projection with expression:

class EmployeeFullName:
    def __init__(self, full_name: str):
        self.full_name = full_name

# Use custom function in query data or raw query
query_data = QueryData.custom_function("o", "{ full_name: o.first_name + ' ' + o.last_name }")
projected_results = list(
    session.query(object_type=Employee).select_fields_query_data(EmployeeFullName, query_data)
from "Employees" as e
select {
    FullName: e.FirstName + " " + e.LastName

Example - Projection with calculations:

class ProductsRaport:
    def __init__(
        self, total_products: int = None, total_discounted_products: int = None, total_price: int = None
        self.total_products = total_products
        self.total_discounted_products = total_discounted_products
        self.total_price = total_price

# Use custom function in query data or raw query
query_data = QueryData.custom_function(
    "total_products: o.lines.length,"
    " total_discounted_products: o.lines.filter((line) => > 0).length,"
    " total_price: o.lines.reduce("
    "(accumulator, line) => accumulator + line.price_per_unit * line.quantity, 0) "
projected_results = list(
    session.query(object_type=Order).select_fields_query_data(ProductsRaport, query_data)
from "Orders" as x
select {
    TotalProducts: x.Lines.length,
    TotalDiscountedProducts: x.Lines.filter(x => x.Discount > 0).length,
    TotalPrice: x.Lines
                  .map(l => l.PricePerUnit * l.Quantity)
                  .reduce((a, b) => a + b, 0)

raw_query with select

Data can be projected by sending the server raw RQL with the select keyword using the raw_query method.

Example - Projection with dates:

class EmployeeAgeDetails:
    def __init__(self, day_of_birth: str = None, month_of_birth: str = None, age: str = None):
        self.day_of_birth = day_of_birth
        self.month_of_birth = month_of_birth
        self.age = age

# Use custom function in query data or raw query
results = session.advanced.raw_query(
    "from Employees as e select {"
    ' "day_of_birth : new Date(Date.parse(e.birthday)).getDate(),'
    " month_of_birth : new Date(Date.parse(e.birthday)).getMonth() + 1,"
    " age : new Date().getFullYear() - new Date(Date.parse(e.birthday)).getFullYear()"
from "Employees" as e 
select { 
    DayOfBirth: new Date(Date.parse(e.Birthday)).getDate(), 
    MonthOfBirth: new Date(Date.parse(e.Birthday)).getMonth() + 1,
    Age: new Date().getFullYear() - new Date(Date.parse(e.Birthday)).getFullYear() 

Example - Projection with raw JavaScript code:

class EmployeeBirthdayAndName:
    def __init__(self, date: str = None, name: str = None): = date = name

# Use custom function in query data or raw query
results = list(
        "from Employees as e select {"
        "date: new Date(Date.parse(e.birthday)),"
        "name: e.first_name.substr(0,3)"
from "Employees" as e 
select {
    Date: new Date(Date.parse(e.Birthday)), 
    Name: e.FirstName.substr(0, 3)

Example - Projection with metadata:

projected_results = list(
        "from Employees as e "
        + "select {"
        + "     name : e.first_name, "
        + "     metadata : getMetadata(e)"
        + "}",
from "Employees" as e 
select {
     Name: e.FirstName, 
     Metadata: getMetadata(e)


The projected fields can also be specified using the select_fields method.

# Lets define an array with the field names that will be projected
# (its optional, you can pass field names as args loosely)
projection_fields = ["name", "phone"]
# Make a query
projected_results = list(
    # Call 'select_fields'
    # Pass the projection class type & the fields to be projected from it
    .select_fields(ContactDetails, *projection_fields)

# Each resulting object in the list is not a 'Company' entity
# it is an object of type 'ContactDetails' containing data ONLY for the specified fields
from "Companies"
select Name, Phone

Single projection per query

  • As of RavenDB v6.0, only a single projection request can be made per query.

  • Attempting multiple projection executions in the same query, e.g. by calling select_fields_query_data multiple times or by calling select_fields_query_data and then select_fields, will result in an exception.

# For example:
query_data = QueryData(["name"], ["funny_name"])
    projected_results = list(
        # Make a first projection
        # A second projection is not supported and will raise an error
        .select_fields_query_data(CompanyNameCityAndCountry, query_data)
except Exception as e:
    # The following exception will be raised:
    # "Projection is already done. You should not project your result twice."