Indexes: Map Indexes
Map
indexes, sometimes referred to as simple indexes, contain one (or more) mapping functions that indicate which fields from the documents should be indexed.- After indexing, documents can be searched by the indexed fields.
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The mapping functions are LINQ-based functions or JavaScript functions (when using JavaScript indexes); they can be considered the core of indexes.
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In This Page:
Also see:
- Indexing fields from related documents
- Aggregating data with Map-Reduce indexes
- Indexing multiple collections with Multi-Map indexes
- Running calculations and storing the results in the index to reduce query time
Indexing single fields
Let's create an index that will help us search for Employees
by their FirstName
, LastName
, or both.
- First, let's create an index called
Employees/ByFirstAndLastName
Note: The naming separator character "
_
" in your code will become "/" in the index name.
In the following sample, "Employees_ByFirstAndLastName
" will become "Employees/ByFirstAndLastName" in your indexes list.
public class Employees_ByFirstAndLastName : AbstractIndexCreationTask<Employee>
{
// ...
}
public class Employees_ByFirstAndLastName : AbstractJavaScriptIndexCreationTask
{
// ...
}
You might notice that we're passing Employee
as a generic parameter to AbstractIndexCreationTask
. This gives our indexing function a strongly-typed syntax. If you are not familiar with AbstractIndexCreationTask
, you can read this article before proceeding.
- The next step is to create the indexing function itself. This is done by setting the
Map
property with our function in a parameterless constructor.
public Employees_ByFirstAndLastName()
{
Map = employees => from employee in employees
select new
{
FirstName = employee.FirstName,
LastName = employee.LastName
};
}
public Employees_ByFirstAndLastName()
{
Map = employees => employees
.Select(employee => new
{
FirstName = employee.FirstName,
LastName = employee.LastName
});
}
public Employees_ByFirstAndLastName()
{
Maps = new HashSet<string>
{
@"map('Employees', function (employee){
return {
FirstName : employee.FirstName,
LastName : employee.LastName
};
})",
};
}
- The final step is to deploy it to the server
and issue a query using the session Query method.
To query an index, the name of the index must be called by the query.
If the index isn't called, RavenDB will either use or create an auto index.
IList<Employee> employees1 = session
.Query<Employee, Employees_ByFirstAndLastName>()
.Where(x => x.FirstName == "Robert")
.ToList();
IList<Employee> employees2 = session
.Query<Employee>("Employees/ByFirstAndLastName")
.Where(x => x.FirstName == "Robert")
.ToList();
from index 'Employees/ByFirstAndLastName'
where FirstName = 'Robert'
Our final index looks like:
public class Employees_ByFirstAndLastName : AbstractIndexCreationTask<Employee>
{
public Employees_ByFirstAndLastName()
{
Map = employees => from employee in employees
select new
{
FirstName = employee.FirstName,
LastName = employee.LastName
};
}
}
public class Employees_ByFirstAndLastName : AbstractJavaScriptIndexCreationTask
{
public Employees_ByFirstAndLastName()
{
Maps = new HashSet<string>
{
@"map('Employees', function (employee){
return {
FirstName : employee.FirstName,
LastName : employee.LastName
};
})",
};
}
}
Field Types
Please note that indexing capabilities are detected automatically from the returned field type from the indexing function.
For example, if our Employee
will have a property called Age
that is an integer
then the following indexing function...
from employee in docs.Employees
select new
{
Age = employee.Age
}
map('Employees', function(employee)
{
return {
Age : employee.Age
};
})
...grants us the capability to issue numeric queries (return all the Employees whose Age is more than 30).
Changing the Age
type to a string
will take that capability away from you. The easiest example would be to issue .ToString()
on the Age
field...
from employee in docs.Employees
select new
{
Age = employee.Age.ToString()
}
map('Employees', function(employee)
{
return {
Age : employee.Age.toString()
};
})
Convention
You will probably notice that in the Studio
, this function is a bit different from the one defined in the Employees_ByFirstAndLastName
class:
from employee in docs.Employees
select new
{
FirstName = employee.FirstName,
LastName = employee.LastName
}
The part you should pay attention to is docs.Employees
. This syntax indicates from which collection a server should take the documents for indexing. In our case, documents will be taken from the Employees
collection. To change the collection, you need to change Employees
to the desired collection name or remove it and leave only docs
to index all documents.
Combining multiple fields
Since each index contains a LINQ function, you can combine multiple fields into one.
Example I
Index definition:
public class Employees_ByFullName : AbstractIndexCreationTask<Employee>
{
public class Result
{
public string FullName { get; set; }
}
public Employees_ByFullName()
{
Map = employees => from employee in employees
select new Result
{
FullName = employee.FirstName + " " + employee.LastName
};
}
}
public class Employees_ByFullName : AbstractJavaScriptIndexCreationTask
{
public class Result
{
public string FullName { get; set; }
}
public Employees_ByFullName()
{
Maps = new HashSet<string>
{
@"map('Employees', function (employee){
return {
FullName : employee.FirstName + ' ' + employee.LastName
};
})",
};
}
}
Query the index:
// notice that we're 'cheating' here
// by marking result type in 'Query' as 'Employees_ByFullName.Result' to get strongly-typed syntax
// and changing type using 'OfType' before sending query to server
IList<Employee> employees = session
.Query<Employees_ByFullName.Result, Employees_ByFullName>()
.Where(x => x.FullName == "Robert King")
.OfType<Employee>()
.ToList();
IList<Employee> employees = session
.Advanced
.DocumentQuery<Employee, Employees_ByFullName>()
.WhereEquals("FullName", "Robert King")
.ToList();
from index 'Employees/ByFullName'
where FullName = 'Robert King'
Example II
Information
In this example, the index field Query
combines all values from various Employee fields into one.
The default Analyzer on fields is changed to enable Full-Text Search
operations. The matches no longer need to be exact.
You can read more about analyzers and Full-Text Search
here.
Index definition:
public class Companies_ByAddress_Country : AbstractIndexCreationTask<Company>
{
public class Result
{
public string City { get; set; }
public string Company { get; set; }
public string Phone { get; set; }
}
public Companies_ByAddress_Country()
{
Map = companies => from company in companies
where company.Address.Country == "USA"
select new Result
{
Company = company.Name,
City = company.Address.City,
Phone = company.Phone
};
}
}
public class Employees_Query : AbstractJavaScriptIndexCreationTask
{
public class Result
{
public string[] Query { get; set; }
}
public Employees_Query()
{
Maps = new HashSet<string>
{
@"map('Employees', function (employee) {
return {
Query : [employee.FirstName,
employee.LastName,
employee.Title,
employee.Address.City]
}
})"
};
Fields = new Dictionary<string, IndexFieldOptions>()
{
{"Query", new IndexFieldOptions(){ Indexing = FieldIndexing.Search} }
};
}
}
Query the index:
IList<Employee> employees = session
.Advanced
.DocumentQuery<Employees_Query.Result, Employees_Query>()
.Search(x => x.Query, "John Doe")
.SelectFields<Employee>()
.ToList();
from index 'Employees/Query'
where search(Query, 'John Doe')
Indexing partial field data
Imagine that you would like to return all employees that were born in a specific year.
You can do it by indexing Birthday
from Employee
, then specify the year in Birthday
as you query the index:
Index definition:
public class Employees_ByBirthday : AbstractIndexCreationTask<Employee>
{
public class Result
{
public DateTime Birthday { get; set; }
}
public Employees_ByBirthday()
{
Map = employees => from employee in employees
select new Result
{
Birthday = employee.Birthday
};
}
}
public class Employees_ByBirthday : AbstractJavaScriptIndexCreationTask
{
public class Result
{
public DateTime Birthday { get; set; }
}
public Employees_ByBirthday()
{
Maps = new HashSet<string>
{
@"map('Employees', function (employee){
return {
Birthday : employee.Birthday
}
})"
};
}
}
Query the index:
DateTime startDate = new DateTime(1963, 1, 1);
DateTime endDate = startDate.AddYears(1).AddMilliseconds(-1);
IList<Employee> employees = session
.Query<Employees_ByBirthday.Result, Employees_ByBirthday>()
.Where(x => x.Birthday >= startDate && x.Birthday <= endDate)
.OfType<Employee>()
.ToList();
DateTime startDate = new DateTime(1963, 1, 1);
DateTime endDate = startDate.AddYears(1).AddMilliseconds(-1);
IList<Employee> employees = session
.Advanced
.DocumentQuery<Employees_ByBirthday.Result, Employees_ByBirthday>()
.WhereBetween(x => x.Birthday, startDate, endDate)
.OfType<Employee>()
.ToList();
from index 'Employees/ByBirthday '
where Birthday between '1963-01-01' and '1963-12-31T23:59:59.9990000'
RavenDB gives you the ability to extract field data and to index by it. A different way to achieve our goal will look as follows:
Index definition:
public class Employees_ByYearOfBirth : AbstractIndexCreationTask<Employee>
{
public class Result
{
public int YearOfBirth { get; set; }
}
public Employees_ByYearOfBirth()
{
Map = employees => from employee in employees
select new Result
{
YearOfBirth = employee.Birthday.Year
};
}
}
public class Employees_ByYearOfBirth : AbstractJavaScriptIndexCreationTask
{
public class Result
{
public int YearOfBirth { get; set; }
}
public Employees_ByYearOfBirth()
{
Maps = new HashSet<string>
{
@"map('Employees', function (employee){
return {
Birthday : employee.Birthday.Year
}
})"
};
}
}
Query the index:
IList<Employee> employees = session
.Query<Employees_ByYearOfBirth.Result, Employees_ByYearOfBirth>()
.Where(x => x.YearOfBirth == 1963)
.OfType<Employee>()
.ToList();
IList<Employee> employees = session
.Advanced
.DocumentQuery<Employees_ByYearOfBirth.Result, Employees_ByYearOfBirth>()
.WhereEquals(x => x.YearOfBirth, 1963)
.OfType<Employee>()
.ToList();
from index 'Employees/ByYearOfBirth'
where YearOfBirth = 1963
Filtering data within fields
In the examples above, where
is used in the query to filter the results.
If you consistently want to filter with the same filtering conditions,
you can use where
in the index definition to narrow the index terms that the query must scan.
This can save query-time but narrows the terms available to query.
Example I
For logic that has to do with special import rules that only apply to the USA
where
can be used to filter the Companies collection Address.Country
field.
Thus, we only index documents where company.Address.Country == "USA"
.
Index definition (LINQ Syntax):
public class Companies_ByAddress_Country : AbstractIndexCreationTask<Company>
{
public class Result
{
public string City { get; set; }
public string Company { get; set; }
public string Phone { get; set; }
}
public Companies_ByAddress_Country()
{
Map = companies => from company in companies
where company.Address.Country == "USA"
select new Result
{
Company = company.Name,
City = company.Address.City,
Phone = company.Phone
};
}
}
Query the index:
IList<Company> orders = session
.Query<Companies_ByAddress_Country.Result, Companies_ByAddress_Country>()
.OfType<Company>()
.ToList();
from index 'Companies_ByAddress_Country'
Example II
Imagine a seed company that needs to categorize its customers by latitude-based growing zones.
They can create a different index for each zone and filter their customers in the index with
where (company.Address.Location.Latitude > 20 && company.Address.Location.Latitude < 50)
.
Index definition (LINQ Syntax):
public class Companies_ByAddress_Latitude : AbstractIndexCreationTask<Company>
{
public class Result
{
public double latitude { get; set; }
public double longitude { get; set; }
public string companyName { get; set; }
public string companyAddress { get; set; }
public string companyPhone { get; set; }
}
public Companies_ByAddress_Latitude()
{
Map = companies => from company in companies
where (company.Address.Location.Latitude > 20 && company.Address.Location.Latitude < 50)
select new
{
latitude = company.Address.Location.Latitude,
longitude = company.Address.Location.Latitude,
companyName = company.Name,
companyAddress = company.Address,
companyPhone = company.Phone
};
}
}
Query the index:
IList<Company> orders = session
.Query<Companies_ByAddress_Latitude.Result, Companies_ByAddress_Latitude>()
.OfType<Company>()
.ToList();
from index 'Companies_ByAddress_Latitude'
Indexing nested data
If your document contains nested data, e.g. Employee
contains Address
, you can index on its fields by accessing them directly in the index. Let's say that we would like to create an index that returns all employees that were born in a specific Country
:
Index definition:
public class Employees_ByCountry : AbstractIndexCreationTask<Employee>
{
public class Result
{
public string Country { get; set; }
}
public Employees_ByCountry()
{
Map = employees => from employee in employees
select new Result
{
Country = employee.Address.Country
};
}
}
public class Employees_ByCountry : AbstractJavaScriptIndexCreationTask
{
public class Result
{
public string Country { get; set; }
}
public Employees_ByCountry()
{
Maps = new HashSet<string>
{
@"map('Employees', function (employee){
return {
Country : employee.Address.Country
}
})"
};
}
}
Query the index:
IList<Employee> employees = session
.Query<Employees_ByCountry.Result, Employees_ByCountry>()
.Where(x => x.Country == "USA")
.OfType<Employee>()
.ToList();
IList<Employee> employees = session
.Advanced
.DocumentQuery<Employees_ByCountry.Result, Employees_ByCountry>()
.WhereEquals(x => x.Country, "USA")
.OfType<Employee>()
.ToList();
from index 'Employees/ByCountry'
where Country = 'USA'
If a document relationship is represented by the document's ID, you can use the LoadDocument
method to retrieve such a document.
Learn more here.
Indexing Missing Fields
By default, indexes will not index a document that contains none of the specified fields. This behavior can be changed using the Indexing.IndexEmptyEntries configuration option.
The option Indexing.IndexMissingFieldsAsNull
determines whether missing fields in documents are indexed with the value null
, or not indexed at all.