Map indexes, sometimes referred to as simple indexes, contain one (or more) mapping functions that indicate which fields from the documents should be indexed. They indicate which documents can be searched by which fields.
These mapping functions are LINQ-based functions and can be considered the core of indexes.
You can:
- index single fields
- combined multiple fields together
- index partial field data
- index nested data
- index fields from related documents
- index fields from multiple collections
- configure whether to index a document if the specified fields are
null - ...and more.
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
{CODE:nodejs indexes_1@indexes/map.js /}
- The next step is to create the indexing function itself. This is done by setting the
mapfield with mapping function in the constructor.
{CODE:nodejs indexes_2@indexes/map.js /}
{CODE-TABS} {CODE-TAB:nodejs:Query indexes_4@indexes/map.js /} {CODE-TAB-BLOCK:sql:RQL} from index 'Employees/ByFirstAndLastName' where FirstName = 'Robert' {CODE-TAB-BLOCK/} {CODE-TABS/}
{INFO: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...
{CODE-BLOCK:csharp} from employee in docs.Employees select new { Age = employee.Age } {CODE-BLOCK/}
...grant us the capability to issue numeric queries (return all the Employees that 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...
{CODE-BLOCK:csharp} from employee in docs.Employees select new { Age = employee.Age.ToString() } {CODE-BLOCK/}
{INFO/}
{WARNING: Convention}
You will probably notice that in the Studio, this function is a bit different from the one defined in the Employees_ByFirstAndLastName class:
{CODE-BLOCK:csharp} from employee in docs.Employees select new { FirstName = employee.firstName, LastName = employee.lastName } {CODE-BLOCK/}
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.
{WARNING/}
Since each index contains a LINQ function, you can combine multiple fields into one.
{CODE:nodejs indexes_7@indexes/map.js /}
{CODE-TABS} {CODE-TAB:nodejs:Query indexes_8@indexes/map.js /} {CODE-TAB-BLOCK:sql:RQL} from index 'Employees/ByFullName' where FullName = 'Robert King' {CODE-TAB-BLOCK/} {CODE-TABS/}
{INFO: Information}
In this example, the index field Query combines all values from various Employee fields into one. The default Analyzer on field 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.
{INFO/}
{CODE:nodejs indexes_1_6@indexes/map.js /}
{CODE-TABS} {CODE-TAB:nodejs:Query indexes_1_7@indexes/map.js /} {CODE-TAB-BLOCK:sql:RQL} from index 'Employees/Query' where search(Query, 'John Doe') {CODE-TAB-BLOCK/} {CODE-TABS/}
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 in the following way:
{CODE:nodejs indexes_1_2@indexes/map.js /}
{CODE-TABS} {CODE-TAB:nodejs:Query indexes_5_1@indexes/map.js /} {CODE-TAB-BLOCK:sql:RQL} from index 'Employees/ByBirthday ' where Birthday between '1963-01-01' and '1963-12-31T23:59:59.9990000' {CODE-TAB-BLOCK/} {CODE-TABS/}
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:
{CODE:nodejs indexes_1_0@indexes/map.js /}
{CODE-TABS} {CODE-TAB:nodejs:Query indexes_6_1@indexes/map.js /} {CODE-TAB-BLOCK:sql:RQL} from index 'Employees/ByYearOfBirth' where YearOfBirth = 1963 {CODE-TAB-BLOCK/} {CODE-TABS/}
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:
{CODE:nodejs indexes_1_4@indexes/map.js /}
{CODE-TABS} {CODE-TAB:nodejs:Query indexes_7_1@indexes/map.js /} {CODE-TAB-BLOCK:sql:RQL} from index 'Employees/ByCountry' where Country = 'USA' {CODE-TAB-BLOCK/} {CODE-TABS/}
If a document relationship is represented by the document's ID, you can use the LoadDocument method to retrieve such a document. More about it can be found here.
Read the article dedicated to Multi-Map indexes here.
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.