Create Map Index

Index Name

Save - Save index definition
Clone - Clone this index (available for an already saved index)
Delete - Delete this index (available for an already saved index)

Options avaliable for an already saved index:
Copy C# - Click to view and copy the C# class that defines the index as set in the Studio.
Query - Click to go the the Query View and query this index.
Terms - Click to see the index terms, see below.

The Map Function of the index.

• In the above example, the index will go over documents from the Products collection and will only index documents whose Discontinued property is 'true'.

• Note: The range of documents from which the query on this index will supply results will be on only Products collection documents that have 'true' in the 'Discontinued' document field property. If the index was defined without the 'where' clause, but only using 'from p in docs.Products', then the documents range for the query result would have been the whole Products collection.

• Each Index Entry that will be created for this index will be composed of the following 4 fields:
  Name, Category, PricePerUnit & SupplierName.
  The first 3 are taken directly from the document fields, while SupplierName is a calculated index field.
  The supplier's name is derived from the Name field that is taken from the loaded supplier document.

• At query time, when querying this index, the resulting documents can be searched on and further filtered
  by these Index Fields defined and by the created Terms. See the query results on this index in Query View.

• See more Map-Indexes examples in Map Index defined from Code
  

Index Fields
The index-fields that are indexed per index-entry with the above index-definition are:
Name, Category, PricePerUnit & SupplierName.

Terms
The terms are listed under each field.
The terms are created from the value of the field that was requested to be indexed according to the specified Field Options.

Default values
Set the default values that will apply to all index fields.

Add a Field
Override the default values with specific settings for selected index entries.

Select Field
Select a field from the drop-down. The settings will override the default settings.

• Store - Setting 'Store' will store the value of this field in the index itself.
  At query time, if 'Store' is set, then the value is fetched directly from the index, instead of from the original document.
  If the field value is not stored in the index then it will be fetched from the document.
  Storing data in the index will increase the index size.
  Learn more in Storing Data in Index.

• Full-Text-Search - Set this to 'Yes' to allow searching for a particular text without having an exact match.
  The terms that are being indexed are tokens that are split from the original string according to the specified Analyzer.
  The Analyzer is set in the 'Indexing' dropdown. The default analyzer is a simple case-insensitive analyzer.

• Indexing - Specify which Analyzer will be used (under Advanced):

  • Exact - A no-operation analyzer. Text is not splitted and matches are case-sensitive.
  • Default - 'LowerCaseKeywordAnalyzer' is used. Matches are case-insensitive, the input string is converted to lowercase.
  • Search - Set a specific analyzer to use.
    The default option is 'StandardAnalyzer'. Input strings are broken into individual terms on a word boundary and are lowercased, while omitting the 'stop words' (a, the, to, from, is, are, etc.) as well as possessive “s”.
    Details about the available analyzers can be found in Indexes: Analyzers.

• Suggestions - Setting 'Suggestions' will allow you to query what the user probably meant to ask about. i.e. spelling errors.
  Learn more in this Blog Post, and in Querying: Suggestions.

• Term Vector - Term Vectors (under Advanced) are used in RavenDB's query feature More Like This, which suggests documents that are similar to a selected document, based on shared indexed terms. i.e. suggest similar catalogs.
  A 'Term Vector' for a text paragraph will contain a list of all unique words and how often they appeared.
  Set 'full-text-search' on the field (index entry) and define it to have a 'Term Vector'.
  Learn more in Indexes: Term Vectors, and in this Blog Post.

• Spatial - See below