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Full-Text Index Structure

A good understanding of the structure of a full-text index will help you understand how the Full-Text Engine works. This topic uses the following excerpt of the Document table in Adventure Works as an example table. This excerpt shows only two columns, the DocumentID column and the Title column, and three rows from the table.

NoteNote

For information about the columns of this sample table, see Document Table (AdventureWorks).

For this example, we will assume that a full-text index has been created on the Title column.

DocumentID

Title

1

Crank Arm and Tire Maintenance

2

Front Reflector Bracket and Reflector Assembly 3

3

Front Reflector Bracket Installation

For example, the following table, which shows Fragment 1, depicts the contents of the full-text index created on the Title column of the Document table. Full-text indexes contain more information than is presented in this table. The table is a logical representation of a full-text index and is provided for demonstration purposes only. The rows are stored in a compressed format to optimize disk usage.

Notice that the data has been inverted from the original documents. Inversion occurs because the keywords are mapped to the document IDs. For this reason, a full-text index is often referred to as an inverted index.

Also notice that the keyword "and" has been removed from the full-text index. This is done because "and" is a stopword, and removing stopwords from a full-text index can lead to substantial savings in disk space thereby improving query performance. For more information about stopwords, see Stopwords and Stoplists.

Fragment 1

Keyword

ColId

DocId

Occurrence

Crank

1

1

1

Arm

1

1

2

Tire

1

1

4

Maintenance

1

1

5

Front

1

2

1

Front

1

3

1

Reflector

1

2

2

Reflector

1

2

5

Reflector

1

3

2

Bracket

1

2

3

Bracket

1

3

3

Assembly

1

2

6

3

1

2

7

Installation

1

3

4

The Keyword column contains a representation of a single token extracted at indexing time. Word breakers determine what makes up a token.

The ColId column contains a value that corresponds to a particular column that is full-text indexed.

The DocId column contains values for an eight-byte integer that maps to a particular full-text key value in a full-text indexed table. This mapping is necessary when the full-text key is not an integer data type. In such cases, mappings between full-text key values and DocId values are maintained in a separate table called the DocId Mapping table. To query for these mappings use the sp_fulltext_keymappings system stored procedure. To satisfy a search condition, DocId values from the above table need to be joined with the DocId Mapping table to retrieve rows from the base table being queried. If the full-text key value of the base table is an integer type, the value directly serves as the DocId and no mapping is necessary. Therefore, using integer full-text key values can help optimize full-text queries.

The Occurrence column contains an integer value. For each DocId value, there is a list of occurrence values that correspond to the relative word offsets of the particular keyword within that DocId. Occurrence values are useful in determining phrase or proximity matches, for example, phrases have numerically adjacent occurrence values. They are also useful in computing relevance scores; for example, the number of occurrences of a keyword in a DocId may be used in scoring.

The logical full-text index is usually split across multiple internal tables. Each internal table is called a full-text index fragment. Some of these fragments might contain newer data than others. For example, if a user updates the following row whose DocId is 3 and the table is auto change-tracked, a new fragment is created.

DocumentID

Title

3

Rear Reflector

In the following example, which shows Fragment 2, the fragment contains newer data about DocId 3 compared to Fragment 1. Therefore, when the user queries for "Rear Reflector" the data from Fragment 2 is used for DocId 3. Each fragment is marked with a creation timestamp that can be queried by using the sys.fulltext_index_fragments catalog view.

Fragment 2

Keyword

ColId

DocId

Occ

Rear

1

3

1

Reflector

1

3

2

As can be seen from Fragment 2, full-text queries need to query each fragment internally and discard older entries. Therefore, too many full-text index fragments in the full-text index can lead to substantial degradation in query performance. To reduce the number of fragments, reorganize the fulltext catalog by using the REORGANIZE option of the ALTER FULLTEXT CATALOGTransact-SQL statement. This statement performs a master merge, which merges the fragments into a single larger fragment and removes all obsolete entries from the full-text index.

After being reorganized, the example index would contain the following rows:

Keyword

ColId

DocId

Occ

Crank

1

1

1

Arm

1

1

2

Tire

1

1

4

Maintenance

1

1

5

Front

1

2

1

Rear

1

3

1

Reflector

1

2

2

Reflector

1

2

5

Reflector

1

3

2

Bracket

1

2

3

Assembly

1

2

6

3

1

2

7

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