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Answers
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Answers to these questions and explanations of why each answer choice is right or wrong are located in the Answers section at the end of the book.
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1. Which of the following is a valid population option for a full-text index A. REORGANIZE B. INCREMENTAL C. REBUILD D. COMPLETE
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21
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Creating Full-Text Catalogs
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Lesson 4: Querying Data by Using a Full-Text Index
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Full-text indexes are useful only if they are used to satisfy requests. However, regular Transact-SQL statements will not cause the query optimizer to automatically select a full-text index. You gain full-text query capability by using the CONTAINS, CONTAINSTABLE, FREETEXT, and FREETEXTTABLE full-text query keywords. Full-text query keywords are available in two types: predicate functions and rowset functions. The CONTAINS and FREETEXT functions are query predicates that return a simple True or False result to limit the result set. The CONTAINSTABLE and FREETEXTTABLE functions return a rowset that must be joined to another table based on a key value; you can use these functions to extend the capabilities of your queries. This lesson looks at each of these full-text keywords and describes which are appropriate for different needs, showing you the query syntax you need to use as well as query examples to help you understand the different results you can achieve.
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After this lesson, you will be able to:
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Explain the differences between the full-text query keywords. Submit full-text queries.
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Estimated lesson time: 20 minutes
Query Execution
When you execute queries that use full-text functions, SQL Server first parses and compiles them and then hands them to the query optimizer. The optimizer recognizes the full-text functions and routes them to the full-text search engine. The fulltext search engine takes the search terms passed and routes them through the dedicated query processor for full-text queries. Before the query processor can search for the keywords in the index, the keywords must be transformed into matching tokens. For this transformation, the full-text query processor launches the word breakers, stemmers, and noise word files discussed previously in this chapter. It also interrogates a thesaurus, which returns a list of synonyms that are also searched. It is this extended capability for matching on derivatives as well as synonyms that makes full-text searches so powerful and flexible capable of even handling common word misspellings. Let s look at each of the full-text query keywords in turn.
Lesson 4: Querying Data by Using a Full-Text Index
FREETEXT
The FREETEXT function accepts one or more columns to search and a search argument. This function performs a fuzzy search in that it automatically searches for inflectional forms (stemming) as well as related words that the thesaurus identifies. The general syntax of the FREETEXT function is as follows:
FREETEXT ( { column_name | (column_list) | * } , 'freetext_string' [ , LANGUAGE language_term ] )
This function does not provide the customization or precision that you typically want in production applications. For example, searching for the keyword bike by using the FREETEXT function would return bike , biker , bike riding , bike-riding , and various synonyms as well as any word that contains the word bike . Let s say you execute the following query against the Production.ProductDescription table using first the FREETEXT function and then the CONTAINS function:
SELECT ProductDescriptionID, Description FROM Production.ProductDescription WHERE FREETEXT(Description, N'bike'); SELECT ProductDescriptionID, Description FROM Production.ProductDescription WHERE CONTAINS(Description, N'bike');
The FREETEXT query returns 16 rows of data as opposed to the 14 rows that the CONTAINS query returns.
Search Argument Data Types for Full-Text Functions
When the SQL Server query optimizer decides how to efficiently satisfy a query, it uses an inspection algorithm that looks at value-distribution statistics to determine whether an index should be used for the query. The full-text engine also maintains a set of distribution statistics. The optimization process includes an algorithm generically referred to as parameter sniffing, which can handle explicit values as well as values contained within variables. The algorithm gives each potential path a basic score that indicates how selective a given path is for a query. These numbers are then used to determine whether an index seek, index scan, nested loop, or other method is used to satisfy a segment of a query. What does parameter sniffing have to do with full-text queries When the full-text optimizer cannot use parameter sniffing for one reason or another, it essentially
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