Full-Text Indexing and Querying Process
The indexing component of full-text search is responsible for the initial population of the full-text index, and the subsequent update of this index when the data in the full-text indexed tables is modified.
Full-Text Indexing Process
When a full-text population (also known as a crawl) is initiated, the Full-Text Engine pushes large batches of data into memory and notifies the filter daemon host. The host filters and word breaks the data and converts the converted data into inverted word lists. The full-text search then pulls the converted data from the word lists, processes the data to remove stopwords, and persists the word lists for a batch into one or more inverted indexes.
When indexing data stored in a varbinary(max) or image column, the filter, which implements the IFilter interface, extracts text based on the specified file format for that data (for example, Microsoft Word). In some cases, the filter components require the varbinary(max), or image data to be written out to the filterdata folder, instead of being pushed into memory.
As part of processing, the gathered text data is passed through a word breaker to separate the text into individual tokens, or keywords. The language used for tokenization is specified at the column level, or can be identified within varbinary(max), image, or xml data by the filter component.
Additional processing may be performed to remove stopwords, and to normalize tokens before they are stored in the full-text index or an index fragment.
When a population has completed, a final merge process is triggered that merges the index fragments together into one master full-text index. This results in improved query performance since only the master index needs to be queried rather than a number of index fragments, and better scoring statistics may be used for relevance ranking.
The master merge can be I/O intensive, because large amounts of data must be written and read when index fragments are merged, though it does not block incoming queries. Also, master merging a large amount of data can create a long running transaction, delaying truncation of the transaction log during checkpoint. In this case, the transaction log might grow significantly under the full recovery model. As a best practice, ensure that your transaction log contains sufficient space for a long-running transaction before reorganizing a large full-text index in a database that uses the full recovery model. For more information, see Managing the Size of the Transaction Log File.
Full-Text Querying Process
The query processor passes the full-text portions of a query to the Full-Text Engine for processing. The Full-Text Engine performs word breaking and, optionally, thesaurus expansions, stemming, and stopword (noise-word) processing. Then the full-text portions of the query are represented in the form of SQL operators, primarily as streaming table-valued functions (STVFs). During query execution, these STVFs access the inverted index to retrieve the correct results. The results are either returned to the client at this point, or they are further processed before being returned to the client.