InterSystems IRIS Basics: SQL Search
This topic introduces you to InterSystems IRIS® support for SQL text search, which provides semantic context searching of unstructured text data in a variety of languages. It covers the following topics:
To use SQL Search in a hands-on online exercise, see Searching Unstructured Text DataOpens in a new tab. For the full documentation on SQL Search, see the Using SQL Search.
SQL Search presupposes that you know what you are looking for. As such, it is distinct from Natural Language Processing (NLP) analyses of unstructured text data, which often require no prior knowledge of the text contents.
Why SQL Search Is Important
SQL Search features that require Semantic and Analytic indexes (entity- and language-aware search) use InterSystems IRIS Natural Language Processing (NLP), which InterSystems has deprecated. As a result, these features may be removed from future versions of InterSystems products. The following documentation is provided as reference for existing users only. Existing users who would like assistance identifying an alternative solution should contact the WRCOpens in a new tab.
The ability to rapidly search unstructured text data is fundamental to accessing the content of the huge volume of text commonly stored by many companies and institutions. Any search facility for such data must have the following functionality:
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Fast search: InterSystems IRIS SQL Search can rapidly search large quantities of data because it is searching a generated optimized index to the data, rather than sequentially searching the data itself.
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Word-aware search: SQL Search is not a string search, it is a search based on semantic structures in the text. The most basic semantic structure for SQL Search is the word. This reduces the number of false positives that result when a string search finds a string embedded in another word, or when a string bridges two words.
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Entity-aware search: SQL Search takes into account multiple words that are grouped by semantic relationship to form entities. It can thus search for multiple words in a specified order (a positional phrase), words appearing within a specific proximity to each other (regardless of sequence), and words found at the beginning or at the end of an entity. This enables you to narrow a search to a word (or phrase) found in a specified context of other words.
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Language-aware search: identifying semantic relationships between words is language-specific. SQL Search contains semantic rules (language models) for ten natural languages. It also provides support for other languages. It does not require the creation or association of dictionaries or ontologies.
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Pattern matching: SQL Search provides both wildcard matching and regular expression (RegEx) matching to match character patterns.
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Fuzzy matching: SQL Search provides fuzzy search for near-matches that take into account a calculated degree of variation from the search string. This enables matching of spelling errors, among other things.
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Derived matching: SQL Search can use decompounding to match root words and component words. SQL Search can use synonym tables to match synonym words and phrases.
How InterSystems IRIS Implements SQL Search
Semantic and Analytic SQL Search indexes use InterSystems IRIS Natural Language Processing (NLP), which InterSystems has deprecated. As a result, these features may be removed from future versions of InterSystems products. The following documentation is provided as reference for existing users only. Existing users who would like assistance identifying an alternative solution should contact the WRCOpens in a new tab.
SQL Search can search text data found in a column in an SQL table. In order to do this, you must create an SQL Search index for the column containing the text data. InterSystems implements a table column as a property in a persistent class.
There are three levels of index available, each supporting additional features as well as all of the features of the lower levels: Basic, Semantic, and Analytic:
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Basic supports word search and positional phrase search, including the use of wildcards, ranges between words in a phrase, regular expression (RegEx) matching, and co-occurrence search.
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Semantic supports all of the Basic functionality, and also supports InterSystems IRIS Natural Language Processing (NLP) entities. It can search for entities, and words or phrases that begin an entity or end an entity. It recognizes NLP attributes, such as negation.
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Analytic supports all of the Semantic functionality, and also supports NLP paths. It can also search based on NLP dominance and proximity scores.
Populating the index. Like all SQL indexes, you can either build the index directly after the table has been populated with data, or have SQL automatically build the index entries as you insert records into an empty table. In either case, SQL automatically updates this index as part of subsequent insert, update, or delete operations.
You perform an SQL Search you write a SELECT query in which the WITH clause contains %ID %FIND search_index() syntax. The search_index() function parameters include the name of the SQL Search index and a search string. This search string can include wildcard, positional phrase, and entity syntax characters. The search string can also include AND, OR, and NOT logical operators.
Learn More About SQL Search
InterSystems has other resources to help you learn more about SQL Search, including: