6 Querying with Oracle Text

Become familiar with Oracle Text querying and associated features.

This chapter contains the following topics:

6.1 Overview of Queries

The basic Oracle Text query takes a query expression, usually a word with or without operators, as input. Oracle Text returns all documents (previously indexed) that satisfy the expression along with a relevance score for each document. You can use the scores to order the documents in the result set.

To enter an Oracle Text query, use the SQL SELECT statement. Depending on the type of index, you use either the CONTAINS or CATSEARCH operator in the WHERE clause. You can use these operators programatically wherever you can use the SELECT statement, such as in PL/SQL cursors.

Use the MATCHES operator to classify documents with a CTXRULE index.

6.1.1 Querying with CONTAINS

When you create an index of type CONTEXT, you must use the CONTAINS operator to enter your query. This index is suitable for indexing collections of large coherent documents.

With the CONTAINS operator, you can use a number of operators to define your search criteria. These operators enable you to enter logical, proximity, fuzzy, stemming, thesaurus, and wildcard searches. With a correctly configured index, you can also enter section searches on documents that have internal structure such as HTML and XML.

With CONTAINS, you can also use the ABOUT operator to search on document themes. CONTAINS SQL Example

In the SELECT statement, specify the query in the WHERE clause with the CONTAINS operator. Also specify the SCORE operator to return the score of each hit in the hitlist. The following example shows how to enter a query:

SELECT SCORE(1), title from news WHERE CONTAINS(text, 'oracle', 1) > 0;

You can order the results from the highest scoring documents to the lowest scoring documents by using the ORDER BY clause as follows:

SELECT SCORE(1), title from news 
           WHERE CONTAINS(text, 'oracle', 1) > 0
           ORDER BY SCORE(1) DESC;

The CONTAINS operator must always be followed by the > 0 syntax, which specifies that the score value returned by the CONTAINS operator must be greater than zero for the row to be returned.

When the SCORE operator is called in the SELECT statement, the CONTAINS operator must reference the score label value in the third parameter, as shown in the previous example. CONTAINS PL/SQL Example

In a PL/SQL application, you can use a cursor to fetch the results of the query.

The following example enters a CONTAINS query against the NEWS table to find all articles that contain the word oracle. The titles and scores of the first ten hits are output.

  rowno number := 0; 
  for c1 in (SELECT SCORE(1) score, title FROM news 
              WHERE CONTAINS(text, 'oracle', 1) > 0
              ORDER BY SCORE(1) DESC) 
    rowno := rowno + 1; 
    dbms_output.put_line(c1.title||': '||c1.score); 
    exit when rowno = 10; 
  end loop; 

This example uses a cursor FOR loop to retrieve the first ten hits. An alias score is declared for the return value of the SCORE operator. The score and title are shown as output by using the cursor dot notation. Structured Query with CONTAINS Example

A structured query, also called a mixed query, is a query that has one CONTAINS predicate to query a text column and another predicate to query a structured data column.

To enter a structured query, specify the structured clause in the WHERE condition of the SELECT statement.

For example, the following SELECT statement returns all articles that contain the word oracle written on or after October 1, 1997:

SELECT SCORE(1), title, issue_date from news 
           WHERE CONTAINS(text, 'oracle', 1) > 0
           AND issue_date >= ('01-OCT-97') 
           ORDER BY SCORE(1) DESC;


Although you can enter structured queries with CONTAINS, consider creating a CTXCAT index and issuing the query with CATSEARCH, which offers better structured query performance.

6.1.2 Querying with CATSEARCH

When you create an index of type CTXCAT, you must use the CATSEARCH operator to enter your query. This index is suitable when your application stores short text fragments in the text column and associated information in related columns.

For example, an application serving an online auction site includes a table that stores item descriptions in a text column and date and price information in other columns. With a CTXCAT index, you can create b-tree indexes on one or more columns, so that query performance is generally faster for mixed queries.

The operators available for CATSEARCH queries are limited to logical operations such as AND or OR. To define your structured criteria, use the following operators : greater than, less than, equality, BETWEEN, and IN. CATSEARCH SQL Query Example

A typical query with CATSEARCH includes the following structured clause to find all rows that contain the word camera ordered by the bid_close date:

SELECT FROM auction WHERE CATSEARCH(title, 'camera', 'order by bid_close desc')> 0;

The type of structured query tht you can enter depends on how you create your sub-indexes.

As shown in the previous example, you specify the structured part of a CATSEARCH query with the third structured_query parameter. The columns in the structured expression must have a corresponding subindex.

For example, assuming that category_id and bid_close have a subindex in the ctxcat index for the AUCTION table, enter the following structured query:

SELECT FROM auction WHERE CATSEARCH(title, 'camera', 'category_id=99 order by bid_close desc')> 0; CATSEARCH Example

The following example shows a field section search against a CTXCAT index. It uses CONTEXT grammar by means of a query template in a CATSEARCH query.

-- Create and populate table
create table BOOKS (ID number, INFO varchar2(200), PUBDATE DATE);
insert into BOOKS values(1, '<author>NOAM CHOMSKY</author><subject>CIVIL
   PRESS</publisher>', '01-NOV-2003');
insert into BOOKS values(2, '<author>NICANOR PARRA</author><subject>POEMS 
  AND ANTIPOEMS</subject><language>SPANISH</language>
  <publisher>VASQUEZ</publisher>', '01-JAN-2001');
insert into BOOKS values(1, '<author>LUC SANTE</author><subject>XML
  PRESS</publisher>', '15-MAY-2002');
-- Create index set and section group
exec ctx_ddl.create_index_set('BOOK_INDEX_SET');
exec ctx_ddl.add_index('BOOK_INDEX_SET','PUBDATE');
exec ctx_ddl.create_section_group('BOOK_SECTION_GROUP',
exec ctx_ddl.add_field_section('BOOK_SECTION_GROUP','AUTHOR','AUTHOR');
exec ctx_ddl.add_field_section('BOOK_SECTION_GROUP','SUBJECT','SUBJECT');
exec ctx_ddl.add_field_section('BOOK_SECTION_GROUP','LANGUAGE','LANGUAGE');
exec ctx_ddl.add_field_section('BOOK_SECTION_GROUP','PUBLISHER','PUBLISHER'); 
-- Create index
create index books_index on books(info) indextype is ctxsys.ctxcat
  parameters('index set book_index_set section group book_section_group');
-- Use the index
-- Note that: even though CTXCAT index can be created with field sections, it
-- cannot be accessed using CTXCAT grammar (default for CATSEARCH).
-- We need to use query template with CONTEXT grammar to access field 
-- sections with CATSEARCH
select  id, info from books
where catsearch(info,
      <textquery grammar="context">
              NOAM within author and english within language
'order by pubdate')>0; 

6.1.3 Querying with MATCHES

When you create an index of type CTXRULE, you must use the MATCHES operator to classify your documents. The CTXRULE index is essentially an index on the set of queries that define your classifications.

For example, if you have an incoming stream of documents that need to be routed according to content, you can create a set of queries that define your categories. You create the queries as rows in a text column. You can create this type of table with the CTX_CLS.TRAIN procedure.

You then index the table to create a CTXRULE index. When documents arrive, you use the MATCHES operator to classify each document MATCHES SQL Query

A MATCHES query finds all rows in a query table that match a given document. Assuming that a querytable table is associated with a CTXRULE index, enter the following query:

SELECT classification FROM querytable WHERE MATCHES(query_string,:doc_text) > 0;

The :doc_text bind variable contains the CLOB document to be classified.

Here is a simple example:

   create table queries (
      query_id      number,
      query_string  varchar2(80)

    insert into queries values (1, 'oracle');
    insert into queries values (2, 'larry or ellison');
    insert into queries values (3, 'oracle and text');
    insert into queries values (4, 'market share');

    create index queryx on queries(query_string)
      indextype is ctxsys.ctxrule;

    select query_id from queries
     where matches(query_string, 
                   'Oracle announced that its market share in databases 
                    increased over the last year.')>0

This query returns queries 1 (the word oracle appears in the document) and 4 (the phrase market share appears in the document), but not 2 (neither the word larry nor the word ellison appears, and not 3 (there is no text in the document, so it does not match the query).

In this example, the document was passed in as a string for simplicity. Your document is typically passed in a bind variable.

The document text used in a MATCHES query can be VARCHAR2 or CLOB. It does not accept BLOB input, so you cannot match filtered documents directly. Instead, you must filter the binary content to CLOB by using AUTO_FILTER. The following example makes two assumptions:

  • The document data is in the :doc_blob bind variable.

  • You have already defined my_policy that CTX_DOC.POLICY_FILTER can use.

For example:

    doc_text clob;
    -- create a temporary CLOB to hold the document text
    doc_text := dbms_lob.createtemporary(doc_text, TRUE, DBMS_LOB.SESSION);
    -- create a simple policy for this example
    ctx_ddl.create_preference(preference_name => 'fast_filter',
                        object_name       => 'AUTO_FILTER');
    ctx_ddl.set_attribute(preference_name => 'fast_filter',
                        attribute_name    => 'OUTPUT_FORMATTING',
                        attribute_value   => 'FALSE');
    ctx_ddl.create_policy(policy_name     => 'my_policy',
                        filter            => 'fast_filter);

    -- call ctx_doc.policy_filter to filter the BLOB to CLOB data
    ctx_doc.policy_filter('my_policy', :doc_blob, doc_text, FALSE);

    -- now do the matches query using the CLOB version
    for c1 in (select * from queries where matches(query_string, doc_text)>0)
      -- do what you need to do here
    end loop;


The CTX_DOC.POLICY_FILTER procedure filters the BLOB into the CLOB data, because you must get the text into a CLOB to enter a MATCHES query. It takes, as one argument, the name of a policy that you already created with CTX_DDL.CREATE_POLICY.

See Also:

Oracle Text Reference for information on CTX_DOC.POLICY_FILTER

If your file is text in the database character set, then you can create a BFILE and load it to a CLOB by using the DBMS_LOB.LOADFROMFILE function, or you can use UTL_FILE to read the file into a temp CLOB locator.

If your file needs AUTO_FILTER filtering, then you can load the file into a BLOB instead and call CTX_DOC.POLICY_FILTER, as previously shown.

See Also:

Classifying Documents in Oracle Text for more extended classification examples MATCHES PL/SQL Examples

The following example assumes that the profiles table of queries is associated with a CTXRULE index. It also assumes that the newsfeed table contains a set of news articles to be categorized.

This example loops through the newsfeed table, categorizing each article by using the MATCHES operator. The results are stored in the results table.

PROMPT  Populate the category table based on newsfeed articles
set serveroutput on;
  mypk   number;
  mytitle varchar2(1000);
  myarticles clob;
  mycategory varchar2(100);
  cursor doccur is select pk,title,articles from newsfeed;
  cursor mycur is  select category from profiles where matches(rule, myarticles)>0;  
  cursor rescur is select category, pk, title from results order by category,pk;

  open doccur;
    fetch doccur into mypk, mytitle, myarticles;
    exit when doccur%notfound;
    open mycur;
      fetch mycur into mycategory;
      exit when mycur%notfound;
      insert into results values(mycategory, mypk, mytitle);
    end loop;
    close mycur;
  end loop;
  close doccur;


The following example displays the categorized articles by category.

PROMPT  display the list of articles for every category
set serveroutput on;

  mypk   number;
  mytitle varchar2(1000);
  mycategory varchar2(100);
  cursor catcur is select category from profiles order by category;
  cursor rescur is select pk, title from results where category=mycategory order by pk;

  open catcur;
    fetch catcur into mycategory;
    exit when catcur%notfound;
    dbms_output.put_line('********** CATEGORY: '||mycategory||' *************');
open rescur;
      fetch rescur into mypk, mytitle;
      exit when rescur%notfound;
dbms_output.put_line('**  ('||mypk||'). '||mytitle);
    end loop;
    close rescur;
  end loop;
  close catcur; 

See Also:

Classifying Documents in Oracle Text for more extended classification examples

6.1.4 Word and Phrase Queries

A word query is a query on a word or phrase. For example, to find all the rows in your text table that contain the word dog, enter a query specifying dog as your query term.

You can enter word queries with both CONTAINS and CATSEARCH SQL operators. However, phrase queries are interpreted differently.

  • CONTAINS Phrase Queries: If multiple words are contained in a query expression, separated only by blank spaces (no operators), the string of words is considered a phrase. Oracle Text searches for the entire string during a query. For example, to find all documents that contain the phrase international law, enter your query with the phrase international law.

  • CATSEARCH Phrase Queries: With the CATSEARCH operator, you insert the AND operator between words in phrases. For example, a query such as international law is interpreted as international AND law.

6.1.5 Querying Stopwords

Stopwords are words for which Oracle Text does not create an index entry. They are usually common words in your language that are unlikely to be searched.

Oracle Text includes a default list of stopwords for your language. This list is called a stoplist. For example, in English, the words this and that are defined as stopwords in the default stoplist. You can modify the default stoplist or create new stoplists with the CTX_DDL package. You can also add stopwords after indexing with the ALTER INDEX statement.

You cannot query on a stopword itself or on a phrase composed of only stopwords. For example, a query on the word this returns no hits when this is defined as a stopword.

Because the Oracle Text index records the position of stopwords even though it does not create an index entry for them, you can query phrases that contain stopwords as well as indexable words, such as this boy talks to that girl.

When you include a stopword within your query phrase, the stopword matches any word. For example, the following query assumes that was is a stopword. It matches phrases such as Jack is big and Jack grew big. It also matches grew, even though it is not a stopword.

'Jack was big'

Starting with Oracle Database 12c Release 2 (12.2), stopwords and unary operators on stopwords are ignored at the initial stages of a query result in different query results than earlier releases. For example, the following query does not return documents because the is a stopword and the $ operator and the stopword are ignored during query processing:

SQL> select count(1) from tabx where contains(text,'$the')>0; 

The next query returns documents containing first because the the stopword and the $ operator are ignored.

SQL> select count(1) from tabx where contains(text,'first and $the')>0; 

6.1.6 ABOUT Queries and Themes

An ABOUT query is a query on a document theme. A document theme is a concept that is sufficiently developed in the text. For example, an ABOUT query on US politics might return documents containing information about US presidential elections and US foreign policy. Documents need not contain the exact phrase US politics to be returned.

During indexing, document themes are derived from the knowledge base, which is a hierarchical list of categories and concepts that represents a view of the world. Some examples of themes in the knowledge catalog are concrete concepts such as jazz music, football, or Nelson Mandela. Themes can also be abstract concepts such as happiness or honesty.

During indexing, the system can also identify and index document themes that are sufficiently developed in the document but that do not exist in the knowledge base.

You can augment the knowledge base to define concepts and terms specific to your industry or query application. When you do so, ABOUT queries are more precise for the added concepts.

ABOUT queries perform best when you create a theme component in your index. Theme components are created by default for English and French.

Querying Stopthemes

Oracle Text enables you to query on themes with the ABOUT operator. A stoptheme is a theme that is not to be indexed. You can add and remove stopthemes with the CTX_DDL package. You can add stopthemes after indexing with the ALTER INDEX statement.

6.2 Oracle Text Query Features

Oracle Text has various query features. You can use these query features in your query application.

6.2.1 Query Expressions

A query expression is everything in between the single quotes in the text_query argument of the CONTAINS or CATSEARCH operator. The contents of a query expression in a CONTAINS query differs from the contents of a CATSEARCH operator. CONTAINS Operators

A CONTAINS query expression can contain query operators that enable logical, proximity, thesaural, fuzzy, and wildcard searching. Querying with stored expressions is also possible. Within the query expression, you can use grouping characters to alter operator precedence. This book refers to these operators as the CONTEXT grammar.

With CONTAINS, you can also use the ABOUT query to query document themes.

See Also:

"The CONTEXT Grammar" CATSEARCH Operator

With the CATSEARCH operator, you specify your query expression with the text_query argument and your optional structured criteria with the structured_query argument. The text_query argument enables you to query words and phrases. You can use logical operations, such as logical and, or, and not. This book refers to these operators as the CTXCAT grammar.

If you want to use the much richer set of operators supported by the CONTEXT grammar, you can use the query template feature with CATSEARCH.

With structured_query argument, you specify your structured criteria. You can use the following SQL operations:

  • =

  • <=

  • >=

  • >

  • <

  • IN


You can also use the ORDER BY clause to order your output.

See Also:

"The CTXCAT Grammar" MATCHES Operator

Unlike CONTAINS and CATSEARCH, MATCHES does not take a query expression as input.

Instead, the MATCHES operator takes a document as input and finds all rows in a query (rule) table that match it. As such, you can use MATCHES to classify documents according to the rules they match.

See Also:

"Querying with MATCHES"

6.2.2 Case-Sensitive Searching

Oracle Text supports case-sensitivity for word and ABOUT queries.

Word queries are not case-insensitive by default. This means that a query on the term dog returns the rows in your text table that contain the word dog, but not Dog or DOG.

You can enable or disable case-sensitive searching with the MIXED_CASE attribute in your BASIC_LEXER index preference. With a case-sensitive index, your queries must be entered in exact case. For example, a query on Dog matches only documents with Dog. Documents with dog or DOG are not returned as hits.

To enable case-insensitive searching, set the MIXED_CASE attribute in your BASIC_LEXER index preference to NO.


If you enable case-sensitivity for word queries and you query a phrase containing stopwords and indexable words, then you must specify the correct case for the stopwords. For example, a query on the dog does not return text that contains The Dog, assuming that the is a stopword.

ABOUT queries give the best results when your query is formulated with proper case because the normalization of your query is based on the knowledge catalog. The knowledge catalog is case-sensitive. Attention to case is required, especially for words that have different meanings depending on case, such as turkey the bird and Turkey the country.

However, you do not have to enter your query in exact case to obtain relevant results from an ABOUT query. The system does its best to interpret your query. For example, if you enter a query of ORACLE and the system does not find this concept in the knowledge catalog, the system might use Oracle as a related concept for lookup.

6.2.3 Query Feedback

Feedback provides broader-term, narrower term, and related term information for a specified query with a CONTEXT index. You obtain this information programatically with the CTX_QUERY.HFEEDBACK procedure.

Broader term, narrower term, and related term information is useful for suggesting other query terms to the user in your query application.

The returned feedback information is obtained from the knowledge base and contains only those terms that are also in the index. This process increases the chances that terms returned from HFEEDBACK produce hits over the currently indexed document set.

See Also:

Oracle Text Reference for more information about using CTX_QUERY.HFEEDBACK

6.2.4 Query Explain Plan

Explain plan information provides a graphical representation of the parse tree for a CONTAINS query expression. You can obtain this information programatically with the CTX_QUERY.EXPLAIN procedure.

Explain plan information tells you how a query is expanded and parsed without having the system execute the query. Obtaining explain information is useful for knowing the expansion for a particular stem, wildcard, thesaurus, fuzzy, soundex, or ABOUT query. Parse trees also show the following information:

  • Order of execution

  • ABOUT query normalization

  • Query expression optimization

  • Stopword transformations

  • Breakdown of composite-word tokens for supported languages

    See Also:

    Oracle Text Reference for more information about using CTX_QUERY.EXPLAIN

6.2.5 Using a Thesaurus in Queries

Oracle Text enables you to define a thesaurus for your query application and process queries more intelligently.

Because users might not know which words represent a topic, you can define synonyms or narrower terms for likely query terms. You can use the thesaurus operators to expand your query to include thesaurus terms.

6.2.6 Document Section Searching

Section searching enables you to narrow text queries down to sections within documents.

You can implement section searching when your documents have internal structure, such as HTML and XML documents. For example, you can define a section for the <H1> tag that enables you to query within this section by using the WITHIN operator.

You can set the system to automatically create sections from XML documents.

You can also define attribute sections to search attribute text in XML documents.


Section searching is supported for only word queries with a CONTEXT index.

6.2.7 Using Query Templates

Query templates are an alternative to the existing query languages. Rather than passing a query string to CONTAINS or CATSEARCH, you pass a structured document that contains the query string in a tagged element. Within this structured document, or query template, you can enable additional query features. Query Rewrite

Query applications sometimes parse end-user queries, interpreting a query string in one or more ways by using different operator combinations. For example, if a user enters a query of kukui nut, your application enters the {kukui nut} and {kukui or nut} queries to increase recall.

The query rewrite feature enables you to submit a single query that expands the original query into the rewritten versions. The results are returned with no duplication.

You specify your rewrite sequences with the query template feature. The rewritten versions of the query are executed efficiently with a single call to CONTAINS or CATSEARCH.

The following template defines a query rewrite sequence. The query of {kukui nut} is rewritten as follows:

{kukui} {nut}

{kukui} ; {nut}

{kukui} AND {nut}

{kukui} ACCUM {nut}

The following is the query rewrite template for these transformations:

select id from docs where CONTAINS (text,
   <textquery lang="ENGLISH" grammar="CONTEXT"> kukui nut
       <seq><rewrite>transform((TOKENS, "{", "}", " "))</rewrite></seq>
       <seq><rewrite>transform((TOKENS, "{", "}", " ; "))</rewrite></seq>
       <seq><rewrite>transform((TOKENS, "{", "}", "AND"))</rewrite></seq>
       <seq><rewrite>transform((TOKENS, "{", "}", "ACCUM"))</rewrite></seq>
  <score datatype="INTEGER" algorithm="COUNT"/>
</query>')>0; Query Relaxation

The query relaxation feature enables your application to execute the most restrictive version of a query first and progressively relax the query until the required number of hits are obtained.

For example, your application searches first on black pen and then the query is relaxed to black NEAR pen to obtain more hits.

The following query template defines a query relaxation sequence. The query of black pen is entered in sequence.

{black} {pen}

{black} NEAR {pen}

{black} AND {pen}

{black} ACCUM {pen}

The following is the query relaxation template for these transformations:

select id from docs where CONTAINS (text,
   <textquery lang="ENGLISH" grammar="CONTEXT">
       <seq>{black} {pen}</seq>
       <seq>{black} NEAR {pen}</seq>
       <seq>{black} AND {pen}</seq>
       <seq>{black} ACCUM {pen}</seq>
   <score datatype="INTEGER" algorithm="COUNT"/>

Query hits are returned in this sequence with no duplication as long as the application needs results.

Query relaxation is most effective when your application needs the top-N hits to a query, which you can obtain with the DOMAIN_INDEX_SORT hint or in a PL/SQL cursor.

Using query templating to relax a query is more efficient than reexecuting a query. Query Language

When you use MULTI_LEXER to index a column containing documents in different languages, you can specify which language lexer to use during querying. You do so by using the lang parameter in the query template, which specifies the document-level lexer.

select id from docs where CONTAINS (text,
'<query><textquery lang="french">bon soir</textquery></query>')>0;

See Also:

Oracle Text Reference for information on LANGUAGE and lang with ALTER INDEX and document sublexer Ordering by SDATA Sections

You can order the query results according to the content of SDATA sections by using the <order> and <orderkey> elements of the query template.

In the following example, the first level of ordering is performed on the SDATA price section, which is sorted in ascending order. The second and third level of ordering are performed by the SDATA pub_date section and score, both of which are sorted in descending order.

select id from docs where CONTAINS (text, '
   <textquery lang="ENGLISH" grammar="CONTEXT"> Oracle </textquery>
   <score datatype="INTEGER" algorithm="COUNT"/>
       <orderkey> SDATA(price) ASC </orderkey>
       <orderkey> SDATA(pub_date) DESC </orderKey>
       <orderkey> Score DESC </orderkey>
</query>', 1)>0;


  • You can add additional SDATA sections to an index. Refer to the ADD SDATA SECTION parameter string under ALTER INDEX in Oracle Text Reference.

  • Documents that were indexed before adding an SDATA section do not reflect this new preference. Rebuild the index in this case.

See Also:

Oracle Text Reference for syntax of <order> and <orderkey> elements of the query template Alternative and User-Defined Scoring

You can use query templating to specify alternative scoring algorithms. Those algorithms help you customize how CONTAINS is scored. They also enable SDATA to be used as part of the scoring expressions. In this way, you can mathematically define the scoring expression by using not only predefined scoring components, but also SDATA components.

With alternative user-defined scoring, you can specify:

  • Scoring expressions of terms by defining arithmetic expressions that define how the query should be scored, using

    • predefined scoring algorithms: DISCRETE, OCCURRENCE, RELEVANCE, and COMPLETION

    • arithmetic operations: plus, minus, multiply, divide

    • arithmetic functions: ABS(n), finding the absolute value of n ; LOG(n), finding the base-10 logarithmic value of n

    • Numeric literals

  • Scoring expressions at the term level

  • Terms that should not be taken into account when calculating the score

  • How the score from child elements of OR and AND operators should be merged

  • Use

You can also use the SDATA that stores numeric or DATETIME values to affect the final score of the document.

The following example specifies an alternative scoring algorithm:

select id from docs where CONTAINS (text,
 <textquery grammar="CONTEXT" lang="english"> mustang  </textquery>     
 <score datatype="float" algorithm="DEFAULT"/>     

The following query templating example includes SDATA values as part of the final score:

select id from docs where CONTAINS (text,
<textquery grammar="CONTEXT" lang="english"> mustang </textquery>
<score datatype="float" algorithm="DEFAULT" normalization_expr ="doc_score+SDATA(price)"/>
</query>')>0" Alternative Grammar

Query templating enables you to use the CONTEXT grammar with CATSEARCH queries and vice versa.

select id from docs where CONTAINS (text,
  <textquery grammar="CTXCAT">San Diego</textquery>
  <score datatype="integer"/>

6.2.8 Query Analysis

Oracle Text enables you to create a log of queries and to analyze the queries. For example, suppose you have an application that searches a database of large animals, and your analysis of its queries shows that users search for the word mouse. This analysis shows you that you should rewrite your application to avoid returning an unsuccessful search. Instead, a search for mouse redirects users to a database of small animals.

With query analysis, you can find out:

  • Which queries were made

  • Which queries were successful

  • Which queries were unsuccessful

  • How many times each query was made

You can combine these factors in various ways, such as determining the 50 most frequent unsuccessful queries made by your application.

You start query logging with CTX_OUTPUT.START_QUERY_LOG. The query log contains all queries made to all CONTEXT indexes that the program is using until a CTX_OUTPUT.END_QUERY_LOG procedure is entered. Use CTX_REPORT.QUERY_LOG_SUMMARY to get a report of queries.

See Also:

Oracle Text Reference for syntax and examples for these procedures

6.2.9 Other Query Features

In your query application, you can use other query features such as proximity searching. Table 6-1 lists some of these features.

Table 6-1 Other Oracle Text Query Features

Feature Description Implement With

Case-Sensitive Searching

Enables you to search on words or phrases exactly as they are entered in the query. For example, a search on Roman returns documents that contain Roman and not roman.

BASIC_LEXER when you create the index

Base-Letter Conversion

Queries words with or without diacritical marks such as tildes, accents, and umlauts. For example, with a Spanish base-letter index, a query of energía matches documents containing both energía and energia.

BASIC_LEXER when you create the index

Word Decompounding

(German and Dutch)

Enables searching on words that contain the specified term as subcomposite.

BASIC_LEXER when you create the index

Alternate Spelling

(German, Dutch, and Swedish)

Searches on alternate spellings of words.

BASIC_LEXER when you create the index

Proximity Searching

Searches for words near one another.

NEAR operator when you enter the query

Expanded operator containing the functionality of PHRASE, NEAR and AND operators.

Breaks a document into clumps based on the given query. Each clump is classified based on a primary feature, and is scored based on secondary features. The final document score adds clump scores such that the ordering of primary features determines the initial ordering of document scores.

NEAR2 operator when you enter the query


Searches for words with the same root as the specified term.

$ operator at when you enter the query

Fuzzy Searching

Searches for words that have a similar spelling as the specified term.

FUZZY operator when you enter the query

Query Explain Plan

Generates query parse information.

CTX_QUERY.EXPLAIN PL/SQL procedure after you index

Hierarchical Query Feedback

Generates broader term, narrower term and related term information for a query.

CTX_QUERY.HFEEDBACK PL/SQL procedure after you index

Browse index

Browses the words around a seed word in the index.


Count hits

Counts the number of hits in a query.

CTX_QUERY.COUNT_HITS PL/SQL procedure after you index

Stored Query Expression

Stores the text of a query expression for later reuse in another query.

CTX_QUERY.STORE_SQE PL/SQL procedure after you index

Thesaural Queries

Uses a thesaurus to expand queries.

Thesaurus operators such as SYN and BT as well as the ABOUT operator

(Use CTX_THES package to maintain the thesaurus.)