Vertica tokenizers

• 1: Preconfigured tokenizers
• 2: ICU tokenizer

1 - Preconfigured tokenizers

The Vertica Analytics Platform provides the following preconfigured tokenizers:

public.FlexTokenizer(LONG VARBINARY)

Splits the values in your flex table by white space.

v_txtindex.StringTokenizer(LONG VARCHAR)

Splits the string into words by splitting on white space.

v_txtindex.StringTokenizerDelim(LONG VARCHAR, CHAR(1))

Splits a string into tokens using the specified delimiter character.

Vertica also provides the following tokenizer, which is not preconfigured:

v_txtindex.ICUTokenizer

Supports multiple languages. Tokenizes based on the conventions of the language you set in the locale parameter. For more information, see ICU Tokenizer.

Examples

The following examples show how you can use a preconfigured tokenizer when creating a text index.

Use the StringTokenizer to create an index from the top_100:

=> CREATE TEXT INDEX idx_100 FROM top_100 on (id, feedback)
                TOKENIZER v_txtindex.StringTokenizer(long varchar)
                 STEMMER v_txtindex.StemmerCaseInsensitive(long varchar);

Use the FlexTokenizer to create an index from unstructured data:

=> CREATE TEXT INDEX idx_unstruc FROM unstruc_data on (__identity__, __raw__)
                                 TOKENIZER public.FlexTokenizer(long varbinary)
                                    STEMMER v_txtindex.StemmerCaseSensitive(long varchar);

Use the StringTokenizerDelim to split a string at the specified delimiter:

=> CREATE TABLE string_table (word VARCHAR(100), delim VARCHAR);
CREATE TABLE
=> COPY string_table FROM STDIN DELIMITER ',';
Enter data to be copied followed by a newline.
End with a backslash and a period on a line by itself.
>>
>> SingleWord,dd
>> Break On Spaces,' '
>> Break:On:Colons,:
>> \.
=> SELECT * FROM string_table;
            word | delim
-----------------+-------
      SingleWord | dd
 Break On Spaces |
 Break:On:Colons | :
(3 rows)

=> SELECT v_txtindex.StringTokenizerDelim(word,delim) OVER () FROM string_table;
      words
-----------------
 Break
 On
 Colons
 SingleWor
 Break
 On
 Spaces
(7 rows)

=> SELECT v_txtindex.StringTokenizerDelim(word,delim) OVER (PARTITION BY word), word as input FROM string_table;
           words | input
-----------------+-----------------
           Break | Break:On:Colons
              On | Break:On:Colons
          Colons | Break:On:Colons
       SingleWor | SingleWord
           Break | Break On Spaces
              On | Break On Spaces
          Spaces | Break On Spaces
(7 rows)

2 - ICU tokenizer

Supports multiple languages. You can use this tokenizer to identify word boundaries in languages other than English, including Asian languages that are not separated by whitespace.

The ICU Tokenizer is not pre-configured. You configure the tokenizer by first creating a user-defined transform Function (UDTF). Then set the parameter, locale, to identify the language to tokenizer.

Parameters

Example

The following example steps show how you can configure the ICU Tokenizer for simplified Chinese, then create a text index from the table foo, which contains Chinese characters.

For more on how to configure tokenizers, see Configuring a tokenizer.

1. Create the tokenizer using a UDTF. The example tokenizer is named ICUChineseTokenizer.

   VMart=> CREATE OR REPLACE TRANSFORM FUNCTION v_txtindex.ICUChineseTokenizer AS LANGUAGE 'C++' NAME 'ICUTokenizerFactory' LIBRARY v_txtindex.logSearchLib NOT FENCED;
   CREATE TRANSFORM FUNCTION
   

2. Get the procedure ID of the tokenizer.

   VMart=> SELECT proc_oid from vs_procedures where procedure_name = 'ICUChineseTokenizer';
        proc_oid
   -------------------
    45035996280452894
   (1 row)
   

3. Set the parameter, locale, to simplified Chinese. Identify the tokenizer using its procedure ID.

   VMart=> SELECT v_txtindex.SET_TOKENIZER_PARAMETER('locale','zh_CN' using parameters proc_oid='45035996280452894');
    SET_TOKENIZER_PARAMETER
   -------------------------
    t
   (1 row)
   

4. Lock the tokenizer.

   VMart=> SELECT v_txtindex.SET_TOKENIZER_PARAMETER('used','true' using parameters proc_oid='45035996273762696');
    SET_TOKENIZER_PARAMETER
   -------------------------
    t
   (1 row)
   

5. Create an example table, foo, containing simplified Chinese text to index.
   

   VMart=> CREATE TABLE foo(doc_id integer primary key not null,text varchar(250));
   CREATE TABLE
   
   VMart=> INSERT INTO foo values(1, u&'\4E2D\534E\4EBA\6C11\5171\548C\56FD');
    OUTPUT
   --------
         1
   

6. Create an index, index_example, on the table foo. The example creates the index without a stemmer; Vertica stemmers work only on English text. Using a stemmer for English on non-English text can cause incorrect tokenization.
   

   VMart=> CREATE TEXT INDEX index_example ON foo (doc_id, text) TOKENIZER v_txtindex.ICUChineseTokenizer(long varchar) stemmer none;
   CREATE INDEX
   

7. View the new index.
   

   VMart=> SELECT * FROM index_example ORDER BY token,doc_id;
    token  | doc_id
   --------+--------
    中华    |      1
    人民   |      1
    共和国 |      1
   (3 rows)